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A systems biology study to tailored treatment in chronic heart failure

Ouwerkerk, W.

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Citation for published version (APA):Ouwerkerk, W. (2017). A systems biology study to tailored treatment in chronic heart failure

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Download date: 27 Aug 2018

SUMMARY OF FINDINGS

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The aim of this thesis was to identify patients at low or high risk of mortality and/orheart failure-related hospitalization, and patients who were likely or not likely to achieve ESC-recommended pharmaceutical treatment.

Part IFirst, a meta-analysis in Chapter 2 found 117 different prediction models, using 249 distinctpredictor variables. The best predictors were: blood urea nitrogen (BUN), presence of cancer, tro-ponin, serum creatinine, systolic blood pressure (SBP) and sodium. These predictors have beenused often before in prediction models, but frequently supported by easy collectable predictorssuch as age and gender. The published prediction models performed moderately for mortality,but exhibited poor performance in predicting heart failure-related hospitalization, and in predict-ing the first occurrence of heart failure-related hospitalization or death. In addition to predictingmortality, better c-statistic values were achieved in models using more variables, data acquired inprospective clinical studies, and data from a registry type data source. Not surprisingly, modelspredicting events over a shorter time span also resulted in more accurate predictions.

We developed new prediction models in Chapter 3, predicting mortality, heart failure-relatedhospitalization and the first occurrence of heart failure-related hospitalization or death. In ourmodel development process, we used only 42 easily obtainable variables. We found that ourmodels performed as well as existing models. C-statistic values of our models were 0.73, 0.68,0.70 for predicting mortality, heart failure hospitalization and the first occurrence of heart fail-ure hospitalization or death, respectively. These models consisted of 16, 10, and 15 predictorvariables, respectively. To make our models more usable in daily clinical practice, we limited thenumber of variables in the models to 5 for predicting mortality and heart failure hospitalization,and 9 for the composite endpoint. This model reduction let to reduced c-statistic values (0.69,0.66, 0.69, respectively). The mortality model consisted of: age, BUN, N-terminal pro B-typenatriuretic peptide (NT-proBNP), hemoglobin, and the use of beta-blockers at time of inclusioninto the study. Variables in the heart failure hospitalization model consisted of: age, heartfailure hospitalization in the year before inclusion, peripheral edema and estimated glomerularfiltration rate (eGFR). The combined model comprised variables from both the mortality andheart failure hospitalization model, with the exception of eGFR and BUN, and the addition ofhigh density lipoprotein (HDL)-cholesterol and sodium. External validation of both the full andcompact model performance gave comparable results in the validation cohort. We also developedan online calculator where individual survival curves can be calculated using the reduced models.We also developed a point score model from the reduced models, which can easily be calculatedby adding a point for each variable reaching specific cut-off value in those cases when the onlinecalculator could not be consulted. Because heart failure with reduced ejection fraction (HFrEF)and heart failure with preserved ejection fraction (HFpEF) patients are different, we looked atthe difference in prediction performance between them. There were differences in c-statistic val-ues between these two groups in the index cohort, but these differences were not observed in thevalidation cohort.

European Society of Cardiology (ESC)-recommended angiotensin-converting-enzyme inhibitor(ACE-inhibitor)/angiotensin II receptor blocker (ARB) and beta-blocker treatment doses werebased on results from large randomized controlled trials, and showed that higher doses were asso-ciated with better survival. In Chapter 4 we developed models to identify patients who wouldlikely achieve lower or higher doses of recommended pharmaceutical treatment. We could confirmthat achieving lower ACE-inhibitor/ARB and beta-blocker doses (<50% of recommended treat-ment dose) resulted in significantly worse survival. There was no significant difference in survivalbetween patients who reach 50-99% of recommended dose and those who achieved the recom-

162 Summary of findings

mended doses for beta-blockers, and only marginally significant differences for ACE-inhibitors/ARBs. Despite the incentive to up-titrate patients to ESC-recommended doses, only 22% and12% of patients achieved recommended ACE-inhibitor/ARB and beta-blocker doses, respectively.The number of patients achieving recommended ACE-inhibitor/ARB and beta-blocker doses werelower than reported in randomized controlled trials. We also looked at reasons why patients werenot up-titrated to recommended doses. Unfortunately, in most cases, no specific reason was givenfor the lack of up-titration. But we did observe that patients who did not reach recommendeddoses due to drug-intolerance had worse survival. There was no significant difference in survivalbetween patients who achieved recommended beta-blocker dose and patients who did not reachrecommended beta-blocker doses for other reasons.

Only a small portion of patients achieved recommended ACE-inhibitor/ARB and beta-blockertreatment doses; most patients did not. These patients did not fully benefit from treatment, butdid endure the negative effects of pharmaceutical treatment. In Chapter 5 we developed atreatment-selection model to determine if a patient should or should not be up-titrated to ≥50%of recommended treatment dose. We evaluated three different hypothetical treatment scenario’s:Scenario A) where all patients were successfully treated; scenario B) where our biomarker-based-model determined if a patient was up-titrated or not, and scenario C) where all patients weresub-optimally treated. First, we developed two models to estimate mortality and/or heart failurehospitalization in patients up-titrated to ≥50% of recommended treatment dose, and in patientsnot up-titrated to that level for both ACE-inhibitor/ARB and beta-blocker. Secondly, we pre-dicted the risk of death and/or heart failure hospitalization for each patient using both models.For Scenario B), the lowest hazard on death and/or heart failure hospitalization out of bothmodels, for each patient, was chosen. Scenario C), where all patients were sub-optimally treated,had the highest event-rate. Scenario B), where all patients were treated according to a biomarker-based-model, had the least number of events. The difference with scenario A), where all patientswere optimally treated, was minor, however, with a large error estimation. Our recommendation,therefore, is to start up-titration in all patients, regardless of the biomarker profile.

Part II

Heart failure is known to be heterogeneous in nature. Cluster methods are frequently and suc-cessfully applied to group patients based on clinically meaningful phenotypes. The use of clusteralgorithms has been criticized in connection with their robustness and reproducibility. In Chap-ter 6 we compared four well-established cluster methods (gaussian mixture for model-basedclustering (Mclust), polytomous latent class analysis (poLCA), partitioning around k-medoids(PAM) and hierarchical cluster analysis (Hclust)). We found that the number of created clustersvaried over the different methods, ranging from 4 (Hclust) to 20 (PAM). Cohen’s kappa was high-est for poLCA in determining clusters and in reproducing clusters in the index cohort. Cohen’skappa was highest for Hclust in reproducing clusters in validation cohort. Clusters produced byMclust and PAM did not only had low Cohen’s kappa values, but also differed in survival andclinical characteristics between index and validation cohorts, where poLCA and Hclust clustersshowed similar results between the clusters in these cohorts. This chapter showed that differentclustering methods gave different results depending on the methods as well as on the variablesused for input. We proposed a step-wise approach to ensure more clinical relevant and robustresults by assessing:

• The number and type of variables, handling of missing data should be well chosen

• Data redundancy should be taken care of

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• Clustering results should be evaluated for robustness, independent reproducibility as wellas clinical implications of the results

We performed our own unsupervised cluster analyses (PAM) in Chapter 7, using the ap-proach suggested in Chapter 6, to distinguish relevant heart failure subtypes. We used principalcomponents with eigenvalue >1, from a principal component analysis (PCA) of 92 pathophys-iological biomarkers in BIOSTAT-CHF. We found 8 different subgroups (endotypes), all witha distinctive biomarker profiles and phenotypes. These endotypes also differed in up-titrationrates, survival, and treatment benefit. We found one and three endotypes that did not profit fromup-titration to ESC-recommended treatment doses for ACE-inhibitors/ARBs and beta-blockers,respectively. We were able to identify patients to endotypes based on only a small numberof biomarker values. Furthermore, we could validate these results in the separate independentvalidation cohort of BIOSTAT-CHF.

In Chapter 8 we introduced a probabilistic formulation of the alternative splicing recon-struction problem, using a finite mixture model based on the maximum likelihood principle ingene-expression data. A systematic approach was used to determine the probability of the pres-ence of splice variants. Our model was based on the assumption that the expected expressionlevel of exons in a particular splice variant is the same for all exons in that variant, but the modelallowed measurement error. The number of possible splice variants in our model was dependenton the number of exons in the gene. With small genes, all splice variants were analyzed, includ-ing biologically improbable variants. These variants were also given low prevalence in the results.For larger genes we used a scenario-based method to analyze possible splice variants. With thismethod, the improbable splice variants were already excluded. Our model showed good perfor-mance in simulations. Using our model, we found four possible splice variants not yet present ingene databases, but possibly present in three genes in Marfan syndrome patients.

In Chapter 9 we developed a penalized canonical correlation analysis (pCCA) to ana-lyze multiple high-dimensional biological data sets, such as genetic and methylation markers,(mi)ribonucleic acid (RNA), protein and peptide expression measurements and phenotypes, allmeasured on the same sample of individuals. The results are described by sparse canonical vari-ates featuring highly associated markers, molecules and phenotypes. When the multiple datasets are (epi)genetic markers, RNA, protein and peptide expression variables and phenotypes,the set of canonical variates and associated variables should correspond to nodes in pathogenetic-molecular pathways that describe the sequential transfer of information from deoxyribonucleicacid (DNA), its transcription to messenger ribonucleic acid (mRNA), its translation and to pro-teins and peptides and their metabolism into metabolites to observable (disease) phenotypes.Applying pCCA to the BIOSTAT-CHF study, we demonstrated that heart failure phenotypes(mortality, heart failure hospitalization and treatment success) of 2,245 patients could be welldescribed by associated canonical variates in genetic, proteomic and metabolomic spaces, sug-gesting key biological processes in heart failure. In this data example we used genetic, genomic,known heart failure (bio-)markers, and phenotypic variables. The pCCA method has a two-stage approach. In the first stage we determined the optimal penalty parameters by 10-foldcross-validation, after which we determined the final canonical variates and enriched the data byexploring knowledge bases. We extracted eight canonical variates, and did the enrichment forone of them. We found that this canonical variate was involved in the GPCR pathway, a groupof membrane receptors which is targeted by 40% of all modern drugs, including ACE-inhibitors/ARBs and beta-blockers. Given that we identified these relevant signals in heart failure patients,we concluded that pCCA is a useful statistical tool to jointly analyze phenotypic and variousomics data gathered from the same samples of patients.

SAMENVATTING

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Het doel van dit proefschrift was om patiënten te identificeren die een laag of hoog risicohebben op overlijden en/of aan hartfalen gerelateerde ziekenhuisopname en patiënten die de doorde ESC aanbevolen medicamenteuze behandeling waarschijnlijk wel of niet verdragen.

Deel IIn een meta-analyse in Hoofdstuk 2, hebben we 117 verschillende predictie modellen gevondenmet in totaal 249 verschillende variabelen. De best voorspellende variabelen waren: BUN, hethebben van kanker, troponine, serum creatinine, SBP en natrium. Deze variabelen werden danook vaak gebruikt in predictie modellen, samen met variabelen die makkelijk te verzamelen zijn,zoals leeftijd en geslacht. De gepubliceerde modellen hadden een acceptabele accuraatheid in hetvoorspellen van het risico op overlijden, maar het voorspellen van ziekenhuisopname en de gecom-bineerde uitkomst van overlijden en/of ziekenhuisopname waren slechter. Naast het voorspellenvan overlijden, werden meer accurate voorspellingen gedaan wanneer gebruik werd gemaakt vanmeerdere variabelen, data uit prospectieve studies, klinische data, en data uit registratieonder-zoek. En niet geheel onverwacht was het voorspellen van uitkomsten voor een kortere periodemakkelijker dan voor een langere.

We hebben in Hoofdstuk 3 nieuwe predictie modellen ontwikkelt voor het voorspellen vanoverlijden, aan hartfalen gerelateerde ziekenhuisopname, en de gecombineerde uitkomst van over-lijden en/of aan hartfalen gerelateerde ziekenhuisopname. Voor het ontwikkelen van onze mo-dellen hebben we gebruik gemaakt van 42 variabelen die in de dagelijkse praktijk standaardgedocumenteerd worden. We vonden dat onze modellen net zo goed voorspelden als reeds ge-publiceerde modellen. C-statistiek waarden van onze modellen waren respectievelijk 0.73, 0.68,0.70 voor het voorspellen van overlijden, aan hartfalen gerelateerde ziekenhuisopname, en de ge-combineerde uitkomst van overlijden en/of aan hartfalen gerelateerde ziekenhuisopname. Dezemodellen bestonden uit 16, 10 en 15 variabelen. Om onze modellen makkelijker toepasbaar temaken in de dagelijkse praktijk hebben we het aantal variabelen terug gebracht naar 5 voorhet overlijden- en ziekenhuisopname-model en 9 voor de gecombineerde uitkomst. Deze reductieverlaagde de c-statistiek waarden naar respectievelijk 0.69, 0.66, en 0.69. Het overlijdens-modelbestond uit: leeftijd, BUN, NT-proBNP, hemoglobine, en het gebruik van beta-blockers op hetmoment van inclusie in de studie. Het model dat hartfalen gerelateerde ziekenhuisopname voor-spelde bestond uit: Leeftijd, hartfalen gerelateerde ziekenhuisopname in het jaar voorafgaandaan de inclusie in de studie, perifeer oedeem, SBP en eGFR. Het model voor de gecombineerdeuitkomst bestond uit de combinatie van beide vorige modellen, waarbij eGFR en BUN werdenverwijderd en HDL-cholesterol en natrium werden toegevoegd. We konden de resultaten vanzowel de volledige en de gereduceerde modellen goed reproduceren in het validatie cohort. Ookhebben we een online calculator gemaakt waar individuele overleving-curves uitgerekend kunnenworden. Als toevoeging bij de online calculator hebben we point score modellen ontwikkeld ge-baseerd op de gereduceerde modellen, deze kunnen makkelijk berekend worden door het optellenvan het aantal variabelen dat een bepaalde waarde bereikt. Omdat HFrEF en HFpEF patiëntenverschillen, hebben we ook gekeken naar het verschil in kwaliteit van de voorspellingen tussenHFrEF en HFpEF patiënten. Er waren verschillen tussen de kwaliteit van de voorspellingen indeze twee groepen in het index cohort, deze verschillen waren niet te zien in het validatie cohort.

De door het ESC aanbevolen medicamenteuze ACE-inhibitor/ARB en beta-blocker doses zijngebaseerd of grote gerandomiseerde klinische onderzoeken (RCTs) en hebben laten zien dat ho-gere doseringen tot betere overleving leiden. In Hoofdstuk 4 hebben we modellen gemaakt ompatiënten te identificeren die waarschijnlijk een lagere of hogere dosis zouden behalen. We kon-den bevestigen dat lagere ACE-inhibitor/ARB en beta-blocker doses (<50% van de aanbevolendosis) resulteerde in een significant lagere overleving. Er was geen significant verschil in overle-

168 Samenvatting

ving tussen patiënten die 50-99% van de aanbevolen beta-blocker doses haalden, en slechts eenmarginaal significant verschil voor ACE-inhibitors/ARBs doses. Ondanks dat artsen werden aan-gemoedigd om patiënten naar ESC aanbevolen doses op te titreren haalden slechts 22% en 12%van de patiënten de aanbevolen doses voor respectievelijk ACE-inhibitor/ARB en beta-blocker.Het aantal mensen dat aanbevolen doses haalde was lager dan we aanvankelijk verwachtten opbasis van de RCTs. We hebben ook gekeken naar redenen waarom de patiënten niet werdenopgetitreerd naar de aanbevolen doses. Helaas werd er vaker niet dan wel een reden opgegevenvoor het niet optitreren van een patiënt. We vonden wel dat patiënten die de aanbevolen dosesniet haalden omdat ze de medicatie niet konden tolereren een slechtere overleving hadden. Erwas geen significant verschil in overleving tussen patiënten die de aanbevolen beta-blocker dosishaalden en patiënten die de aanbevolen beta-blocker dosis niet haalden om andere redenen.

Slechts een klein deel van de patiënten haalden de aanbevolen ACE-inhibitor/ARB en beta-blocker doses, de meeste patiënten ondervonden daarmee niet de voordelen van de medicamen-teuze behandeling, maar wel de nadelige gevolgen. In Hoofdstuk 5 hebben we gekeken of wekonden de keuze - welke patiënten we wel en welke we niet moesten gaan optitreren - kondenvoorspellen. We hebben een model gemaakt om de kijken welke van drie hypothetische scenario’sde beste was: scenario A) alle patiënten werden succesvol behandeld, scenario B) optitreren ofniet wordt gebaseerd op basis van een biomarker waarden, scenario C) alle patiënten wordensub-optimaal behandeld (<50% aanbevolen doses). Allereest hebben we modellen ontwikkeld omhet overlijden en/of ziekenhuisopname te schatten in succesvol en niet succesvol opgetitreerdepatiënten voor zowel ACE-inhibitor/ARB en beta-blocker. Succesvol optitratie was, op basisvan de resultaten uit Hoofdstuk 4, gedefinieerd als optitratie naar ≥50% van aanbevolen ACE-inhibitor/ARB en beta-blocker doses. Daarna hebben we voor alle patiënten het risico op over-lijden en/of ziekenhuisopname geschat in beide modellen. Scenario B) werd gevormd door voorelke patiënt het laagte risico te nemen van beide modellen. Scenario C), waarin alle patiëntensub-optimaal werden behandeld, had het hoogste aantal events. Scenario B), waar alle patiëntenwerden behandeld aan de hand van onze biomarker-modellen, had het minst aantal events. Hetverschil met scenario A), waar alle patiënten optimaal behandeld werden, was klein en had eenvrij grote foutmarge. Ons advies luidt daarom om bij alle patiënten te starten met optitrerennaar de aanbevolen doses.

Deel IIHartfalen is een heterogene ziekte. Cluster-methoden zijn regelmatig en succesvol toegepastom patiënten te groeperen op basis van klinisch relevante fenotypes. Het gebruik van dit soortcluster-methoden wordt echter bekritiseerd door het gebrek van robuustheid en reproduceerbaar-heid. In Hoofdstuk 6 hebben we vier bekende veel gebruikte cluster-methoden (normal mixturemodelling (Mclust), latente klasse analyse (poLCA), PAM and hiërarchisch clustering (Hclust))vergeleken. We vonden dat het aantal gevonden clusters varieerde tussen 4 (Hclust) en 20 (PAM).Cohen’s kappa waarden voor het opstellen van de clusters en in het reproduceren van clusters inhet index cohort waren het hoogst voor poLCA. Cohen’s kappa waarden waren het hoogst voorHclust in het reproduceren van clusters in het validatie cohort. Clusters in Mclust en PAM had-den niet alleen lage Cohen’s kappa waarden, maar verschilde ook in klinische karakteristieken enprognose tussen het index en validatie cohort. poLCA en Hclust clusters lieten hier meer verge-lijkbare resultaten zien. In dit hoofdstuk hebben we laten zien dat cluster-methoden verschillenderesultaten laten zien aan de hand van verschillende methodes en variabelen die gebruikt worden.We hebben een methode voorgesteld dat moet zorgen voor een meer klinisch relevant en robuustresultaat:

1. Het aantal en type variabelen, hoe om te gaan met missende data moet wel overwogen

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worden

2. Er moet met data redundancy worden afgerekend

3. Cluster resultaten moeten worden beoordeeld op robuustheid, onafhankelijke reproduceer-baarheid en klinische relevantie

In Hoofdstuk 7 hebben we onze eigen cluster analyse uitgevoerd (PAM), waar we de me-thode voorgesteld in Hoofdstuk 6 hebben gebruikt om onderscheidt te maken tussen hart falensubtypen (endotypen). We gebruikten principale componenten met een eigenwaarde >1, uit eenprincipale-componentenanalyse (PCA) van 92 biomarkers in BIOSTAT-CHF. We vonden 8 ver-schillende endotypen, allen met een kenmerkend biomarker profiel en fenotypen. Patiënten indeze endotypen verschilden in optitratie, overleving, en profijt van medicamenteuze behandeling.We vonden één en drie endotypen die geen profijt hadden bij optitratie naar ESC aanbevolendoses voor respectievelijk ACE-inhibitors/ARBs en beta-blockers. We konden patiënten aan en-dotypen koppelen op basis van slechts een klein aantal biomarkers. Ook konden we de gevondenresultaten goed reproduceren in het validatie cohort van BIOSTAT-CHF.

In Hoofdstuk 8 hebben we een methode bedacht om het alternatieve splicing reconstructieprobleem in gen-expressie data op te lossen. We hebben hier een mixture model voor gebruikdat gebaseerd is op het maximum likelihood principe. We hebben op een systematische maniergeprobeerd om de waarschijnlijkheid van een bepaalde splice variant te schatten. Ons modelwas gebaseerd op de assumptie dat de verwachtte expressie van één exon in een willekeurigesplice variant gelijk is voor alle exonen in die variant, maar met een bepaalde foutmarge. Hetaantal mogelijke splice varianten in ons model was afhankelijk van het aantal exonen in een gen.Bij kleine genen werden alle varianten geanalyseerd, inclusief de biologisch onwaarschijnlijkevarianten. Deze varianten kregen een lage prevalentie in onze resultaten. In grotere genengebruikten we een selectie van verschillende scenario’s van mogelijke splice varianten. In dezescenario’s konden de onwaarschijnlijke splice varianten weg gelaten worden. In simulaties gaf onsmodel een accurate schattingen. Met dit model hebben we vier mogelijk splice varianten gevondenin drie genen, die niet in de genetische databases staan, in patiënten met Marfan syndroom.

In Hoofdstuk 9 hebben we een penalized canonical correlation analysis (pCCA) om meer-dere hoog dimensionale biologische datasets te analyseren, bijvoorbeeld genetische en methylatiemarkers, (mi)RNA, eiwit en peptide expressie en fenotypen, gemeten in dezelfde individuen. Deresultaten worden weergegeven door sparse canonische variaten bestaande uit hoog-correlerendemarkers, moleculen en fenotypen. Wanneer de verschillende datasets bestaan uit (epi)genetischemarkers, RNA, eiwitten en peptide expressie variabelen en fenotypen, corresponderen de cano-nische varianten en de geassocieerde variabelen met de punten in de onderlinge pathogenetische-moleculaire pathways. Deze beschrijven het process van DNA, DNA transcriptie naar mRNA,en de translatie en proteïnen en peptiden en de metabolisme naar metabolieten en uiteindelijknaar observeerbare (ziekte-)fenotypen. Wanneer we pCCA toepasten op 2,245 BIOSTAT-CHFpatiënten, zagen we dat fenotypen voor hartfalen (overlijden, door hartfalen gerelateerde zie-kenhuisopname, en succesvolle behandeling) goed konden worden beschreven door geassocieerdecanonische variaten in genetische, proteomische en metabolische datasets. Onze pCCA bestaatuit twee facetten. Als eerste bepaalden we de optimale penalty parameters door 10-splits kruis-validatie, waarna we de uiteindelijke canonische variaten bepaalden. Vervolgens, werd er opdeze variaten nog een enrichment gedaan door bekende databanken door te zoeken. We heb-ben acht variaten berekend en hebben de enrichment voor één van hen uitgevoerd. We vondendat deze canonische variaat was betrokken bij de GPCR pathway, welke bestaat uit een groepvan cell-membraan receptoren en 40% van alle moderne medicatie is hier op gericht, inclusiefACE-inhibitor/ARB en beta-blocker. Dat we deze relevante resultaten vonden in patiënten met

170 Samenvatting

hartfalen, geeft aan dat pCCA een goede statistische methode is om fenotypen en verschillendeomic datasets gezamenlijk te analyseren.

LIST OF CONTRIBUTING AUTHORS

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Stefan D. Anker, MD, PhDInnovative Clinical Trials, Department of Cardiology and Pneumology,University Medical Centre Göttingen (UMG), Göttingen, Germany

John G.F. Cleland, MD, PhDNational Heart & Lung Institute, Royal Brompton and Harefield Hospitals,Imperial College, London, UK

Biniyam G. Demissei, MD, PhDUniversity of Groningen, University Medical Center Groningen, The Netherlands

Kenneth Dickstein, MD, PhDUniversity of Stavanger, Stavanger, Norway andUniversity of Bergen, Bergen, Norway

Gerasimos Filippatos, MD, PhDDepartment of Cardiology, Heart Failure Unit,Athens University Hospital Attikon, Athens, Greece

Pim van der Harst, MD, PhDDepartment of Cardiology, University of Groningen, Groningen, the Netherlands

Hans L. Hillege, MD, PhDDepartment of Cardiology, University of Groningen, Groningen, the Netherlands

Michel H. Hof, PhDDepartment of Epidemiology, Biostatistics and Bioinformatics,Academic Medical Centre, Amsterdam, the Netherlands

Mohsin A.F Khan, PhDDepartment of Cardiology, Academic Medical Centre, Amsterdam, the Netherlands

Chim C. Lang, MD, PhDSchool of Medicine Centre for Cardiovascular and Lung Biology,Division of Medical Sciences,University of Dundee, Ninewells Hospital & Medical School, Dundee, UK

Peter van der Meer, MD, PhDDepartment of Cardiology, University of Groningen, Groningen, the Netherlands

Jozine M. ter Maaten, MD, PhDDepartment of Cardiology, University of Groningen, Groningen, the Netherlands

Marco Metra, MD, PhDInstitute of Cardiology, Department of Medical and Surgical Specialties,Radiological Sciences and Public Health, University of Brescia, Italy

176 List of contributing authors

Leong L. Ng, MD, PhDDepartment of Cardiovascular Sciences, University of Leicester, Glenfield Hospital andCardiovascular Theme, NIHR Leicester Biomedical Research Centre,Glenfield Hospital, Leicester, UK

Piotr Ponikowski, MD, PhDDepartment of Heart Diseases,Wroclaw Medical University, Poland andCardiology Department, Military Hospital, Wroclaw, Poland

Michiel Rienstra, MD, PhDDepartment of Cardiology, University of Groningen, Groningen, the Netherlands

Nilesh J. Samani, MD, PhDDepartment of Cardiovascular Sciences, University of Leicester, Glenfield Hospital andCardiovascular Theme, NIHR Leicester Biomedical Research Centre,Glenfield Hospital, Leicester, UK

Jasper Tromp, MDDepartment of Cardiology, University of Groningen, Groningen, the Netherlands

Dirk-Jan van Veldhuisen, MD, PhDDepartment of Cardiology, University of Groningen, Groningen, the Netherlands

Adriaan A. Voors, MD, PhDDepartment of Cardiology, University of Groningen, Groningen, the Netherlands

Faiez Zannad, MD, PhDInserm CIC 1433, Université de Lorrain, CHU de Nancy, Nancy, France

Aeilko H. Zwinderman, PhDDepartment of Epidemiology, Biostatistics and Bioinformatics,Academic Medical Centre, Amsterdam, the Netherlands

ACKNOWLEDGEMENTS

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Een proefschrift schrijven is een project dat mijn leven zowel op wetenschappelijk, profes-sioneel als op sociaal gebied enorm veranderd heeft. Dit proces heb ik uiteraard niet alleenkunnen doorlopen en is in grote mate een resultaat dat ontstaan is door bijdrage van veel ver-schillende mensen. Ik wil daarom iedereen bedanken die, in welke vorm dan ook, een aandeelheeft gehad aan de totstandkoming van dit proefschrift. Ik wil hier dan ook van de gelegenheidgebruik maken om een aantal personen in het bijzonder te bedanken voor hun bijdrage aan ditproefschrift.

Allereerst wil ik mijn eerste promotor, prof. dr. A.H. Zwinderman bedanken. Koos, enorm be-dankt voor de kans die je me gegeven hebt om mijn onderzoek onder jouw supervisie te voltooien.Het was een genoegen om onder jouw begeleiding aan dit proefschrift te kunnen werken. Je hebtme veel dingen geleerd, wat ik in de toekomst nog veelvuldig hoop toe te kunnen passen. Juistde ontspannen sfeer die je creëert en de persoonlijke aandacht die je geeft zijn enorm fijn om meete werken. Ondanks dat je enorm druk bent met van alles en nog wat, en mensen continu ietsvan je willen, krijg je het altijd voor elkaar tijd voor me vrij te maken. Ook wanneer ik ergensniet uit kwam, en ik plots binnen kwam lopen. Je hebt me altijd enorm vrij gelaten in mijnwerkzaamheden, wat uiteindelijk heeft geresulteerd in dit proefschrift.

Mijn tweede promotor, prof. dr. A.A. Voors. Beste Adriaan, je bent pas op het einde vanmijn promotietraject officieel betrokken als mijn promotor. Echter ben je, als hoofd en kartrekkervan BIOSTAT-CHF, al vanaf het allereerste begin van mijn promotietraject betrokken bij al mijnwerk binnen Work Package 7 - Systems Biology. Ik wil je danken voor alle teksten die je hebtdoorgelezen en aangepast. Vooral wanneer Koos en ik vanuit onze visie weer met een stuk aankwamen zetten die vol stond met statistiek waar jij je scherpe klinische blik op los liet om het stuktoch meer klinisch relevant te maken. Ik bewonder in het bijzonder hoe snel je op mails reageertmet alle teksten al nagekeken in de bijlage. Ik heb altijd bijzonder fijn met je samengewerkt.

Promotiecommissie, Yigel Pinto, Rudolf de Boer, Ameen Abu-Hanna, Bert Groen, Natal vanRiel en Dave Speijer, enorm bedankt voor het lezen en beoordelen van dit proefschrift. Ondanksjullie strakke schema hebben jullie de tijd genomen om dit proefschrift door te nemen en met mijin het openbaar van gedachten te wisselen tijden mijn verdediging van dit proefschrift.

Ook wil ik mijn Groningse collega promovendi, Jasper, bedanken. Jasper, we hebben veelgebrainstormd over hoe we nu weer een probleem konden oplossen. We konden altijd even bellen,ook al zat je merendeel van de tijd aan de andere kant van de wereld. Ik heb altijd bijzonderprettig met je samengewerkt. En ik hoop dat we in de toekomst nog een paar mooie projectenkunnen afronden.

I also want to thank all the members of the BIOSTAT-CHF consortium. With all yourenthusiasm, ideas and comments for many of the chapters in this PhD thesis. You all had a greatcontribution to many of the chapters in this thesis. The monthly and yearly BIOSTAT-CHFmeetings, first on congresses and later at Schiphol always were inspiring. I always left with newinsights for existing projects and new ideas for future projects.

Ook wil ik graag alle collega’s en oud-collega’s op de afdeling Klinische Epidemiologie, Bio-statistiek en Bioinformatica bedanken. Ik heb me vanaf het eerste moment altijd thuis gevoeldop de afdeling en daardoor altijd mezelf kunnen zijn. De KEBB-uitjes waren ook elk jaar weereen feest. Ik zal nog frequent langs blijven komen en hoop ook altijd contact te houden met hetmerendeel van de afdeling.

In het bijzonder wil ik mijn 207 kamergenoten bedanken. Erik, Michel, Raha en Marit. Toenik op de KEBB kwam werken had 207 de naam een echte rebelse kamer te zijn. Er werd tegenme gezegd: ’maak je borst maar nat’ wanneer ik zei dat ik op kamer J1B-207 kwam te zitten. Ikheb altijd met plezier op de kamer gezeten, en dat rebelse is er in de loop van de jaren wel eenbeetje af gegaan. Het lijkt er nu eerder op dat 207 een zeer vruchtbare kamer is waar iedereenop een gegeven moment ouder wordt. Ik hoop wel dat er wat nieuw bloed komt die de naam van

182 Acknowledgements

207 hoog weet te houden. Ook wil ik Marit bedanken dat ze bereid was om mij, als paranimf,bij te staan tijdens mijn verdediging.

Sam Garrett, bedankt voor het redigeren van een aantal hoofdstukken in dit proefschrift. Ikvoel me vereerd dat ik kan zeggen dat Sam Garrett aan een deel van mijn proefschrift heeftgewerkt.

Pap, mam, jullie hebben mij altijd gesteund in wat ik ook maar wilde doen. Of het nu wasom me zondag ’s ochtends om 8 uur naar volleybal training te brengen. Of wanneer ik bedachtom toch nog een extra Master te gaan doen. De mogelijkheden die jullie me geboden hebben zalik altijd blijven onthouden. En ik hoop dat ik dat ook aan mijn dochter kan bieden.

Maaike, je bent inmiddels zelf net begonnen met je PhD. Ik hoop dat je net zo een leuke tijdgaat hebben als dat ik heb gehad. Deze periode is zeer speciaal en gaat voorbij voor je het doorhebt. Dus geniet er van zolang het duurt! Jij bent degene geweest waardoor ik ben gaan kijkennaar een PhD positie. Dus eigenlijk heb ik dit gehele proefschrift aan jou te danken. Ik ga ervan uit dat er over een jaar of 3 ook een boekje van jou op de planken ligt. Ik ben er ook trotsop dat je de uitdaging bent aangegaan, en dat je bij mijn promotie als paranimf aanwezig wildezijn.

Niet in de laatste plaats wil ik in het bijzonder mijn steun en toeverlaat bedanken. Rosa,zonder jou was ik waarschijnlijk nooit op dit punt gekomen. Je hebt al mijn overdenkingen aanmoeten horen, ook als je er niet alles van snapte. Je was altijd mijn luisterend oor. Tijdens mijnPhD heb je zelf even een Master afgerond. Waar ik voltijd bezig was heb jij alles gewoon naastje werk gedaan. Het was af en toe best zwaar, maar je hebt het toch maar mooi geflikt! Ik hebdaar nog steeds enorm veel bewondering voor. Ik denk niet dat ik dat gekund had. Ik hoop nogheel lang met je samen te kunnen zijn.

Als laatste wil ik mijn kleine meisje bedanken. Terwijl ik dit aan het schrijven ben zit je nogin de buik van mamma. Ze zeggen dat je promotie onderzoek een zeer bijzondere ervaring is. Ikdenk dat het krijgen van een kind daar nog even voorbij schiet. Ik heb enorm veel zin om je opdeze wereld te mogen verwelkomen. Ik denk nu al enorm veel aan je. En dat zal de komende tijdalleen maar meer worden.

PHD PORTFOLIO

187

Name PhD student: Wouter OuwerkerkPhD period: 2012-2017Name PhD supervisors: Prof. dr. A.H. Zwinderman

Prof. dr. A.A. Voors

Conferences• 34th Annual Conference of the ISCB 2013 Munich

Poster: Contribution of Alternative splicing Isoforms in gene expression data

• European Society of Cardiology Congress 2014 BarcelonaPresentation: Baseline characteristics and mortality and heart failure hospitalization risks of Biostat-CHF

• 35th Annual Conference of the ISCB 2014 ViennaPoster: Contribution of Alternative splicing Isoforms in gene expression data

• American College of Cardiology Congress 2015 San Diego

• 36th Annual Conference of the ISCB 2015 UtrechtPoster: Integration of genomewide genetic, molecular and clinical censored outcome

• IBS Channel Network Conference 2015 NijmegenPoster: Integration of genomewide genetic, molecular and clinical censored outcome

• 37th Annual Conference of the ISCB 2016 BirminghamPoster: Penalized Canonical Corelation Analysis combining genomic, proteomic, laboratory and clinicalphenotypic data

• Annual BIOSTAT-CHF meeting 2012-2016Progress presentations

Teaching

• 2nd years medicine 2012-2014Tutorial: Medical statistics (SPSS)

• 3rd years medicine 2012-2014Tutorial: Medical statistics (SPSS)

• Master medical biochemistry and molecular biology 2013Workgroup: homosysteinemea; a risk factor for CVD

• Graduate-school: Advanced topics in biostatistics 2014R tutorial: Longitudinal data analysis

• Graduate-school: Genetic epidemiology 2014R tutorial: Genetic analysis

188 PhD Portfolio

Courses

• ISCB Munich 2013Prediction models

• ISCB Vienna 2014Statistical methods in Systems Medicine

• ISCB Utrecht 2015Applied multiple imputation in R

• IBS Nijmegen 2015Splines

• Weekly KEBB seminar 2012-2016

List of Publications• W. Ouwerkerk, A. A. Voors, S. D. Anker, J. G. Cleland, K. Dickstein, G. Filippatos, P.

van der Harst, H. L. Hillege, C. C. Lang, J. M. ter Maaten, L. Ng, P. Ponikowski, N. J.Samani, D. J. van Veldhuisen, F. Zannad, M. Metra, and A. H. Zwinderman, ”Determinantsand clinical outcome of uptitration of ACE-inhibitor and beta-blocker in patients with heartfailure: a prospective European study,” Eur. Heart J., in press (2017)

• A. A. Voors*, W. Ouwerkerk*, F. Zannad, D. J. van Veldhuisen, N. J. Samani, P.Ponikowski, L. Ng, M. Metra, J. M. ter Maaten, C. C. Lang, H. L. Hillege, P. van derHarst, G. Filippatos, K. Dickstein, J. G. Cleland, S. D. Anker, and A. H. Zwinderman,”Development and validation of multivariable models to predict mortality and hospitaliza-tion in patients with heart failure,” Eur. J. Heart Fail., in press (2017)

• W. Ouwerkerk and A. H. Zwinderman, ”Alternative Splice Variants in Gene ExpressionValues in Patients with Marfan’s Syndrome,” J. Proteomics Bioinform. 8, 1-8 (2015)

• W. Ouwerkerk, A. A. Voors, and A. H. Zwinderman, ”Factors influencing the predictivepower of models for predicting mortality and/or heart failure hospitalization in patientswith heart failure.,” JACC. Heart Fail. 2, 429-36 (2014)

• I. M. Visman, G. M. Bartelds, W. Ouwerkerk, A. C. J. Ravelli, L. M. Peelen, B. A.C. Dijkmans, M. Boers, and M. T. Nurmohamed, ”Effect of the application of trial inclu-sion criteria on the efficacy of adalimumab therapy in a rheumatoid arthritis cohort.,” J.Rheumatol., 38, 1884-90 (2011)

* Authors contributed equally

CURRICULUM VITAE

193

Wouter Ouwerkerk was born in Apeldoorn on 7 December1983. After receiving his pre-university degree at the Heemgaard,Apeldoorn, in 2002, he started with Medical Informatics at theAcademic Medical Center, University of Amsterdam. His masterthesis, titled: The place of biologicals (’the Eldorado gold’) inthe battle against rheumatism, was published in 2011 (Visman etal. J Rheumatol 2011). In this study his interest in personalizedmedicine were triggered. During his medical informatics study heworked as data-manager at the Jan van Breemen Institute, Ams-terdam, a specialized center which focused on complaints relatingto the musculoskeletal system, and rheumatic diseases. He wasresponsible for developing study databases for research projects,and facilitating research staff in ICT solutions.

After obtaining his masters degree medical informatics in 2006,he started another masters programme ’Management, Policy Anal-ysis and Entrepreneurship’, at the Vrije University, Amsterdam.In this master he focussed on governmental policy, qualitativeresearch methods, knowledge integration and patient participation, and followed several manage-ment courses.

In 2009 he started working at Factory-CRO, Bilthoven. A contract research organisationspecialized in medical devices and in-vitro diagnostics. He worked as data-manager on severaldifferent projects and was responsible for the creation of case report forms and study databases,the process of data cleaning and validation and export of study data. He also developed andimproved software applications for documenting and reporting in data-management and clinicaltrial processes. At Factory-CRO, he got additional training in good clinical practice (ICH-GCP),clinical investigation of medical devices for human subjects (ISO 14155), and adaptive trial de-signs.

In 2012 he started his PhD at the Department of Clinical Epidemiology, Biostatistics andBioinformatics at the Academic Medical Center, University of Amsterdam: A Systems biologystudy to tailored treatment in chronic heart failure. This PhD was part of a large multicenterEuropean project (BIOSTAT-CHF). BIOSTAT-CHF was especially designed to find biologicalmechanisms involved with response to ESC guideline-recommended pharmacological treatmentand patients prognosis. In this project he collaborated with the consortium members and workedon studies presented in this PhD thesis.

In 2016 he started working as a post-doc on a new research project at the ExperimentalDermatology Department at the Academic Medical Center, University of Amsterdam. Thisproject tries to identify a set of genetic auto-immune and vitiligo markers in melanoma patientsthat is able to predict response to immune checkpoint inhibitor treatment.

TERMS AND ABBREVIATIONS

197

Notation Description Page List

ACE-inhibitor angiotensin-converting-enzyme inhibitor

vii, ix, x, xiii–xv, 7, 9–11, 13, 14,23, 31, 40, 43–58, 62–78, 83, 84,87, 90, 94, 96, 102–106, 109, 110,112, 115–117, 136, 140, 143, 144,149–154, 161–163, 167–169, 197,219–221, 227, 229, 232, 234–243,

Glossary:angiotensin-converting-enzyme

inhibitor

ADHF acute decompensated heart failure xiii, xiv, 19, 21, 22, 24–26, 219,222, 224–226

AF atrial fibrillation3, 9, 48–50, 54, 56, 67, 73, 84, 87,96, 103, 108–110, 115, 117, 227,

228, 232–244AIC Akaike information criterion 32, 120, 123–131ALAT alanine aminotransferase 84, 227, 228, 230, 233, 244

albumin 8, 70, 71, 86, 87, 94, 96, 153, 227,230, 232, 234–243

ALCAM CD166 antigen 230, 245, 247

alkalinephosphatase

34, 35, 48, 50, 57, 58, 71, 72, 84,86, 87, 96, 98, 105, 227, 228, 230,

232–244angiotensin IIreceptor blocker ARBs block the action of angiotensin II by preventing an-

giotensin II from binding to angiotensin II receptors on themuscles surrounding blood vessels

7, 31, 45, 63, 83, 103, 140, 149,161, 197, 219–221

angiotensin-converting-enzymeinhibitor

ACE inhibitors block the conversion of angiotensin I to an-giotensin II

7, 31, 45, 63, 83, 103, 140, 149,161, 197, 219–221

ANP-propeptide atrial natriuretic peptide-propeptide 230, 232AP-N aminopeptidase N 230, 245, 247

ARB angiotensin II receptor blocker

vii, ix, x, xiii–xv, 7, 9–11, 13, 14,23, 31, 40, 43–58, 62–78, 83, 84,87, 90, 94, 96, 102–106, 109, 110,112, 115–117, 136, 140, 143, 144,149–154, 161–163, 167–169, 197,219–221, 227, 229, 232, 234–243,

Glossary: angiotensin II receptorblocker

ASAT aspartate aminotransferase 70–72, 84, 87, 96, 153, 227, 228,230, 232–242, 244

AXL tyrosine-protein kinase receptor UFO 230, 246, 250

AZU1 azurocidin 71, 72, 113, 114, 230, 233, 245,247

beta-blocker Beta blockers block the action of endogenous catecholaminesepinephrine (adrenaline) and norepinephrine (noradrenaline)on adrenergic beta receptors, of the sympathetic nervous sys-tem, which mediates the fight-or-flight response. Some blockall activation of β-adrenergic receptors and others are selec-tive.

vii, ix, x, xiii–xv, 7, 9–11, 13, 14,22, 30, 31, 34–36, 40, 43–58,62–78, 83, 84, 87, 90, 94, 96,102–106, 109, 110, 112, 113,115–117, 136, 140, 143, 144,

149–154, 161–163, 167–169, 227,229, 233–243

BIC Bayesian information criterion 84–88, 97, 120, 123–131bio-ADM bioactive adrenomedullin 70, 72, 228, 230, 232, 244

BIOSTAT-CHF The BIOlogy STudy to TAilored Treatment in Chronic HeartFailure

ix, xiii, 8–11, 13, 14, 30–32, 36,39–41, 44–48, 51, 56–58, 61–64,76, 78, 82, 83, 98, 102, 103, 105,106, 110, 112, 116, 117, 137, 140,141, 149–153, 155, 156, 163, 169

BLM hydrolase Bleomycin hydrolase 230, 245, 247

BMI body mass index8, 9, 22, 47–50, 54, 56–58, 65, 67,73, 84, 86, 87, 96, 105, 109, 115,

220, 227, 228, 232–244

198

Notation Description Page List

BNP B-type natriuretic peptide8–10, 31, 41, 45, 63, 64, 67, 72,73, 84, 103, 137, 151, 228, 230,

233, 244

BUN blood urea nitrogen

8, 9, 18, 20–23, 25, 30, 34–36, 40,64, 66–73, 76, 78, 84, 105, 110,

151, 153, 161, 167, 219–221, 227,228, 230, 232, 233, 244

CABG coronary artery bypass graft 9, 67, 73, 84, 109, 115, 227, 228,244

CASP-3 caspase-3 72, 113, 114, 231, 245, 247CCA canonical correlation analysis 14, 137, 155CCL15 C-C motif chemokine 15 231, 245, 247CCL16 C-C motif chemokine 16 231, 233, 245, 247CCL22 C-C motif chemokine 22 230, 245, 247CCL24 C-C motif chemokine 24 230, 245, 247CD163 scavenger receptor cysteine-rich type 1 protein m130 230, 246, 250CD93 complement component C1q receptor 231, 245, 247CDH5 cadherin-5 230, 245, 247

CHF chronic heart failure xiii, xiv, 19, 21, 22, 24–26, 56,219, 222–226

CHI3L1 chitinase-3-like protein 1 71, 231, 245, 247

CHIT1 chitoriosidase-1 71, 113, 114, 117, 154, 230, 233,245, 247

CI confidence intervalxiv, 3, 22–24, 36, 44, 51, 53, 54,

68–70, 72, 74, 102, 110, 112,219–221

CNTN1 contactin-1 230, 245, 247COL1A1 collagen alpha-1 (I) chain 231, 245, 247

COPD chronic obstructive pulmonary disease8, 9, 34, 35, 67, 68, 73, 84, 86, 87,

96, 98, 109, 115, 227, 228,232–244

CPA1 carboxypeptidase A1 231, 245, 247CPB1 carboxypeptidase B 231, 245, 247CRP C-reactive protein 72, 77, 231, 233CSTB cystatin-B 71, 72, 230, 245, 247CTSD cathepsin D 231, 245, 247CTSZ cathepsin Z 231, 245, 247CXCL16 C-X-C motif chemokine 16 230, 245, 247cystatin C 69, 72, 231

DBP diastolic blood pressure9, 23, 34, 35, 48–50, 54, 56–58, 67,68, 73, 84, 105, 109, 115, 152, 219,

228, 232, 233, 244DLK-1 protein delta homolog 1 230, 246, 249

DM diabetes mellitus

3, 8, 9, 19, 22, 23, 34, 35, 48–50,54, 56, 67, 68, 73, 84, 87, 92, 96,108, 109, 115, 116, 154, 219–221,

227, 228, 232–244

DNA deoxyribonucleic acid 4, 6, 131, 137, 141, 144, 154, 163,169

EGFR epidermal growth factor receptor 114, 231, 245, 248

eGFR estimated glomerular filtration rate

8, 9, 30, 34–36, 40, 47–50, 54,56–58, 67, 71, 73, 84, 86, 87, 90,

92, 96, 98, 105, 109, 110, 115, 151,153, 161, 167, 197, 219, 220, 227,

228, 232–244, Glossary:estimated glomerular filtration

rateEp-Cam epithelial cell adhesion molecule 114, 230, 245, 248EPHB4 ephrin type-B receptor 4 230, 245, 248ESAM-1 endothelial cell selective adhesion molecule 1 66, 230, 233

ESC European Society of Cardiologyxiii, 7, 8, 11, 13, 40, 45, 56–58,

63–66, 77, 83, 103, 104, 140, 149,152, 155, 156, 161–163, 167–169

199

Notation Description Page List

estimatedglomerularfiltration rate

We used two equations to calculation eGFR: MDRD, andCKD-EPIMDRD = 175 × sCr−1.154 × Age−0.203 × (0.742 if female) ×(1.212 if African American)?

CKD-EPI = 141 × min(sCr/λ, 1)α × max(sCr/λ, 1)−1.209 ×0.993Age × (1.018 if female) × (1.159 if African American)?

where: sCr is serum creatinine in mg/dL, λ is 0.7 for femalesand 0.9 for males, α is -0.329 for females and -0.411 for males,min indicates the minimum of sCr/λ or 1, and max indicatesthe maximum of sCr/λ or 1

8, 9, 34–36, 47–50, 54, 56, 67, 73,84, 87, 96, 105, 109, 115, 151, 161,

197, 219, 220, 227, 232–243

ET-1 endothlin-1 72, 230, 233

FABP4 fatty acid-binding protein, adipocyte 114, 230, 245, 248FAS tumor necrosis factor receptor superfamily member 6 231, 246, 250FGF-23 fibroblast growth factor 23 69–72, 153, 230, 232FT4 free thyroxine 228, 230, 233, 244

Gal-3 galectin-3 68, 230–233, 245Gal-4 galectin-4 72, 231, 245, 248Gamma-GT gamma glutamyl transferase 228, 230, 233, 244GDF-15 growth/differentiation factor 15 66, 114, 230, 231, 233, 245, 248GRN granulins 230, 245, 248GWAS genome wide association study 4, 12, 140, 156

Hclust hierarchical cluster analysis x, xv, 82–85, 88, 90, 92, 93, 95–98,153, 154, 162, 168, 242, 243

HDL high density lipoprotein34–36, 40, 64, 66, 71, 72, 84, 87,94, 96, 106, 109, 110, 115, 161,

167, 227, 228, 230, 232, 234–244hematocrit 34, 35, 64, 66, 84, 227, 230, 233

hemoglobin

8, 9, 22, 30, 34–36, 64, 66, 67, 69,71–73, 76–78, 84, 87, 96, 105, 109,115, 153, 161, 167, 227, 228, 230,

232, 234–244HFmrEF heart failure with mid-range ejection fraction 109, 114–116, 154, 156

HFpEF heart failure with preserved ejection fractionxiii, 4, 7, 9, 14, 32, 36, 39, 41, 97,109, 114–116, 150, 151, 154, 156,

161, 167, 227

HFrEF heart failure with reduced ejection fractionxiii, 3, 4, 7, 14, 32, 36, 39, 41, 44,

75, 97, 103, 109, 115, 116, 150,151, 154, 156, 161, 167

HR hazard ratio xiv, 20–23, 34–36, 44, 51, 53, 54,68, 71, 72, 102, 110, 112, 219–221

ICAM-2 intercellular adhesion molecule 2 231, 245, 248IGFBP insulin-like growth factor-binding protein 112

IGFBP-1 insulin-like growth factor-binding protein 1 71, 72, 113, 114, 230, 233, 245,248

IGFBP-2 insulin-like growth factor-binding protein 2 70–72, 114, 231, 232, 245, 248IGFBP-7 insulin-like growth factor-binding protein 7 114, 231, 245, 248IL-17RA interleukin-17 receptor A 71, 230, 245, 248IL-18BP interleukin-18 binding protein 231, 245, 248IL-1RT1 interleukin-1 receptor type 1 230, 245, 248IL-1RT2 interleukin-1 receptor type 2 231, 245, 248IL2-RA interleukin-2 receptor subunit Alpha 230, 245, 248IL6-RA interleukin-6 receptor subunit Alpha 114, 230, 245, 248IPW inverse probability weighting xiii, 47, 58, 106, 117

IQR interquartile range9, 10, 31, 33, 48, 50, 54, 56, 64,67, 73, 87, 88, 90, 96, 137, 140,

227, 228, 230, 231, 234–244, 247ITGB2 integrin beta-2 230, 245, 248

JAM-A junctional adhesion molecule A 113, 114, 231, 245, 248

JVP jugular venous pressure3, 8, 9, 34, 35, 67, 68, 73, 84, 87,

96, 98, 109, 115, 227, 228,232–244

200

Notation Description Page List

KLK6 kallikrein-6 231, 245, 248

LCA latent class analysis 83, 84LDL low density lipoprotein 64, 66, 84, 230, 232, 233LDL-receptor low-density lipoprotein receptor 71, 72, 114, 230, 245, 249LTβR lymphotoxin beta receptor 66, 230LTBR lympotoxin-beta receptor 230, 245

LVEF left ventricular ejection fraction

xiii, 3, 7–10, 22, 30, 31, 33, 44, 45,47–50, 54, 56, 63, 64, 66–68, 71,73, 78, 84, 86, 87, 90, 96, 103,

109, 115, 116, 151, 154, 227, 228,230, 232–244

m/z mass-to-charge ratio 140, 141MALDI matrix assisted laser desorption and ionization 140MALDI-TOF MALDI time-of-flight 6MALDI-TOF-MS MALDI-TOF mass spectrometry 137MB myoglobin 231, 245, 249

Mclust gaussian mixture for model-based clusteringx, xv, 82–86, 88, 89, 92, 95, 97,98, 124, 153, 154, 162, 168, 234,

235MCP-1 monocypte chemotactic protein 1 230, 245MEPE matrix extracellular phosphoglycoprotein 230, 249

MI myocardial infarction 3, 8, 9, 19, 67, 73, 84, 227, 228,232, 244

MMP-2 matrix metalloproteinase-2 230, 245, 249MMP-3 matrix metalloproteinase-3 231, 233, 245, 249MMP-9 matrix metalloproteinase-9 70, 71, 230, 245, 249MPO myeloperoxidase 66, 71, 230, 233, 245MRA mineralocorticoid receptor antagonist 7

mRNA messenger ribonucleic acid 6, 14, 121, 122, 124, 131, 137, 154,163, 169

NGAL neutrophil gelatinase associated lipocalin 71, 231–233NOTCH3 neurogenic locus notch homolog protein 3 230, 245, 249NPX normalized protein expression units 64, 71, 72, 104, 230–233

NT-proBNP N-terminal pro B-type natriuretic peptide

8–10, 21–23, 30, 31, 34–36, 41, 45,48–50, 54, 56, 63, 64, 67, 69–73,

76, 77, 84, 86, 87, 90, 92, 94,96–98, 103, 105, 107–110, 115,

116, 137, 141, 151, 153, 161, 167,219–221, 227, 228, 230–245

NT-proCNP N-terminal pro C-type natriuretic peptide 230

NYHA class New York Heart Association class

7–9, 22, 23, 30, 33–35, 65, 67, 71,73, 78, 84, 86, 87, 90, 92, 94, 96,97, 107–109, 115, 116, 137, 151,153, 219–221, 227, 228, 232–244

OPG osteoprotegerin 230, 233, 245, 249OPN osteopontin 66, 230, 231, 245, 249OR odds ratio 20–23, 219–221, 232, 233

PAI plasminogen activator inhibitor 1 230, 233, 245, 249

PAM partitioning around k-medoidsx, xv, 82–85, 88, 90, 92, 95, 97,98, 102, 105, 106, 153, 154, 162,

163, 168, 169, 238–241PCA principal component analysis 14, 105, 106, 117, 154, 163, 169

pCCA penalized canonical correlation analysis vii, 135–138, 140, 142, 144, 155,156, 163, 169, 170

PCI percutaneous coronary intervention 9, 67, 73, 84, 109, 115, 227, 228,232, 233, 244

PCSK9 proprotein convertase subtilisin/kexin type 9 231, 246, 249PCT procalcitonin 230PDGF platelet-derived growth factor subunit A 70, 72, 114, 231, 233, 246, 249PEA proximity extension assay 64, 104PECAM-1 platelet endothelial cell adhesion molecule 113, 114, 231, 245, 249PGLYRP1 peptidoglycan recognition protein 1 231, 245, 249PI3 elafin 72, 230, 245, 248

201

Notation Description Page List

PIGR-1 polymeric immunoglobulin receptor 1 231, 233PLC perlecan 230, 245, 249

poLCA polytomous latent class analysisx, xv, 82, 84, 85, 87, 88, 91, 92,95–98, 153, 154, 162, 168, 236,

237PON3 paraoxnase 72, 113, 114, 231, 245, 249

potassium 9, 64, 66, 67, 73, 84, 87, 96, 115,140, 227, 228, 230, 233–244

pro-ENK pro-enkephalin 69–72, 153, 230, 232, 233proADM pro-adrenomedullin 77, 136, 144, 231, 233PRTN3 myeloblastin 113, 114, 231, 245PSAP-B prosaposin B 66, 230PSP-D pulmonary surfactant-associated protein D 71, 230, 246, 249

RAGE receptor for advanced glycation endproducts 231RARRES2 retinoic acid receptor responder protein 2 231, 233, 246, 249

RCT randomized controlled trial7, 20, 25, 27, 31, 39, 45, 46, 56,

62–64, 77, 106, 116, 149, 152, 161,162, 168, 222–226

RETN resistin 230, 233, 246, 249

RNA ribonucleic acid 6, 120, 124, 125, 131, 136, 137,144, 154, 163, 169

RSS residual sum of squares 125, 126

SBP systolic blood pressure

8, 9, 21–23, 30, 34–36, 47–50, 54,56, 67, 73, 84, 86, 87, 90, 96, 106,

109, 110, 115, 152, 161, 167,219–221, 227, 228, 232–244

SCGB3A2 secretoglobin family 3A member 2 231, 246, 250

SD standard deviation9, 33, 48, 50, 54, 56, 67, 68, 73,84, 86–88, 90, 92, 96, 227, 228,

230, 231, 234–244

SE standard error 21, 24, 25, 47, 49, 50, 71, 72, 232,233

SELE E-selectin 230, 233, 245, 248SELP p-selectin 113, 114, 230, 245, 249

serum creatinine 8, 9, 64, 67, 69, 71, 73, 84, 140,161, 167, 220, 230, 232

SHPS-1 tyrosine-protein phosphatase non-receptor type substrate 1 231, 246, 250

SNP single nucleotide polymorphism xi, 4, 6, 12, 14, 141, 143, 145, 155,156

sodium

8, 9, 18, 20–22, 25, 34–36, 40, 64,66, 67, 71–73, 78, 84, 87, 96, 106,110, 115, 153, 161, 167, 220, 221,

227, 228, 230, 233–244SPON1 spondin-1 71, 230, 246, 250

ST2 69, 71, 72, 76, 77, 113, 114, 136,144, 231–233, 246, 250

sTfR soluble transferrin receptor 71, 72, 228, 230, 233, 244

t-PA tissue-type plasminogen activator 71, 113, 114, 231, 232, 246, 250TFF3 trefoil factor 3 71, 72, 230, 246, 250TFPI tissue factor pathway inhibitor 72, 230, 233, 246, 250TIMP4 metalloproteinase inhibitor 4 230, 245, 249TLT-2 trem-like transcript 2 protein 113, 114, 230, 246, 250TNF-R1 tumor necrosis factor receptor 1 231–233, 246, 250TNF-R1A tumor necrosis factor receptor 1A 231TNF-R2 tumor necrosis factor receptor 2 230, 246, 250TNFRSF10C tumor necrosis factor receptor superfamily member 10C 230, 246, 250TNFRSF14 tumor necrosis factor receptor superfamily member 14 114, 230, 233, 246, 250TNFSF13B tumor necrosis factor ligand superfamily member 13B 231, 246, 250TR trassferrin receptor protein 1 230, 246, 250TR-AP tartrate-resistant acid phosphatase type 5 230, 246, 250TRIPOD the Transparent Reporting of a multivariable prediction model

for Individual Prognosis Or Diagnosis12, 31, 150, 151

TSH hyroid-stimulating hormone 228, 230, 233, 244

U-PAR urokinase plasminogen activator surface receptor 69, 71, 72, 231, 246, 250

202

Notation Description Page List

uPA urokinase-type plasminogen activator 231, 246, 250

VEGFR-1 vascular endothelial growth factor receptor 71, 231vWF von Willebrand factor 114, 231, 233, 246, 250

WAP-4C WAP Four-Disulphide Core Domain Protein HE4 77, 231, 233

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SUPPLEMENTARY DATA

223

Table S1: The 10 variables with the highest predicted values (highest z-score), used in morethan 5 chronic heart failure models

# z-score Mean 95% CI

10 highest odds ratiosBlood urea nitrogen 24 61.50 2.37 2.34-2.39Systolic blood pressure 45 54.72 1.16 1.15-1.16Cancer 9 38.00 1.84 1.81-1.88Troponin 8 34.59 1.73 1.69-1.76Creatinine 36 34.19 1.12 1.11-1.13Sodium 44 33.50 1.41 1.39-1.43Heart Failure 9 27.92 1.28 1.26-1.30Arterial pH 6 27.75 1.87 1.83-1.92Diastolic blood pressure 11 22.01 1.15 1.14-1.16Renal failure 8 21.11 1.26 1.24-1.28

10 highest hazard ratiosSodium 44 36.53 1.07 1.06-1.07Race 10 27.03 1.11 1.10-1.12Diabetes mellitus 41 21.23 1.44 1.41-1.47Age 73 20.65 1.06 1.06-1.07Systolic blood pressure 45 18.65 1.18 1.16-1.19New York Heart Association class 34 17.51 1.41 1.37-1.44N-terminal pro B-type natriuretic peptide 15 15.24 1.47 1.42-1.52Angiotensin-converting-enzyme inhibitor/Angiotensin II receptor blocker 8 14.01 1.19 1.17-1.21Ejection fraction 23 12.84 1.08 1.07-1.10Blood urea nitrogen 24 12.01 1.07 1.06-1.08#: Number of times used; CI: confidence interval

Table S2: The 10 variables with the highest predicted values (highest z-score), used in acutedecompensated heart failure models

# z-score Mean 95% CI

10 highest odds ratiosHeart Failure admissions 2 12.44 1.44 1.39-1.50Age 4 8.45 1.46 1.37-1.55Dementia/Alzheimers disease or senility 1 6.31 2.42 2.15-2.70Systolic blood pressure 6 2.18 1.22 1.04-1.41Mode of arrival 1 2.13 5.07 3.57-6.57Metastatic cancer 1 1.92 4.60 3.04-6.16Depression or anxiety 1 1.85 1.72 1.15-2.30Hepatic cirrhosis 1 1.09 3.22 1.11-5.33Nitrates 1 1.08 2.00 0.74-3.26Cancer 1 0.83 1.86 0.39-3.33

10 highest hazard ratiosSodium 2 1.66 1.33 0.99-1.67New York Heart Association class 1 0.85 1.94 0.41-3.47Heart Failure admissions 2 0.74 2.00Gender 1 0.44 1.33Systolic blood pressure 6 0.38 1.28 -0.01-2.57Blood urea nitrogen 4 0.34 1.33 -0.32-2.98Age 4 0.25 1.27 -0.57-3.11N-terminal pro B-type natriuretic peptide 1 0.09 1.08Estimated glomerular filtration rate 1 0.06 1.01Systolic blood pressure 1 0.06 1.01#: Number of times used; CI: confidence interval

224 Supplementary data

Table S3: The 10 variables with the highest predicted values (highest z-score), used in mortalityprediction models

# z-score Mean 95% CI

10 highest odds ratiosBlood urea nitrogen 24 65.19 3.02 2.99-3.05Systolic blood pressure 45 42.75 1.17 1.16-1.17Cancer 9 38.00 1.84 1.81-1.88Troponin 8 34.59 1.73 1.69-1.76Sodium 44 34.41 1.44 1.42-1.46Creatinine 36 32.69 1.12 1.11-1.12Cardiac arrest or mechanical ventilation 5 32.61 13.26 13.1-13.41Arterial pH 6 27.75 1.87 1.83-1.92Prothrombin time/international normalized ratio 4 27.03 1.40 1.38-1.42Arterial pCo2 5 25.39 1.42 1.40-1.45

10 highest hazard ratiosSodium 44 30.34 1.09 1.08-1.09Age 73 17.93 1.06 1.05-1.06New York Heart Association class 34 16.83 1.40 1.36-1.44N-terminal pro B-type natriuretic peptide 15 15.24 1.47 1.42-1.52Diabetes mellitus 41 14.58 1.38 1.33-1.42Angiotensin-converting-enzyme inhibitor/angiotensin II receptor blocker 8 14.01 1.19 1.17-1.21Serum creatinine 36 10.20 1.06 1.05-1.08Body mass index 21 10.19 1.08 1.07-1.10Systolic blood pressure 45 9.91 1.11 1.09-1.13Ejection fraction 23 8.97 1.04 1.03-1.05#: Number of times used; CI: confidence interval

Table S4: The 10 variables with the highest prediction values (highest z-score), used in mortalityand/or heart failure related hospitalization prediction models

# z-score Mean 95% CI

10 highest odds ratiosHeart Failure admissions 3 12.47 1.40 1.35-1.45Depression or anxiety 1 8.82 1.12 1.10-1.15Acuity of Admission 1 6.56 1.47 1.35-1.59Nitrates 1 6.42 1.48 1.36-1.60Creatinine 2 6.10 1.25 1.18-1.32Length of stay 1 5.94 1.56 1.41-1.71Cancer 1 5.75 1.19 1.13-1.24Emergency department visits 1 5.59 1.21 1.14-1.28Blood urea nitrogen 4 5.24 1.33 1.22-1.44Drug/Alcohol 2 4.96 1.07 1.04-1.10

10 highest hazard ratiosRace 1 27.03 1.11 1.10-1.12Age 4 23.73 1.51 1.48-1.54Estimated glomerular filtration rate 1 21.41 2.34 2.26-2.42Systolic blood pressure 6 17.75 1.23 1.20-1.25Diabetes mellitus 1 17.51 1.52 1.47-1.57Anemia 1 15.93 1.69 1.62-1.75Blood pressure treatment 1 15.91 1.20 1.18-1.23N-terminal pro B-type natriuretic peptide 1 14.46 1.62 1.55-1.68Ejection fraction 1 10.65 1.13 1.10-1.15Gender 1 10.28 1.20 1.17-1.24#: Number of times used; CI: confidence interval

225

Table S5: The 10 variables with the highest prediction values (highest z-score), used in heartfailure related hospitalization prediction models

# z-score Mean 95% CI

10 highest odds ratiosBlood urea nitrogen 24 60.70 2.28 2.26-2.31Cancer 9 38.00 1.84 1.81-1.88Troponin 8 34.59 1.73 1.69-1.76Creatinine 36 34.19 1.12 1.11-1.13Sodium 44 33.50 1.41 1.39-1.43Systolic blood pressure 45 31.80 1.30 1.29-1.32Heart Failure 9 27.92 1.28 1.26-1.30Cardiac arrest or mechanical ventilation 5 27.91 6.54 6.41-6.67Arterial pH 6 27.75 1.87 1.83-1.92Prothrombin time/international normalized ratio 4 27.03 1.40 1.38-1.42

10 highest hazard ratiosSodium 44 30.34 1.09 1.08-1.09Race 10 27.03 1.11 1.10-1.12Diabetes mellitus 41 21.23 1.44 1.41-1.47Age 73 20.73 1.06 1.06-1.07Systolic blood pressure 45 19.35 1.16 1.15-1.18New York Heart Association class 34 17.68 1.41 1.37-1.45Anemia 5 15.93 1.69 1.62-1.75Blood pressure treatment 4 15.91 1.20 1.18-1.23N-terminal pro B-type natriuretic peptide 15 15.32 1.44 1.39-1.49angiotensin-converting-enzyme inhibitor/angiotensin II receptor blocker 15 14.01 1.19 1.17-1.21#: Number of times used; CI: confidence interval

226 Supplementary data

Table S6: Papers and models selected for meta-analysis

Paper N Pop SM Pt Du P # E C DS V Type Age ♂Selker et al.197 1 CHF RR 5773 2 D 4 M 0.9 MR P COH 74 50Aaronson 2 CHF RR 268 365 D 7 M 0.74 MR P COH 50 80et al.390 2 CHF RR 199 365 V 7 M 0.69 MR P COH 52 81

3 CHF RR 231 365 D 8 M 0.74 MR P COH 50 803 CHF RR 199 365 V 8 M 0.66 MR P COH 52 81

Chin and 4 CHF RR 257 60 D 6 M MR P COH 67 49Goldman391 4 CHF RR 257 60 D 6 MH MR P COH 67 49Philbin et al.392 5 CHF RR 52010 365 D 16 H 0.62 CD R REG 74 44

6 CHF AR 52010 365 D 16 H 0.6 CD R REG 74 446 CHF AR 21504 365 V 16 H 0.6 CD R REG 74 447 CHF AR 52010 365 D 16 H 0.61 CD R REG 74 44

Alla et al.393 8 CHF RR 219 549 D 5 M MR P COH 66 839 CHF RR 182 549 D 8 M MR P COH 64 76

Krumholz 10 CHF RR 1129 183 D 4 H MR R REG 79 41et al.394 10 CHF RR 1047 183 V 4 H MR R REG 79 41Rosenthalet al.395 11 CHF RR 13834 30 D 27 M 0.8 CD R REG 79 42

Bouvy et al.396 12 CHF RR 152 549 D 7 M 0.77 MR P RCT 70 6613 CHF RR 152 549 D 8 M 0.80 MR P RCT 70 6614 CHF RR 152 549 D 9 M 0.84 MR P RCT 70 6615 CHF RR 152 549 D 10 M 0.85 MR P RCT 70 66

Kearney et al.397 16 CHF RR 553 1825 D 7 M 0.74 MR P COH 63 7616 CHF RR 553 1825 D 7 M 0.78 MR P COH 63 76

Lee et al.398 17 CHF RR 2624 30 D 10 M 0.8 CD R REG 76 5017 CHF RR 2624 30 D 10 M 0.82 CD R REG 76 5017 CHF RR 1407 30 V 10 M 0.79 CD R REG 75 5018 CHF RR 2624 365 D 11 M 0.77 CD R REG 76 5018 CHF RR 1407 365 V 11 M 0.76 CD R REG 75 50

Brophy et al.399 19 CHF RR 4277 365 D 9 M MR P RCT 63 7819 CHF RR 2145 365 V 9 M MR P RCT 63 7820 CHF RR 4277 1095 D 11 M MR P RCT 63 7820 CHF RR 2145 1095 V 11 M MR P RCT 63 78

Felker et al.400 21 ADHF RR 949 60 D 5 M 0.76 MR P RCT 68 6622 ADHF RR 949 60 D 5 MH 0.68 MR P RCT 68 66

Adlam et al.401 23 CHF RR 532 1825 D 6 M 0.75 MR P COH 75 4124 CHF AR 532 1825 D 6 M 0.75 MR P COH 75 41

Auble et al.402 25 CHF CA 33533 0 D 21 MH MR R COH 83.1 44Fonarow et al.403 26 ADHF CA 33046 0 D 3 M 0.69 MR R REG 73 48

26 ADHF CA 32229 0 V 3 M 0.67 MR R REG 73 4927 ADHF RR 33046 0 D 4 M 0.76 MR R REG 73 4827 ADHF RR 32229 0 V 4 M 0.76 MR R REG 73 49

Heywood et al.404 28 CHF RR 680 365 D 5 M MR P COH 62 6628 CHF RR 680 1825 D 5 M MR P COH 62 66

O’Connoret al.405 29 ADHF RR 930 60 D 6 MH MR P COH 62 52

Krumholz 30 CHF RR 222424 30 D 24 M 0.71 CD R REG 80 41et al.198 30 CHF RR 222157 30 V 24 M 0.7 CD R REG 80 41

30 CHF RR 422552 30 V 24 M 0.7 CD R REG 80 4130 CHF RR 426576 30 V 24 M 0.7 CD R REG 80 4130 CHF RR 422351 30 V 24 M 0.7 CD R REG 80 4131 CHF RR 46700 30 D 21 M 0.78 CD R REG 80 4131 CHF RR 46700 30 V 21 M 0.7 CD R REG 80 41

Levy et al.196 32 CHF RR 1125 365 D 14 M 0.73 MR P RCT 65 7632 CHF RR 925 365 V 14 M 0.68 MR P RCT 62 7832 CHF RR 2987 365 V 14 M 0.68 MR P RCT 71 6932 CHF RR 5010 365 V 14 M 0.69 MR P RCT 63 8032 CHF RR 872 365 V 14 M 0.75 MR R COH 64 7632 CHF RR 148 365 V 14 M 0.81 MR P COH 53 78

Pocock et al.406 33 CHF RR 7599 730 D 21 MH 0.75 MR P COH 66 7234 CHF RR 7599 730 D 21 M 0.75 MR P COH 66 68

Tabak et al.192 35 CHF RR 273034 0 D 1 M 0.61 MR R COH 77 4536 CHF RR 273034 0 D 13 M 0.77 MR R COH 77 4537 CHF RR 273034 0 D 15 M 0.77 MR R COH 77 4538 CHF RR 273034 0 D 18 M 0.8 MR R COH 77 4539 CHF RR 273034 0 D 20 M 0.81 MR R COH 77 45

TableS6– Continued on next page

227

TableS6– Continued from previous pagePaper N Pop SM Pt Du P # E C DS V Type Age ♂Yamokoski 40 CHF RR 373 180 D 3 M 0.6 MR P RCT 56 74et al.191 CHF 373 180 D M 0.61 MR P RCT 56 74

CHF 373 180 D H 0.58 MR P RCT 56 7441 CHF RR 373 180 D 2 H 0.52 MR P RCT 56 74

CHF 373 180 D M 0.68 MR P RCT 56 74CHF 373 180 D H 0.57 MR P RCT 56 74

Abraham et al.407 42 CHF RR 37548 680 D 17 M 0.77 MR R REG 73 4843 CHF AR 40201 680 D 7 M 0.76 MR R REG 73 4843 CHF AR 40201 680 V 7 M 0.75 MR R REG 73 4843 CHF AR 181830 680 V 7 M 0.75 MR R REG 73 4844 CHF CA 37548 680 D 4 M 0.68 MR R REG 73 48

Keenan et al.408 45 CHF RR 283919 30 D 34 H 0.6 CD R REG 80 4245 CHF RR 283528 30 V 34 H 0.6 CD R REG 80 4245 CHF RR 561763 30 V 34 H 0.61 CD R REG 80 046 CHF RR 64329 20 D 20 H 0.58 CD R REG 4246 CHF RR 64329 20 V 20 H 0.61 CD R REG 42

O’Connor 47 CHF RR 4402 90 D 13 M 0.72 MR R REG 73 48et al.409 48 CHF RR 4402 90 D 14 M 0.77 MR R REG 73 48

49 CHF AR 4402 60 D 8 M 0.72 MR R REG 73 4850 CHF RR 4014 90 D 15 MH 0.64 MR R REG 73 48

Levy et al.410 49 CHF RR 2521 365 D 17 M 0.71 MR P RCT 60 7749 CHF RR 10038 365 V 17 M 0.71 MR P COH 0

Vazquez et al.411 50 CHF RR 992 1338 D 8 M 0.78 MR P COH 65 7250 CHF RR 992 1338 V 8 M 0.78 MR P COH 65 7251 CHF RR 992 1338 D 6 M 0.8 MR P COH 65 7251 CHF RR 992 1338 V 6 M 0.78 MR P COH 65 7252 CHF RR 992 1338 D 5 M 0.77 MR P COH 65 7252 CHF RR 992 1338 V 5 M 0.74 MR P COH 65 7253 CHF RR 992 1338 D 9 M 0.76 MR P COH 65 7253 CHF RR 992 1338 V 9 M 0.75 MR P COH 65 72

Wedel et al.141 54 CHF RR 3368 1095 D 20 MH 0.653 MR P RCT 73 7554 CHF RR 3368 1095 D 20 M 0.667 MR P RCT 73 7554 CHF RR 3368 1095 D 20 M 0.742 MR P RCT 73 7555 CHF RR 3368 1095 D 14 MH 0.666 MR P RCT 73 7555 CHF RR 3368 1095 D 14 M 0.684 MR P RCT 73 7555 CHF RR 3368 1095 D 14 M 0.757 MR P RCT 73 7556 CHF RR 3368 1095 D 14 MH 0.701 MR P RCT 73 7556 CHF RR 3368 1095 D 14 M 0.719 MR P RCT 73 7556 CHF RR 3368 1095 D 14 M 0.8 MR P RCT 73 75

Amarasingham 57 CHF RR 1372 30 D 12 MH 0.73 MR P COH 57 61et al.412 57 CHF RR 1372 30 V 12 MH 0.69 MR P COH 57 61

27 CHF RR 1341 30 V 4 H 0.56 MR R COH 57 6127 CHF RR 1372 30 V 4 M 0.73 MR R COH 57 6130 CHF RR 1372 30 V 24 M 0.72 MR R COH 57 6139 CHF RR 1372 30 V 20 M 0.84 MR R COH 57 6139 CHF RR 1341 30 V 20 H 0.61 MR R COH 57 6157 CHF RR 1372 30 V 12 M 0.86 MR R COH 57 6130 CHF RR 1341 30 V 24 H 0.66 MR R COH 57 6157 CHF RR 1341 30 V 12 H 0.72 MR R COH 57 61

Lee et al.413 58 CHF RR 50816 7 D 7 M 0.81 CD R REG 74 4958 CHF RR 50816 30 D 12 M 0.76 CD R REG 74 49

O’Connor 59 CHF RR 433 182 D 4 M 0.78 MR P RCT 56 73et al.414 60 CHF RR 433 182 D 2 M 0.68 MR P RCT 56 73

60 CHF RR 433 182 V 2 M 0.74 MR P RCT 65 76Van Walraven 61 CHF RR 2406 30 D 4 MH 0.7 MR P COH 61 47et al.415 62 CHF AR 2406 30 D 4 MH 0.71 MR P COH 61 47

62 CHF AR 2406 30 V 4 MH 0.69 MR P COH 61 4762 CHF AR 4812 30 D 4 MH 0.80 MR P COH 61 4762 CHF AR 4812 30 V 4 MH 0.70 MR P COH 61 4762 CHF AR 1M 30 V 4 MH 0.68 MR P COH 59 5262 CHF AR 4812 30 D 4 H 0.688 MR P COH 61 47

Allen et al.416 63 CHF RR 2033 168 D 8 M 0.74 MR P RCT 67 7564 CHF RR 2033 168 D 9 M 0.72 MR P RCT 67 7565 CHF AR 2033 168 D 9 M 0.72 MR P RCT 67 7565 CHF AR 2033 168 V 9 M 0.73 MR P RCT 67 75

Axente et al.417 66 CHF RR 101 1342 D 5 M MR P COH 71 51Ky et al.193 49 CHF RR 1141 365 V 17 MH 0.81 MR P COH 56 67

TableS6– Continued on next page

228 Supplementary data

TableS6– Continued from previous pagePaper N Pop SM Pt Du P # E C DS V Type Age ♂

67 CHF RR 1141 365 D 1 MH 0.75 MR P COH 56 6770 CHF RR 1141 365 D 18 MH 0.83 MR P COH 56 6771 CHF RR 1141 365 D 18 MH 0.82 MR P COH 56 6772 CHF RR 1141 365 D 19 MH 0.82 MR P COH 56 6768 CHF RR 1141 365 D 1 MH 0.77 MR P COH 56 6769 CHF RR 1141 365 D 2 MH 0.80 MR P COH 56 67

Manzano et al.418 73 CHF RR 1400 640 D 10 MH 0.68 MR P RCT 76 6773 CHF RR 728 640 V 10 MH 0.66 MR P RCT 76 6474 CHF RR 1400 640 D 9 M 0.72 MR P RCT 76 6774 CHF RR 728 640 V 9 M 0.69 MR P RCT 76 64

Senni et al.419 75 CHF RR 2012 365 D 14 M 0.88 MR P COH 68 7075 CHF RR 4049 365 V 14 M 0.83 MR P COH 70 6176 CHF AR 2012 365 D 11 M 0.87 MR P COH 68 7076 CHF AR 4049 365 V 11 M 0.82 MR P COH 70 61

Smith et al.420 58 CHF RR 68380 7 V 7 M 0.75 MR R COH 74 4977 CHF RR 4696 1825 D 4 MH 0.63 MR R COH 4978 CHF RR 4696 1825 D 8 MH 0.67 MR R COH 4979 CHF RR 4696 1825 D 10 MH 0.68 MR R COH 4980 CHF RR 4696 1825 D 14 MH 0.69 MR R COH 4981 CHF RR 4696 1825 D 22 MH 0.71 MR R COH 49

Subramanian 82 CHF RR 963 365 D 5 M 0.73 MR P RCT 61 78et al.421 83 CHF RR 963 365 D 5 M 0.74 MR P RCT 61 78

84 CHF RR 963 365 D 5 M 0.81 MR P RCT 61 78Van Spall 58 ADHF RR 68380 1 V 7 M 0.81 MR R COH 74 49et al.422 58 ADHF RR 68380 0 V 7 M 0.88 MR R COH 74 49

85 ADHF RR 68380 30 D 2 M 0.65 MR R COH 76 4985 ADHF RR 68380 7 D 2 M 0.68 MR R COH 76 4985 ADHF RR 68380 1 D 2 M 0.72 MR R COH 76 4985 ADHF RR 68380 0 D 2 M 0.82 MR R COH 76 4958 ADHF RR 68380 30 V 12 M 0.71 MR R COH 74 49

Au et al.423 45 CHF RR 59652 30 V 34 M 0.69 CD R REG 76 5045 CHF RR 59652 40 V 34 H 0.59 CD R REG 76 5045 CHF RR 23454 40 V 34 M 0.68 CD R REG 76 5045 CHF RR 23454 30 V 34 H 0.59 CD R REG 76 5045 CHF RR 19764 30 V 34 H 0.58 CD R REG 76 5045 CHF RR 19764 30 V 34 M 0.66 CD R REG 76 5045 CHF RR 59652 30 V 34 MH 0.61 CD R REG 76 5045 CHF RR 23454 40 V 34 MH 0.60 CD R REG 76 5045 CHF RR 19764 30 V 34 MH 0.59 CD R REG 76 5045 CHF RR 59652 30 V 34 M 0.72 CD R REG 76 5045 CHF RR 23454 40 V 34 M 0.69 CD R REG 76 5045 CHF RR 19764 30 V 34 M 0.67 CD R REG 76 5086 CHF AR 59652 40 V 4 M 0.67 CD R REG 76 5086 CHF AR 23454 30 V 4 M 0.64 CD R REG 76 5086 CHF AR 19764 30 V 4 M 0.66 CD R REG 76 5086 CHF AR 59652 40 V 4 H 0.60 CD R REG 76 5086 CHF AR 23454 30 V 4 H 0.61 CD R REG 76 5086 CHF AR 19764 30 V 4 H 0.60 CD R REG 76 5086 CHF AR 59652 40 V 4 MH 0.61 CD R REG 76 5086 CHF AR 23454 40 V 4 MH 0.61 CD R REG 76 5086 CHF AR 19764 30 V 4 MH 0.60 CD R REG 76 5086 CHF AR 59652 30 V 4 M 0.66 CD R REG 76 5086 CHF AR 23454 30 V 4 M 0.66 CD R REG 76 5086 CHF AR 19764 30 V 4 M 0.65 CD R REG 76 5062 CHF AR 59652 30 V 4 M 0.55 CD R REG 76 5062 CHF AR 23454 30 V 4 M 0.55 CD R REG 76 5062 CHF AR 19764 40 V 4 M 0.56 CD R REG 76 5062 CHF AR 59652 30 V 4 H 0.58 CD R REG 76 5062 CHF AR 23454 40 V 4 H 0.58 CD R REG 76 5062 CHF AR 19764 30 V 4 H 0.58 CD R REG 76 5062 CHF AR 59652 30 V 4 MH 0.59 CD R REG 76 5062 CHF AR 23454 40 V 4 MH 0.59 CD R REG 76 5062 CHF AR 19764 40 V 4 MH 0.58 CD R REG 76 5062 CHF AR 59652 30 V 4 M 0.61 CD R REG 76 5062 CHF AR 23454 30 V 4 M 0.61 CD R REG 76 5062 CHF AR 19764 30 V 4 M 0.60 CD R REG 76 5011 CHF RR 59652 30 V 4 MH 0.60 CD R REG 76 5011 CHF RR 23454 30 V 4 MH 0.59 CD R REG 76 50

TableS6– Continued on next page

229

TableS6– Continued from previous pagePaper N Pop SM Pt Du P # E C DS V Type Age ♂

11 CHF RR 19764 40 V 4 MH 0.59 CD R REG 76 5011 CHF RR 59652 30 V 4 H 0.68 CD R REG 76 5011 CHF RR 23454 30 V 4 H 0.64 CD R REG 76 5011 CHF RR 19764 40 V 4 MH 0.58 CD R REG 76 5011 CHF RR 19764 40 V 4 H 0.66 CD R REG 76 5011 CHF RR 59652 30 V 4 MH 0.58 CD R REG 76 5011 CHF RR 23454 30 V 4 MH 0.58 CD R REG 76 5011 CHF RR 19764 40 V 4 M 0.66 CD R REG 76 5011 CHF RR 59652 30 V 4 M 0.71 CD R REG 76 5011 CHF RR 23454 30 V 4 M 0.68 CD R REG 76 50

Barlera et al.424 32 CHF RR 6975 1058 V 14 M 0.74 MR P RCT 77 7587 CHF RR 6975 1058 D 25 M 0.76 MR P RCT 77 7588 CHF RR 6975 1058 D 12 M 0.75 MR P RCT 77 75

Bayes-Genis 89 CHF RR 891 1018 D 11 M 0.76 MR P COH 70 72et al.425 90 CHF RR 891 1018 D 12 M 0.77 MR P COH 70 72

91 CHF RR 891 1018 D 12 M 0.78 MR P COH 70 7292 CHF RR 891 1018 D 13 M 0.79 MR P COH 70 72

Clemens et al.257 32 CHF RR 427 365 V 14 M 0.74 MR P COH 62 7332 CHF RR 427 1825 V 14 M 0.76 MR P COH 62 7332 CHF RR 427 730 V 14 M 0.80 MR P COH 62 7393 CHF RR 427 365 D 15 M 0.74 MR P COH 62 7393 CHF RR 427 1825 D 15 M 0.76 MR P COH 62 7393 CHF RR 427 730 D 15 M 0.79 MR P COH 62 7394 CHF RR 427 1825 D 15 M 0.76 MR P COH 62 7394 CHF RR 427 365 D 15 M 0.78 MR P COH 62 7394 CHF RR 427 730 D 15 M 0.81 MR P COH 62 7395 CHF RR 427 1825 D 15 M 0.76 MR P COH 62 7395 CHF RR 427 365 D 15 M 0.79 MR P COH 62 7395 CHF RR 427 730 D 15 M 0.81 MR P COH 62 7396 CHF RR 427 1825 D 15 M 0.77 MR P COH 62 7396 CHF RR 427 365 D 15 M 0.77 MR P COH 62 7396 CHF RR 427 730 D 15 M 0.80 MR P COH 62 7397 CHF RR 427 1825 D 15 M 0.75 MR P COH 62 7397 CHF RR 427 365 D 15 M 0.76 MR P COH 62 7397 CHF RR 427 730 D 15 M 0.80 MR P COH 62 7398 CHF RR 427 365 D 15 M 0.74 MR P COH 62 7398 CHF RR 427 1825 D 15 M 0.76 MR P COH 62 7398 CHF RR 427 730 D 15 M 0.80 MR P COH 62 7399 CHF RR 427 365 D 15 M 0.76 MR P COH 62 7399 CHF RR 427 1825 D 15 M 0.76 MR P COH 62 7399 CHF RR 427 730 D 15 M 0.80 MR P COH 62 73100 CHF RR 427 1825 D 16 M 0.78 MR P COH 62 73100 CHF RR 427 365 D 16 M 0.81 MR P COH 62 73100 CHF RR 427 730 D 16 M 0.82 MR P COH 62 73

de la Cámaraet al.426 101 CHF RR 600 365 D 5 M 0.76 MR P COH 74 49

Ketchum et al.194 53 CHF RR 961 365 V 17 M 0.69 MR P COH 62 80102 CHF RR 961 365 V 1 M 0.66 MR P COH 62 80103 CHF RR 961 365 D 18 M 0.73 MR P COH 62 80

Lee et al.427 104 CHF RR 7433 7 D 10 M 0.81 MR P COH 75 52104 CHF RR 5158 7 V 10 M 0.83 MR P COH 76 52

Martín-Sánchez 17 ADHF RR 1068 30 V 10 M 0.69 CD R REG 80 47et al.190 105 ADHF RR 1068 30 D 11 M 0.75 CD R REG 80 47

ADHF RR 1068 30 V 10 M 0.65 CD R REG 80 47O’Connor 106 CHF RR 2331 912 D 9 MH 0.64 MR P RCT 59 72et al.428 107 CHF RR 2331 912 D 10 M 0.74 MR P RCT 59 72

108 CHF AR 2331 912 D 4 MH 0.63 MR P RCT 59 72109 CHF AR 2331 912 D 4 M 0.7 MR P RCT 59 72

Oh et al.429 110 CHF RR 239 730 D 4 M 0.78 MR P COH 67 67110 CHF RR 66 730 V 4 M 0.8 MR P COH 67 70

Perrotta et al.430 32 CHF RR 342 730 V 14 M 0.69 MR P COH 72 7932 CHF RR 342 1825 V 14 M 0.69 MR P COH 72 7932 CHF RR 342 365 V 14 M 0.70 MR P COH 72 79

Postmus et al.431 111 CHF RR 1023 549 D 11 M 0.73 MR P RCT 71 62111 ADHF RR 576 549 V 11 M 0.70 MR P RCT 74 51112 CHF RR 1023 549 D 5 H 0.66 MR P RCT 71 62

Regoli et al.432 32 CHF RR 1139 365 V 14 M 0.66 MR R REG 67 77TableS6– Continued on next page

230 Supplementary data

TableS6– Continued from previous pagePaper N Pop SM Pt Du P # E C DS V Type Age ♂

32 CHF RR 1139 730 V 14 M 0.67 MR R REG 67 7732 CHF RR 1139 1825 V 14 M 0.68 MR R REG 67 77

Richter et al.433 113 CHF RR 349 1825 D 8 M 0.81 MR P COH 75 66114 CHF RR 349 1825 D 13 M 0.77 MR P COH 75 66115 CHF RR 349 1825 D 8 M 0.80 MR P COH 75 66

Wang et al.195 116 CHF RR 198640 30 D 49 MH 0.80 MR R COH 73 98116 CHF RR 198640 30 D 49 M 0.80 MR R COH 73 98116 CHF RR 198640 30 D 49 H 0.82 MR R COH 73 98117 CHF RR 198640 365 D 65 M 0.76 MR R COH 73 98117 CHF RR 198640 365 D 65 MH 0.77 MR R COH 73 98117 CHF RR 198640 365 D 65 H 0.82 MR R COH 73 98

N: Model number; Pt: Number of patients; Du: Duration; C: C-statistic; ♂: % male;Pop: Diagnosis of patients; CHF: chronic heart failure; ADHF: acute decompensated heart failure;SM: Statistical model; RR: regression; AR: Point-based additive risk score; CA: CART Model;V: View of study; P: Prospective; R: Retrospective;E: Event type; M: Mortality; H: Hospitalization; MH: Mortality or Hospitalizaion;DS: data source; MR: Medical Record; CD: Claims DataP: Procedure (Derivation or Validation); D: Derivation, V: Validation; #: Number of variables in model;Type: Type of study; COH: cohort; REG: registry; RCT: randomized controlled trial

231

Table S7: Description of the variables used in development of multivariate risk prediction models(Chapter 3) (percentage (number), mean ± standard deviation (SD) or median (interquartilerange (IQR)), with the percentage and number of values missing for patients

Index Validationmissing missing

Sex (male) 73.4% (1846) 0% (0) 65.9 (1145) 0% (0)Age (years) 68.9 ± 12 0% (0) 73.7 ± 10.7 0% (0)Smoking 0% (0) 1% (12)

Past 48% (1220) 35% (602)Current 14% (353) 13.7% (236)

Alcohol usage 28% (700) 1% (4) 47% (790) 2% (40)Body mass index (kg/m2) 27.9 ± 5.5 2% (38) 28.1 ± 6.4 2% (35)Heart rate (beats/ min) 80 ± 19.5 1% (6) 74.2 ± 16.6 2% (38)Systolic blood pressure (mmHg) 124.7 ± 21.9 1% (5) 125.9 ± 22.6 2% (28)Systolic blood pressure (mmHg) 74.9 ± 13.4 1% (5) 69.2 ± 13.2 2% (28)Left ventricular ejection fraction (%) 31 ± 10.6 11% (274) 41 ± 13.0 9% (163)HFpEF (LVEF>45%) 7 (162) 11% (274) 34% (529) 9% (163)NYHA class 3% (70) 1% (1)

I 2.2% (56) 1.0% (17)II 34.5% (868) 41.0% (712)III 48.8% (1228) 44.4% (772)IV 11.7% (294) 13.6% (236)

Ischemic heart disease 60.5% (1358) 11% (273) 64.9% (1128) 0% (0)Hospitalization in year before inclusion 31.6% (794) 0% (0) 26.5% (460) 0% (0)History of atrial fibrillation 45.4% (1143) 0% (0) 43.7% (760) 1% (14)Diabetes mellitus 32.6% (819) 0% (0) 32.3% (561) 1% (9)Hypertension 62.4% (1569) 0% (0) 57.9% (1007) 1% (7)eGFR (CKD-EPI) (mL/ min /1.73 m2) 64.4 (47.5-83.4) 6% (155) 66.1 (47.5-83.4) 1% (6)Myocardial infarction 38.3% (963) 0% (0) 48.8% (849) 1% (4)Coronary artery bypass graft 17.2% (433) 0% (0) 17.7% (308) 1% (2)Percutaneous coronary intervention 21.6% (544) 0% (0) 18.7% (325) 1% (18)Stroke 9.3% (233) 0% (0) 18.1% (315) 1% (16)Peripheral artery disease 10.9% (273) 0% (0) 21.5% (374) 3% (45)Chronic obstructive pulmonary disease 17.3% (436) 0% (0) 18.4% (319) 1% (15)Pulmonary congestion 3% (71) 5% (84)

Single base 12.7% (311) 5.7% (95)Bi-basilar 40.1% (980) 38.7% (639)

Edema 29.7 (624) 17% (417) 54.9 (955) 11% (192)Elevated jugular venous pressure 22% (554) 34% (861) 25.9% (450) 0% (0)Hepatomegaly 14.3% (358) 1% (7) 3.5% (60) 10% (171)Rales >1⁄3 up lung fields 19.2% (248) 49% (1225) 2.9% (50) 0% (0)Baseline medication

ACE-inhibitor/ARB 72.3% (1820) 0% (0) 70.1% (1218) 0% (0)Beta-blocker 83.2% (2093) 0% (0) 72.7% (1264) 0% (0)

Hematocrit (%) 40.1% (36.3-43.7) 11% (274) 40.5% (37.0-44.3) 1% (18)Blood urea nitrogen (mmol/L) 11.1 (7.4-17.6) 12% (301) 8.6 (6.5-11.9) 1% (9)NT-proBNP (pg/mL) 4275 (2360-8486) 53% (1334) 1376 (510-3548) 2% (29)Sodium (mmol/L) 140 (137-142) 8% (189) 139.0 (137.0-141.0) 1% (7)Potassium(mmol/L) 4.2 (3.9-4.6) 8% (192) 4.3 (4.0-4.6) 1% (13)Bilirubin (µmol/L) 14 (10-21) 45% (1135) 10 (7-15) 1% (20)HDL-cholesterol (mmol/L) 1 (0.8-1.3) 54% (1350) 1 (0.9-1.4) 4% (72)Alkaline phosphatase (µg/L) 84 (65-117) 6% (156) 89 (72-116) 1% (10)Hemoglobin (g/dL) 13.3 (11.9-14.5) 9% (223) 13.2 (11.8-14.5) 1% (16)Albumin (g/L) 33 (27-38) 6% (156) 38 (34-42) 1% (13)ALAT (U/L) 25 (19-35) 39% (981) 22 (17-33) 1% (23)ASAT (U/L) 25 (17-38) 28% (712) 23 (18-31) 6% (105)Glucose (mmol/L) 6.3 (5.5-7.9) 25% (622) 6.3 (5.2-8.4) 14% (248)ALAT: alanine aminotransferase; ALAT: alanine aminotransferase; eGFR: estimated glomerular filtration rate;HDL: high density lipoprotein; HFpEF: heart failure with preserved ejection fraction;LVEF: left ventricular ejection fraction; NYHA class: New York Heart Association class;NT-proBNP: N-terminal pro B-type natriuretic peptide

232 Supplementary data

Table S8: Variables used in the stepwise regression methods (Chapter 4) to predict successfulor not successful up-titration, with number (percentage), mean ± SD, or median (IQR)

Description of baseline patient characteristicsN 2100 LaboratoryDemographics eGFR (CKD-EPI) (mL/ min /1.73 m2) 66.7 ± 23.66Sex (Male) 1589 (75.7%) Hematocrit (%) 40.5 ± 5.26Age (years) 67.7 ± 11.95 Blood urea nitrogen (mmol/L) 10.8 (7.3-17.17)Country NT-proBNP (pg/mL) 4138 (2249-8220)

Netherlands 276 (13.1%) Hemoglobin (g/L) 13.4 ± 1.85Germany 84 (4%) Sodium (mmol/L) 139.2 ± 3.83France 195 (9.3%) Potassium (mmol/L) 4.3 ± 0.55Greece 278 (13.2%) BNP (pg/mL) 637 (291-1197)Italy 289 (13.8%) Bilirubin (µmol/L) 14 (9.92-20.61)Norwegen 93 (4.4%) Total-cholesterol (mmol/L) 4.3 ± 1.36Poland 244 (11.6%) HDL-cholesterol (mmol/L) 1.1 ± 0.39Serbia 366 (17.4%) Hepcidin (nmol/L) 6.5 (2.3-17)Slovenia 22 (1%) STfR (mg/L) 1.5 (1.14-2.02)Sweden 96 (4.6%) FT4 (pmol/L) 15.8 (13.16-18.9)United Kingdom 157 (7.5%) HbA1c (%) 6.3 (5.74-7.12)

Smoking ASAT (U/L) 25 (17-38)No 772 (36.8%) ALAT (U/L) 25 (19-35)Past 1026 (48.9%) TSH (µU/L) 1.8 (1.19-2.9)Current 302 (14.4%) Gamma-GT (U/L) 54 (28-103)

Alcohol usage 595 (28.4%) Alkaline phosphatase (µg/L) 84 (64.98-117)Body mass index (kg/m2) 28 ± 5.52 TnI (pg/mL) 12.2 (6.56-25.87)NYHA class ET-1 (pg/mL) 5.2 (3.93-6.93)

I 54 (2.6%) Bio-ADM (pg/mL) 31.8 (21.95-49.67)II 760 (37.1%) Proteinuria (pg/dL) 5.0 (0-19.25)III 1004 (49%) Troponin (µg/L) 0.04 (0.01-0.10)IV 232 (11.3%)

Clinical ProfileLeft ventricular ejection fraction (%) 28.6 ± 7.49Heart Rate (beats/ min) 79.8 ± 19.43Systolic blood pressure (mmHg) 124.2 ± 21.24Diastolic blood pressure (mmHg) 75.5 ± 13.05Pulmonary congestion

Single base 260 (12.7%)Bi-basilar 756 (37%)

Peripheral oedema 988 (47%)Elevated jugular venous pressure 442 (30%)Hepatomegaly 291 (13.9%)3rd Heart Tone 220 (10.5%)Rales >1⁄3 up lung fields 183 (18%)Orthopnea present 678 (32.3%)Medical HistoryIschemic heart disease 1154 (55%)Hospitalizationin year before inclusion 669 (31.9%)Heart failure duration (years) 8 (3.55-13.27)Diabetes mellitus 676 (32.2%)Atrial fibrillation 901 (42.9%)Myocardial infarction 822 (39.1%)Coronary artery bypass graft 344 (16.4%)Coronary artery disease 957 (45.6%)Percutaneous coronary intervention 473 (22.5%)Stroke 187 (8.9%)Peripheral arterial disease 214 (10.2%)COPD 344 (16.4%)

233

Table S9: CRF page on how ACE-inhibitor/ARB and beta-blocker medication was recorded

ACE-inhibitor/ARB

Drug name* Total dailydose (mg)

Start date(dd/mm/yyyy)

End date(dd/mm/yyyy) Ongoing at 9

month visitReason # Specify reason

Beta-blocker

Drug name* Total dailydose (mg)

Start date(dd/mm/yyyy)

End date(dd/mm/yyyy) Ongoing at 9

month visitReason # Specify reason

*also include drugs stopped within 3 months before inclusion

reasons #1=Non optimal dose acc. to ESC guidelines;2=Symptoms;3=Side effects ;4=Non-cardiac organ dysfunction;99=Other, specify

234 Supplementary data

Table S10: Description of the variables used in development of treatment-selection model, withmean ± SD, or median (IQR)

Mean ± SD ormedian (IQR))

%Missing

Mean ± SD ormedian (IQR))

%Missing

Standard laboratory results Olink Proseek Multiplex panel (NPX)Hematocrit (%) 40.13 ± 5.3 6% TNFRSF14 (NPX) 4.20 ± 0.84 0%Total Cholesterol(mmol/L) 4.32 ± 1.34 41% LDL-receptor (NPX) 3.01 ± 0.87 0%Serum creatinine(µmol/L) 101.0 (83.1-127.0) 0% ITGB2 (NPX) 4.40 ± 0.73 10%BUN (mmol/L) 14.51 ± 11.65 12% IL-17RA (NPX) 3.25 ± 0.71 0%LVEF (%) 31.05 ± 10.58 10% TNF-R2 (NPX) 4.35 ± 0.88 0%NT-proBNP (ng/L) 3949 (2254-7690) 51% MMP-9 (NPX) 3.09 ± 1.05 0%Hemoglobin (g/dL) 13.25 ± 1.88 4% EPHB4 (NPX) 1.54 ± 0.58 0%Sodium (mmol/L) 139.31 ± 3.79 2% IL2-RA (NPX) 3.65 ± 0.82 0%Potassium (mmol/L) 4.26 ± 0.56 2% OPG (NPX) 2.63 ± 0.71 0%BNP (local) (pg/mL) 662 (354-1281) 88% ALCAM (NPX) 4.1 ± 0.63 0%Total Bilirubin (µmol/L) 13.68 (9.80-20.52) 41% TFF3 (NPX) 5.22 ± 0.93 0%Glucose (mmol/L) 6.27 (5.38-7.9) 20% SELP (NPX) 8.21 ± 1.13 0%LDL-cholesterol(mmol/L) 2.61 ± 1.07 54% CSTB (NPX) 4.63 ± 0.87 0%HDL-cholesterol(mmol/L) 1.11 ± 0.38 51% MCP-1 (NPX) 2.26 ± 0.69 0%Serum Iron (local)(µmol/L) 12.0 (8.0-16.7) 78% CD163 (NPX) 6.77 ± 0.8 0%Calcium (mmol/L) 1.77 (1.51-2.03) 4% Gal-3 (NPX) 4.42 ± 0.71 0%Phosphate (mmol/L) 0.85 (0.68-1.03) 4% GRN (NPX) 2.99 ± 0.64 0%Albumin (g/L) 32 (27-38) 4% MEPE (NPX) 2.21 ± 0.72 0%Serum Iron (UMCG)(µg/L) 8 (5-13) 4% BLM hydrolase (NPX) 4.51 ± 0.66 0%Ferritin (µg/L) 102 (50-192) 4% PLC (NPX) 6.41 ± 0.76 0%Transferrin (g/L) 2.0 (1.6-2.5) 4% LTBR (NPX) 3.00 ± 0.75 0%Hepcidin (nmol/L) 6.7 (2.2-17.0) 4% NOTCH3 (NPX) 3.18 ± 0.75 0%sTfR (mg/L) 1.51 (1.16-2.06) 5% TIMP4 (NPX) 4.46 ± 0.82 0%FT4 pmol/L) 16 (13.6-19.13) 77% CNTN1 (NPX) 1.85 ± 0.67 0%HbA1c (%) 6.58 ± 1.49 79% CDH5 (NPX) 2.74 ± 0.71 0%ASAT (U/L) 25 (17-38) 23% TLT-2 (NPX) 3.49 ± 0.77 0%ALAT (U/L) 25 (19-35) 31% FABP4 (NPX) 5.28 ± 1.32 0%TSH (mU/L) 1.8 (1.1-2.8) 60% TFPI (NPX) 7.68 ± 0.73 0%Proteinuria (mg/dL) 5 (0-17) 90% PAI (NPX) 4.89 ± 1.19 0%Gamma-GT (mU/L) 54 (28-107) 50% CCL24 (NPX) 4.83 ± 1.08 0%Alkaline phosphatase(µg/L) 83.59 (64.78-116) 49% TR (NPX) 5.01 ± 0.83 0%Troponin I (pg/mL) 12.35 (6.75-26.69) 3% TNFRSF10C (NPX) 5.23 ± 0.77 0%ET-1 (pg/mL) 5.27 (4.00-6.99) 4% GDF-15 (NPX) 4.92 ± 1.02 0%pro-ENK (pmol/L) 84.45 (62.77-116.71) 0% SELE (NPX) 1.49 ± 0.78 0%bio-ADM (pg/mL) 32.99 (22.41-51.55) 0% AZU1 (NPX) 2.13 ± 0.95 0%Troponin (µg/L) 0.03 (0.01-0.10) 72% DLK-1 (NPX) 4.20 ± 0.94 0%FGF-23 (RU/mL) 211.7 (118.1-524.2) 0% SPON1 (NPX) 1.70 ± 0.65 0%Erythrocytes(10 · 1012/L) 4.48 (4.05-4.88) 26% MPO (NPX) 3.51 ± 0.71 0%Platelets (10 · 109/L) 215 (173-260) 17% CXCL16 (NPX) 5.50 ± 0.67 0%Leucocytes(10 · 109/L) 7.8 (6.41-9.46) 16% IL6-RA (NPX) 10.08 ± 0.66 0%

Alere Luminex Panel RETN (NPX) 5.96 ± 0.84 0%ANP-propeptide(ng/mL) 20.47 (12.71-31.02) 3% IGFBP-1 (NPX) 4.58 ± 1.35 0%BNP (pg/mL) 223.12 (90.58-452.6) 3% CHIT1 (NPX) 2.16 ± 1.51 0%ESAM-1 (ng/mL) 63.84 (57.31-70.4) 3% TR-AP (NPX) 4.31 ± 0.70 0%LTβR (ng/mL) 0.15 (0.10-0.23) 3% CCL22 (NPX) 1.58 ± 0.98) 0%Mesothelin (ng/mL) 54.73 ± 12.66 3% PSP-D (NPX) 2.1 ± 0.80 0%MPO (ng/mL) 31.51 ± 14.69 3% PI3 (NPX) 3.27 ± 0.85 0%Neuropilin (ng/mL) 21.8 ± 7.67) 3% Ep-Cam (NPX) 2.93 ± 1.00 0%NT-proCNP (pg/mL) 12.31 ± 14.26 3% AP-N (NPX) 4.24 ± 0.71 0%OPN (ng/mL) 220.44 ± 63.96 3% AXL (NPX) 7.07 ± 0.72 0%PCT (pg/mL) 15.95 (5.97-36.58) 3% IL-1RT1 (NPX) 5.83 ± 0.71 0%PSAP-B (ng/mL) 31.46 (22.94-37.85) 3% MMP-2 (NPX) 2.77 ± 0.79 0%

TableS10– Continued on next page

235

TableS10– Continued from previous pageMean ± SD ormedian (IQR))

%Missing

Mean ± SD ormedian (IQR))

%Missing

VEGFR-1 (ng/mL) 0.14 (0.14-0.23) 3% FAS (NPX) 4.15 ± 0.71 0%D-dimer (ng/mL) 101.92 (101.92-135.41) 3% MB (NPX) 6.22 ± 1.00 0%Pentraxin-3 (ng/mL) 2.03 (1.24-3.41) 3% TNFSF13B (NPX) 5.35 ± 0.78 0%PIGR-1 (ng/mL) 123.89 (76.6-200.64) 3% PRTN3 (NPX) 3.99 ± 0.81 0%RAGE (ng/mL) 2.75 (1.93-4.03) 3% PCSK9 (NPX) 1.84 ± 0.58 0%Syndecan-1 (ng/mL) 2.17 (1.16-3.87) 3% U-PAR (NPX) 4.06 ± 0.75 0%TNF-R1A (ng/mL) 1.02 (0.61-1.67) 3% OPN (NPX) 4.79 ± 0.95 0%Troy (ng/mL) 0.24 (0.13-0.41) 3% CTSD (NPX) 3.21 ± 0.70 0%GDF-15 (ng/mL) 3.44 (2.72-4.30) 3% PGLYRP1 (NPX) 6.56 ± 0.84 0%ProADM (ng/mL) 0.49 (0.32-0.78) 3% CPA1 (NPX) 3.70 ± 1.10 0%ST2 (ng/mL) 8.51 (3.81-18.36) 3% JAM-A (NPX) 4.64 ± 1.24 0%WAP-4C (ng/mL) 1.41 (0.77-2.83) 3% Gal-4 (NPX) 3 ± 0.80 0%Periostin (ng/mL) 6.12 (3.52-9.85) 3% IL-1RT2 (NPX) 4.02 ± 0.67 0%Angiogenin (ng/mL) 4565 (3147-7002) 3% SHPS-1 (NPX) 2.93 ± 0.70 0%Cystatin C (ng/mL) 15074 (10282-22083) 3% CCL15 (NPX) 6.55 ± 0.81 0%CRP (ng/mL) 12898 (5739-26146) 3% CASP-3 (NPX) 6.74 ± 1.72 0%Gal-3 (ng/mL) 20.84 (15.13-29.09) 3% uPA (NPX) 3.87 ± 0.69 0%NGAL (ng/mL) 58.85 (37.48-93.25) 3% CPB1 (NPX) 3.41 ± 1.05 0%

CHI3L1 (NPX) 5.63 ± 1.20 0%(NPX) 3.75 ± 1.02 0%t-PA (NPX) 5.05 ± 1.44 0%SCGB3A2 (NPX) 2.17 ± 1.04 0%EGFR (NPX) 0.59 ± 0.51 0%IGFBP-7 (NPX) 3.69 ± 0.91 0%CD93 (NPX) 8.86 ± 0.68 0%IL-18BP (NPX) 5.67 ± 0.77 0%COL1A1 (NPX) 1.61 ± 0.67 0%PON3 (NPX) 4.22 ± 1.02 0%CTSZ (NPX) 4.15 ± 0.70 0%MMP-3 (NPX) 6.71 ± 1.01 0%RARRES2 (NPX) 10.97 ± 0.60 0%ICAM-2 (NPX) 4.26 ± 0.72 0%KLK6 (NPX) 2.74 ± 0.48 0%PDGF(NPX) 1.86 ± 1.18 0%TNF-R1 (NPX) 4.95 ± 0.93 0%IGFBP-2 (NPX) 7.59 ± 0.92 0%vWF (NPX) 6.08 ± 1.36 0%PECAM-1 (NPX) 4.29 ± 0.99 0%NT-proBNP (NPX) 2.96 ± 1.35 0%CCL16 (NPX) 5.37 ± 0.86 0%

236 Supplementary data

Table S11: Biomarkers predictive for successful up-titration to recommended ACE-inhibitors/ARBs doses (Chapter 5)

log(OR) SE p log(OR) SE pIntercept 1.1389 1.4057 0.42 BUN (mmol/L) -0.0059 0.011 0.59NYHA class -0.0147 0.0467 0.75 LVEF (%) -0.0216 0.0152 0.15Ischemic etiology -0.0642 0.0558 0.25 NT-proBNP (ng/L) <0.00001 <0.00001 0.86Atrial fibrillation -0.0322 0.0911 0.72 Hemoglobin (g/dL) <0.00001 <0.00001 0.82Diabetes mellitus -0.1097 0.1919 0.57 Glucose (mmol/L) 0.0059 0.0251 0.82Hypertension 0.1547 0.1219 0.20 LDL (mmol/L) 0.0328 0.0301 0.28Smoking 0.1567 0.1361 0.25 HDL (mmol/L) 0.0701 0.1831 0.70Alcohol use 0.0387 0.1071 0.72 Calcium (mmol/L) 0.0075 0.0112 0.50Coronary artery disease 0.1307 0.1576 0.41 Phosphate (mmol/L) 0.084 0.1558 0.59Renal disease -0.0733 0.1898 0.70 Albumin (g/L) 0.072 0.1858 0.70Myocardial infarction -0.2858 0.2139 0.18 ASAT (U/L) 0.0105 0.0316 0.74Valvular surgery -0.0512 0.1532 0.74 Proteinuria (mmol/dL) -0.0076 0.0223 0.73

PCI -0.2062 0.2174 0.34 Alkaline phosphatase(µg/mL) -0.0001 0.0006 0.81

Device therapy -0.0371 0.0931 0.69 Troponin I (pg/mL) -0.0013 0.0021 0.54Height (m) -0.1533 0.1026 0.14 Pro-ENK (pmol/L) -0.0002 0.0009 0.83Weight (kg) 0.0024 0.0065 0.711 Bio-ADM (pg/mL) -0.0006 0.0015 0.70Heart rate (beats/ min) 0.0087 0.0076 0.26 FGF-23 RU/mL -0.0001 0.0002 0.74

SBP (mmHg) 0.0001 0.0074 0.99 ANP-propeptide(ng/mL) -0.0002 0.0002 0.39

DBP (mmHg) 0.0109 0.0036 0.003 Periostin (ng/mL) 0.0007 0.0226 0.98Pulmonary congestion -0.0199 0.0825 0.81 Gal-3 (ng/mL) -0.0009 0.003 0.77Elevated JVP -0.1024 0.0805 0.20 NGAL (ng/mL) -0.0042 0.005 0.40

Hepatomegaly -0.0665 0.1763 0.71 Serum creatinine(µmol/L) -0.0003 0.0012 0.80

3rd heart tone -0.3022 0.2297 0.19 T-PA (NPX) -0.0026 0.0382 0.94BMI (kg/m2) 0.0007 0.009 0.94 TNF-R1 (NPX) -0.0245 0.0715 0.73Rales >1⁄3 up lung fields 0.0049 0.018 0.78 IGFBP-2 (NPX) -0.1036 0.099 0.30Total cholesterol(mmol/L) 0.0047 0.0217 0.83 ST2 (NPX) -0.0053 0.0295 0.86

BMI: body mass index; BUN: Blood urea nitrogen;COPD:Chronic obstructive pulmonary disease;DBP: diastolic blood pressure; eGFR: estimated glomerular filtration rate; JVP: Jugular venous pressure;LVEF: Left ventricular ejection fraction; NPX: normalized protein expression units;NYHA class: New York Heart Association class; OR: Odds ratio; PCI: Percutaneous coronary intervention;p: p-value; SBP: Systolic blood pressure; SE: standard error

237

Table S12: Biomarkers predictive for successful beta-blocker up-titration to recommended doses(Chapter 5)

log(OR) SE p log(OR) SE pIntercept -5.8903 3.9583 0.14 FT4 (pmol/L) -0.0815 0.0812 0.32Male gender 0.0866 0.2228 0.70 ASAT (U/L) 0.0107 0.0305 0.73Race 0.229 0.2594 0.38 ALAT (U/L) 0.0023 0.0031 0.462Previous heart failurehospitalization in yearbefore inclusion

-0.1046 0.2018 0.60 TSH (mU/L) 0.0077 0.0225 0.73

Valvular disease -0.029 0.0848 0.73 CRP (ng/mL) <0.000001 <0.000001 0.72Heart failure duration 0.1421 0.1381 0.30 Proteinuria (mg/dL) 0.0196 0.0346 0.57NYHA class -0.0052 0.0069 0.46 Gamma-GT (U/L) -0.0008 0.0036 0.81

Ischemic etiology -0.0218 0.044 0.62 Alkaline phosphatase(µg/L) 0.0001 0.0022 0.98

Atrial fibrillation 0.0093 0.0524 0.86 Troponin I (pg/mL) -0.0017 0.0017 0.31Diabetes mellitus 0.0581 0.1033 0.57 ET-1 (pg/mL) -0.0123 0.029 0.67Hypertension -0.0325 0.0958 0.73 pro-ENK (pmol/mL) -0.053 0.0414 0.20Alcohol use 0.0639 0.1645 0.70 BNP (UMCG) (pg/mL) 0.0001 0.0003 0.72Coronary arterydisease 0.3228 0.124 0.01 ESAM-1 (ng/mL) 0.0004 0.0005 0.39Renal disease 0.1843 0.1632 0.26 MPO (ng/mL) -0.003 0.0076 0.69PCI 0.0073 0.0684 0.91 Neuropilin (ng/mL) -0.0114 0.0083 0.17Stroke 0.0023 0.1155 0.98 D-dimer (ng/mL) -0.0003 0.0008 0.70Peripheral arterydisease -0.0423 0.1262 0.74 Pentraxin-3 (ng/mL) 0.0247 0.067 0.71COPD -0.1949 0.1676 0.24 PIGR-1 ng/mL) 0.1158 0.0937 0.22Device therapy -0.0269 0.1432 0.85 GDF-15 (ng/mL) 0.0043 0.0279 0.88Weight (kg) 0.0864 0.0618 0.16 proADM (pg/mL) 0.0494 0.1336 0.71Height (m) 0.0063 0.0083 0.44 (ng/mL) 0.2341 0.247 0.34Heart rate(beats/ min) 0.0028 0.0069 0.69 WAP-4C (ng/mL) -0.0119 0.0135 0.38SBP (mmHg) 0.0123 0.008 0.13 Periostin (ng/mL) -0.029 0.0577 0.6DBP (mmHg) 0.0034 0.0085 0.69 NGAL (ng/mL) -0.0034 0.0054 0.53Pulmonary congestion -0.0325 0.1178 0.78 Gal-3 (ng/mL) -0.0015 0.0043 0.72Elevated JVP -0.1798 0.0735 0.01 CCL16 (NPX) 0.0225 0.0644 0.73Hepatomegaly -0.0321 0.0868 0.71 TNFRSF14 (NPX) -0.0008 0.0014 0.58eGFR (CKD-EPI)(mL/ min /1.73 m2) -0.0363 0.0912 0.69 OPG (NPX) -0.0576 0.1058 0.59

Hematocrit (%) -0.0197 0.0756 0.79 TFPI (NPX) -0.0602 0.1546 0.70BUN (mmol/L) -0.0033 0.0088 0.71 PAI (NPX) -0.1717 0.1959 0.38LVEF (%) -0.0113 0.017 0.51 SELE (NPX) 0.038 0.0976 0.70NT-proBNP (ng/L) 0.0112 0.0086 0.19 AZU1 (NPX) 0.1564 0.1206 0.19Sodium (mg/dL) 0.0043 0.0122 0.72 RETN (NPX) 0.0315 0.0929 0.73Potassium (mg/dL) 0.0163 0.016 0.31 IGFBP-1 (NPX) -0.0066 0.0234 0.78BNP (local) (pg/mL) 0.0376 0.1008 0.71 CHIT1 (NPX) -0.0118 0.0339 0.73Total bilirubin (µg/dL) -0.0025 0.0068 0.71 MMP-3 (NPX) 0.0409 0.1048 0.70Glucose (mg/dL) -0.0129 0.0097 0.19 RARRES2 (NPX) 0.1598 0.1377 0.25LDL-cholesterol(mmol/L) 0.0151 0.0271 0.58 PDGF

(NPX) -0.011 0.0311 0.72Serum iron (µmol/L) -0.034 0.1942 0.86 TNF-R1 (NPX) -0.0562 0.0464 0.23Calcium (mmol/L) -0.062 0.16 0.70 vWF (NPX) -0.0088 0.0463 0.85Phosphate(mmol/L) -0.1603 0.1689 0.34 Leucocytes

(10 · 109 cells/L) 0.0007 0.0009 0.43

Serum iron (µmol/L) 0.0081 0.0207 0.69 Erythrocytes(10 · 1012/L

0.0682 0.0822 0.41

Ferritin (µg/L) 0.0109 0.0184 0.55 Platelets(10 · 109 cells/L) 0.019 0.0567 0.74

sTfR (µg/L) -0.0156 0.0496 0.75BMI: body mass index; BUN: Blood urea nitrogen;COPD:Chronic obstructive pulmonary disease;DBP: diastolic blood pressure; eGFR: estimated glomerular filtration rate; JVP: Jugular venous pressure;LVEF: Left ventricular ejection fraction; NPX: normalized protein expression units;NYHA class: New York Heart Association class; OR: Odds ratio; PCI: Percutaneous coronary intervention;p: p-value; SBP: Systolic blood pressure; SE: standard error

238 Supplementary dataTa

ble

S13:

Dem

ogra

phic

sofM

clus

tclu

ster

ing

(Cha

pter

6)in

the

inde

xco

hort

,with

perc

enta

ges(

num

bers

),m

ean

±SD

,orm

edia

n(I

QR

),an

d%

ofm

issin

gva

lues

Clu

ster

s1

23

45

67

89

1011

p-v

alu

eN

654

5309

31276

19191

306

6702

17Sex(m

ale)

37%

(241)

80%

(4)

75%

(233)

87%

(27)

78%

(215)

89%

(17)

100%

(191)

82%

(251)

83%

(5)

93%

(650)

71%

(12)

<0.00001

Age

72(±

11.7)

72(±

7.9)

72(±

9.1)

63(±

15)

71(±

10.6)

57(±

11.4)

67(±

13.7)

68(±

11.2)

63(±

12.3)

66(±

12.3)

59(±

12.5)

<0.00001

race

(Cau

casian

)100%

(654

)100%

(5)

100%

(309)

65%

(20)

100%

(276)

95%

(18)

100%

(191)

100%

(306)

100%

(6)

100%

(702)

12%

(2)

<0.00001

Smok

ing

<0.00001

Past

37%

(239)

40%

(2)

62%

(192)

45%

(14)

57%

(157)

47%

(9)

46%

(88)

50%

(152)

33%

(2)

51%

(356)

53%

(9)

Currently

8%

(54)

40%

(2)

18%

(56)

19%

(6)

16%

(45)

32%

(6)

18%

(35)

14%

(44)

17%

(1)

14%

(100)

24%

(4)

Alcoh

oluse

17%

(113)

60%

(3)

31%

(96)

35%

(11)

28%

(77)

58%

(11)

40%

(76)

31%

(96)

0%

(0)

30%

(212)

29%

(5)

<0.00001

BMI

28(±

5.8)

25(±

5.3)

27(±

5.5)

26(±

4.3)

28(±

5.3)

28(±

5.1)

27(±

4.5)

28(±

5.8)

25(±

5.9)

28(±

5.3)

27(±

8.3)

0.95

Heart

rate

82(±

20.6)

105(±

33.2)

79(±

18.7)

86(±

17.7)

78(±

18.4)

91(±

24.6)

88(±

23.4)

81(±

18.6)

78(±

10.4)

76(±

17.1)

83(±

16.1)

0.0002

NYHA

class

<0.00001

I2%

(10)

0%

(0)

0%

(1)

0%

(0)

1%

(3)

0%

(0)

1%

(2)

1%

(4)

0%

(0)

5%

(35)

7%

(1)

II31

%(195)

40%

(2)

29%

(85)

14%

(4)

29%

(77)

22%

(4)

23%

(42)

18%

(54)

33%

(2)

58%

(398)

33%

(5)

III

53%

(336)

60%

(3)

54%

(159)

54%

(15)

55%

(148)

56%

(10)

59%

(108)

66%

(196)

50%

(3)

35%

(242)

53%

(8)

IV15

%(96)

0%

(0)

17%

(49)

32%

(9)

15%

(41)

22%

(4)

17%

(31)

15%

(45)

17%

(1)

2%

(17)

7%

(1)

LVEF

33(±

11.3)

24(±

8)31

(±10.9)

27(±

12)

32(±

10.8)

25(±

12.6)

29(±

11.3)

29(±

10.2)

27(±

12.6)

30(±

9)28

(±7)

<0.00001

HFho

spitalizationin

year

before

inclusion

34%

(220)

40%

(2)

30%

(94)

32%

(10)

37%

(101)

5%

(1)

17%

(33)

41%

(124)

33%

(2)

29%

(202)

29%

(5)

0.00001

Ischem

icHF

50%

(327)

40%

(2)

57%

(176)

45%

(14)

72%

(200)

26%

(5)

44%

(84)

52%

(159)

33%

(2)

55%

(383)

35%

(6)

<0.00001

AF

45%

(293)

80%

(4)

50%

(153)

39%

(12)

50%

(139)

37%

(7)

47%

(90)

53%

(161)

50%

(3)

40%

(278)

18%

(3)

0.0009

DM

44%

(286)

20%

(1)

33%

(102)

42%

(13)

51%

(140)

16%

(3)

1%

(2)

36%

(109)

0%

(0)

23%

(159)

24%

(4)

<0.00001

COPD

0%

(0)

0%

(0)

99%

(307)

13%

(4)

20%

(56)

11%

(2)

1%

(1)

21%

(64)

17%

(1)

0%

(0)

6%

(1)

<0.00001

Peripheralartery

disease

0%

(0)

0%

(0)

0%

(0)

0%

(0)

99%

(272)

5%

(1)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

<0.00001

Pulmon

arycong

estion

<0.00001

Sing

leba

se20

%(126)

0%

(0)

11%

(34)

16%

(5)

13%

(34)

0%

(0)

21%

(40)

15%

(44)

17%

(1)

3%

(23)

24%

(4)

Bi-ba

silar

53%

(331)

60%

(3)

43%

(131)

48%

(15)

48%

(129)

58%

(11)

75%

(141)

53%

(162)

50%

(3)

7%

(46)

47%

(8)

Peripheraledem

a52

%(343)

60%

(3)

55%

(169)

74%

(23)

56%

(154)

68%

(13)

55%

(106)

69%

(210)

83%

(5)

32%

(224)

35%

(6)

<0.00001

Rales

1 ⁄3lung

fields

16%

(75)

33%

(1)

22%

(36)

30%

(6)

22%

(36)

9%

(1)

17%

(30)

18%

(37)

25%

(1)

30%

(21)

33%

(4)

0.15

ElevatedJV

P28

%(116)

20%

(1)

28%

(60)

52%

(12)

41%

(82)

36%

(5)

40%

(50)

62%

(158)

50%

(3)

13%

(63)

36%

(4)

<0.00001

Hepatom

egaly

0%

(0)

0%

(0)

0%

(0)

35%

(11)

12%

(34)

5%

(1)

1%

(2)

100%

(306)

67%

(4)

0%

(0)

0%

(0)

<0.00001

Hyp

ertension

70%

(459)

40%

(2)

60%

(185)

45%

(14)

77%

(213)

47%

(9)

35%

(67)

62%

(189)

33%

(2)

59%

(416)

76%

(13)

<0.00001

SBP

129

110

123

113

126

120

121

120

107

125

120

(mm

Hg)

(±24.1)

(±20.8)

(±20.4)

(±16.1)

(±24.4)

(±19.2)

(±24.4)

(±19.4)

(±10.8)

(±19.2)

(±17.3)

0.0002

Hem

oglobin(g

/dL)

13(±

1.8)

13(±

2.6)

13(±

1.8)

13(±

2)13

(±1.8)

13(±

1.6)

14(±

2.1)

13(±

1.9)

13(±

1.5)

14(±

1.9)

14(±

1.5)

<0.00001

Sodium

(mm

ol/L)

139(±

4.3)

133(±

9)139(±

3.8)

137(±

5)139(±

3.8)

137(±

4.2)

139(±

4.1)

139(±

4.1)

135(±

3.3)

140(±

3.5)

140(±

2.2)

0.19

eGFR

(MDRD

for-

mula)

7645

6861

6359

6766

7373

750.16

(mL

/m

in/

1.73

m2)

(±34.7)

(±22.7)

(±28.4)

(±27.3)

(±26.3)

(±28.7)

(±23.7)

(±27.3)

(±12.2)

(±27.9)

(±19.7)

0.16

Potassium

4.21

4.08

4.33

4.11

4.25

4.36

4.24

4.23

3.89

4.32

3.98

(mm

ol/L)

(±0.56)

(±0.93)

(±0.65)

(±0.46)

(±0.57)

(±0.5)

(±0.55)

(±0.61)

(±0.41)

(±0.49)

(±0.47)

0.03

Alkaline

phos-

phatase

84102

8084

94100

8587

336

8077

(µg /

L)

(66-112)

(69-138)

(65-113)

(71-104)

(77-130)

(71-188)

(67-111)

(67-122)

(94-578)

(62-117)

(71-92)

0.03

Total

bilirub

in(µ

mol

/L)

13(9-19)

36(32-36)

14(10-21)

27(15-58.1)

14(10-21)

32(20-40)

17(12-25)

18(12-26)

28(19-83)

13(10-19)

16(10-19)

<0.00001

HDL

1.17

1.14

1.14

0.87

1.07

0.96

1.04

0.98

0.60

1.12

1.05

(mm

ol/L)

(±0.39)

(±0.76)

(±0.34)

(±0.62)

(±0.42)

(±0.37)

(±0.32)

(±0.27)

(±0.07)

(±0.39)

(±0.25)

<0.00001

Album

in(g

/L)

32(±

8.6)

34(±

6.3)

32(±

8.5)

32(±

7.1)

31(±

9.7)

29(±

10)

32(±

8.6)

32(±

8.5)

31(±

2.9)

34(±

8.6)

35(±

10.8)

<0.00001

24172

23172

22553

3324

3226

36ASA

T(U

/L)

(16-35)

(127-208)

(16-35)

(69-341)

(15-31)

(234-1343)

(19-69)

(17-34)

(22-211)

(18-36)

(32-45)

<0.00001

4208

29054

4479

9846

4206

8191

5654

5734

3186

3036

2142

NT-proBNP

2585

20596

2542

6613

2449

4961

2767

2500

3040

1776

1278

(pg /

mL)

--

--

--

--

--

-

( 8186

)( 41

989

)( 86

44

)( 18

122

)( 98

05

)( 13

428

)( 90

91

)( 10

236

)( 33

33

)( 59

40

)( 37

35

)<0.00001

Use

ofbe

ta-blocker

atba

selin

e69

%(450)

80%

(4)

72%

(224)

58%

(18)

76%

(209)

68%

(13)

65%

(124)

72%

(220)

83%

(5)

85%

(600)

100%

(17)

<0.00001

Use

ofACE-inh

ibitor/

ARB

atba

selin

e57

%(374)

60%

(3)

66%

(204)

74%

(23)

59%

(163)

79%

(15)

62%

(118)

63%

(192)

67%

(4)

74%

(517)

82%

(14)

<0.00001

AF:atrial

fibrilla

tion

;ASA

T:aspa

rtateam

inotransferase;BMI:bo

dymassindex;

COPD:chronicob

structivepu

lmon

arydisease;

DM:diab

etes

mellitus;eG

FR:estimated

glom

erular

filtrationrate;

HDL:high

densitylip

oprotein-cho

lesterol;HF:heartfailu

re;JV

P:jugu

larveno

uspressure;LV

EF:left

ventricularejection

fraction

;NT-proBNP:N-terminal

proB-typ

ena

triureticpe

ptide;

NYHA

class:

New

YorkHeart

Association

class;

SBP:systolic

bloo

dpressure

239Ta

ble

S14:

Dem

ogra

phic

sof

Mcl

ust

clus

ters

(Cha

pter

6)in

the

valid

atio

nco

hort

,with

perc

enta

ges

(num

bers

),m

ean

±SD

,or

med

ian

(IQ

R),

and

%of

miss

ing

valu

es

Clu

ster

s1

23

46

89

1011

p-v

alu

eNum

berof

patients

310

127

118

4112

833

1181

Sex(m

ale)

4%

(11)

72%

(92)

100%

(1)

89%

(16)

98%

(40)

92%

(11)

100%

(8)

70%

(23)

79%

(937)

<0.00001

Age

75(±

11.1)

71(±

10.5)

5475

(±12.6)

73(±

6)73

(±12.6)

73(±

16.8)

71(±

9.2)

74(±

10.6)

0.69

Race(C

aucasian

)100%

(310)

100%

(127)

100%

(1)

100%

(18)

98%

(40)

100%

(12)

25%

(2)

100%

(33)

100%

(1175)

<0.00001

Smok

ing

<0.00001

Past

25%

(76)

73%

(91)

0%(0)

33%

(6)

24%

(10)

42%

(5)

25%

(2)

24%

(8)

34%

(404)

Currently

9%

(27)

1%

(1)

100%

(1)

11%

(2)

27%

(11)

0%(0)

0%(0)

21%

(7)

16%

(187)

Alcoh

oluse

31%

(95)

61%

(74)

0%(0)

39%

(7)

39%

(16)

25%

(3)

12%

(1)

58%

(19)

50%

(575)

<0.00001

BMI

30(±

7.7)

33(±

9.5)

2629

(±1.7)

31(±

8.4)

31(±

8.5)

35(±

18.1)

28(±

4.8)

28(±

5.3)

<0.00001

Heart

rate

74(±

17.6)

82(±

23.9)

108

74(±

25.1)

78(±

27.7)

66(±

15.1)

77(±

12.3)

88(±

23.8)

73(±

14.3)

0.0003

NYHA

class

<0.00001

I0%

(1)

3%

(4)

0%(0)

0%(0)

0%(0)

0%(0)

0%(0)

3%

(1)

1%

(11)

II41

%(127)

36%

(46)

100%

(1)

11%

(2)

12%

(5)

25%

(3)

50%

(4)

12%

(4)

44%

(518)

III

42%

(129)

46%

(59)

0%(0)

50%

(9)

88%

(36)

58%

(7)

38%

(3)

79%

(26)

42%

(499)

IV17

%(52)

14%

(18)

0%(0)

39%

(7)

0%(0)

17%

(2)

12%

(1)

6%

(2)

13%

(153)

LVEF

44(±

14.7)

42(±

13)

3042

(±15.2)

41(±

12.3)

41(±

10)

46(±

16.4)

42(±

10.5)

40(±

12.5)

<0.00001

Heart

failu

reho

spitalization

inyear

before

inclusion

35%

(109)

34%

(43)

100%

(1)

72%

(13)

29%

(12)

42%

(5)

12%

(1)

33%

(11)

38%

(449)

0.04039

Ischem

icetiology

53%

(165)

43%

(55)

0%(0)

39%

(7)

46%

(19)

50%

(6)

38%

(3)

48%

(16)

38%

(453)

0.002

AF

44%

(135)

42%

(53)

100%

(1)

35%

(6)

38%

(15)

50%

(6)

38%

(3)

42%

(14)

45%

(524)

0.91

DM

28%

(87)

31%

(40)

100%

(1)

28%

(5)

27%

(11)

42%

(5)

38%

(3)

34%

(11)

34%

(396)

0.55

COPD

2%

(5)

25%

(32)

100%

(1)

11%

(2)

22%

(9)

27%

(3)

25%

(2)

15%

(5)

22%

(258)

<0.00001

Peripheralartery

disease

0%(0)

19%

(23)

0%(0)

28%

(5)

31%

(12)

8%

(1)

25%

(2)

30%

(10)

27%

(316)

<0.00001

Pulmon

arycong

estion

0.05

Sing

leba

se4%

(11)

8%

(10)

0%(0)

6%

(1)

0%(0)

8%

(1)

0%(0)

3%

(1)

6%

(71)

Bi-ba

silar

36%

(105)

39%

(47)

100%

(1)

67%

(12)

39%

(16)

42%

(5)

43%

(3)

66%

(21)

38%

(429)

Peripheraledem

a63

%(174)

70%

(78)

100%

(1)

100%

(18)

67%

(24)

50%

(6)

50%

(4)

79%

(23)

60%

(625)

<0.00001

Rales

1 ⁄3lung

fields

2%

(6)

6%

(7)

0%(0)

0%(0)

0%(0)

17%

(2)

12%

(1)

27%

(9)

2%

(25)

<0.00001

ElevatedJV

P26

%(81)

35%

(44)

100%

(1)

61%

(11)

20%

(8)

25%

(3)

25%

(2)

45%

(15)

24%

(284)

0.02

Hepatom

egaly

0%(0)

8%

(8)

0%(0)

27%

(4)

0%(0)

8%

(1)

17%

(1)

0%(0)

4%

(46)

<0.00001

Hyp

ertension

63%

(195)

42%

(53)

100%

(1)

61%

(11)

72%

(29)

64%

(7)

50%

(4)

73%

(24)

58%

(678)

0.002

SBP

(mm

Hg)

128(±

24.3)

132(±

25.8)

127

130(±

29.2)

134(±

25.5)

117(±

7.1)

134(±

16.1)

125(±

19.8)

124(±

21.6)

0.0002

Hem

oglobin(g

/dL)

16(±

21.1)

14(±

10.9)

1012

(±1.5)

20(±

31)

13(±

1.4)

12(±

2.1)

12(±

2.3)

15(±

13.3)

0.12

Sodium

(mm

ol/L)

139(±

3.6)

138(±

3.9)

127

138(±

3.8)

137(±

19.9)

140(±

3.4)

140(±

4.8)

138(±

1.9)

139(±

3.4)

0.84

eGFR

(MDRD

form

ula)

(mL

/m

in/

1.73

m2)

91(±

87.2)

121(±

211.2)

6657

(±24.4)

57(±

30.5)

84(±

38.7)

75(±

23.8)

135(±

233.8)

68(±

25.4)

<0.00001

Potassium

(mm

ol/L)

4.23

(±0.51)

4.47

(±3.57)

506

3.99

(±0.4)

4.42

(±0.48)

4.37

(±0.58)

4.06

(±0.57)

4.09

(±0.41)

4.37

(±1.69)

0.25

Alkalineph

osph

atase(µ

g /L)

88(72-111)

90(68.5-135)

265

107(90-152.5)

90(70-116)

96(76.5-160.75)

89(80.2-113.5)

102(80-12

1)89

(72-116)

0.17

Total

bilirub

in(µ

mol

/L)

9(6-12)

11(8-19)

614

(10.2-27)

10(7-13)

9(6.8-18.75)

10(6.5-12.25)

11(7-19)

11(7-15)

<0.00001

HDL(m

mol

/L)

1.32

(±0.58)

1.1(±

0.4)

3.9(±

NA)

1(±

0.53)

1.24

(±1.15)

1.01

(±0.22)

1.02

(±0.18)

1.13

(±0.46)

1.17

(±0.44)

<0.00001

Album

in(g

/L)

38(±

6.2)

34(±

6.9)

2435

(±6.2)

38(±

7.7)

39(±

7.4)

36(±

8.5)

34(±

8.6)

38(±

5.6)

<0.00001

ASA

T(U

/L)

23(18-30)

24(17-33)

1425

(20-32)

24(18-28)

23(20.5-41)

32(18.5-42)

21(17-28)

23(18-31)

0.40

1164

1446

5026

7103

1772

978

4741

3038

1357

NT-proBNP

430

458

5026

5968

572

386

923

980

532

(pg /

mL)

--

--

--

--

( 2857

)( 50

82

)( 50

26

)( 14

266

)( 15

599

)( 37

76

)( 57

43

)( 13

596

)( 32

64

)<0.00001

Use

ofbe

ta-blocker

atba

selin

e68

%(211)

74%

(94)

100%

(1)

61%

(11)

71%

(29)

33%

(4)

88%

(7)

64%

(21)

70%

(831)

0.14

Use

ofACE-inh

ibitor/A

RB

atba

selin

e70

%(216)

65%

(82)

100%

(1)

67%

(12)

56%

(23)

67%

(8)

50%

(4)

58%

(19)

70%

(831)

0.31

AF:atrial

fibrilla

tion

;ASA

T:aspa

rtateam

inotransferase;BMI:bo

dymassindex;

COPD:chronicob

structivepu

lmon

arydisease;

DM:diab

etes

mellitus;eG

FR:estimated

glom

erular

filtrationrate;

HDL:high

densitylip

oprotein-cho

lesterol;HF:heartfailu

re;JV

P:jugu

larveno

uspressure;LV

EF:left

ventricularejection

fraction

;NT-proBNP:N-terminal

proB-typ

ena

triureticpe

ptide;

NYHA

class:

New

YorkHeart

Association

class;

SBP:systolic

bloo

dpressure

240 Supplementary data

Table S15: poLCA demographics (Chapter 6) in the index cohort with percentages (numbers),mean ± SD, or median (IQR), and % of missing values

Clusters 1 2 3 4 p-valueNumber of patients 675 811 440 590Sex (male) 89 % (603) 79 % (641) 20 % (88) 87 % (514) <0.00001Age 74 (±8.6) 68 (±11) 77 (±9.2) 58 (±10) <0.00001Race (caucasian) 100 % (672) 100 % (808) 100 % (438) 97 % (571) 0.00003Smoking <0.00001

Past 63 % (427) 51 % (417) 23 % (102) 46 % (274)Smoking (currently) 6 % (43) 12 % (97) 6 % (28) 31 % (185)Alcohol use 29 % (196) 26 % (207) 14 % (63) 40 % (234) <0.00001BMI 28 (±5.2) 28 (±5.1) 27 (±5.4) 28 (±6.2) 0.98Heart rate 78 (±16.9) 73 (±14) 83 (±20.2) 90 (±22.9) <0.00001NYHA class <0.00001

I 0 % (3) 5 % (36) 1 % (4) 2 % (13)II 12 % (79) 68 % (546) 25 % (104) 25 % (139)III 66 % (435) 27 % (214) 61 % (258) 57 % (321)IV 22 % (142) 0 % (3) 13 % (57) 16 % (92)

LVEF 31 (±10.4) 31 (±8.4) 39 (±12.2) 25 (±8.4) <0.00001HF hospitalizationin year before inclusion 48 % (322) 33 % (264) 21 % (93) 19 % (115) <0.00001Ischemic etiology 73 % (496) 58 % (474) 35 % (155) 39 % (233) <0.00001AF 61 % (415) 39 % (313) 51 % (223) 33 % (192) <0.00001DM 50 % (335) 28 % (227) 33 % (146) 19 % (111) <0.00001COPD 25 % (169) 14 % (115) 13 % (57) 16 % (95) <0.00001Peripheral artery disease 18 % (121) 8 % (66) 9 % (38) 8 % (48) <0.00001Pulmonary congestion <0.00001

Single base 16 % (108) 3 % (20) 18 % (76) 19 % (107)Bi-basilar 61 % (406) 2 % (17) 59 % (257) 52 % (300)

Peripheral edema 71 % (476) 22 % (182) 62 % (274) 55 % (324) <0.00001Rales 1⁄3 lung fields 22 % (111) 36 % (14) 20 % (65) 14 % (58) 0.001Elevated JVP 51 % (255) 9 % (48) 35 % (96) 37 % (155) <0.00001Hepatomegaly 29 % (198) 3 % (22) 7 % (32) 18 % (106) <0.00001Hypertension 71 % (477) 64 % (519) 74 % (327) 42 % (246) <0.00001SBP (mmHg) 121 (±19.7) 126 (±19.4) 133 (±24.5) 121 (±23.4) 0.25Hemoglobin (g/dL) 12 (±1.9) 14 (±1.7) 12 (±1.5) 14 (±1.5) <0.00001Sodium (mmol/L) 138 (±4.8) 140 (±3.1) 140 (±4.3) 139 (±3.5) 0.04EGFR (MDRD formula)(mL/ min /1.73 m2) 48 (±18.2) 74 (±27.7) 82 (±36.2) 82 (±23) <0.00001

Potassium (mmol/L) 4.32 (±0.61) 4.39 (±0.55) 4.04 (±0.48) 4.19 (±0.52) <0.00001Alkaline phosphatase(µg/L) 91 (67-122.5) 79 (62-112) 86 (70.1-118.75) 82 (66-112) 0.003Total bilirubin (µmol/L) 16 (10.4-23.32) 12 (8.7-16.07) 13 (9-19.2) 17 (12-27.6025) <0.00001HDL-cholesterol (mmol/L) 0.97 (±0.33) 1.19 (±0.38) 1.28 (±0.39) 1 (±0.35) <0.00001Albumin (g/L) 29 (±9.1) 35 (±8.5) 30 (±8.4) 34 (±7.7) <0.00001ASAT (U/L) 22 (15-30.45) 23 (17-33) 22 (15-33) 36 (25-58.5) <0.00001NT-proBNP (pg/mL) 7150 (3529-13259) 2682 (1389-4455) 4678 (2621-8391) 4347 (2364-8000) <0.00001Use of beta-blockerat baseline 71 % (481) 83 % (673) 66 % (291) 74 % (439) <0.00001Use of ACE-inhibitor/ARB at baseline 56 % (376) 74 % (598) 54 % (237) 71 % (416) <0.00001

AF: atrial fibrillation; ASAT: aspartate aminotransferase; BMI: body mass index;COPD: chronic obstructive pulmonary disease; DM: diabetes mellitus; eGFR: estimated glomerular filtration rate;HDL: high density lipoprotein-cholesterol; HF: heart failure; JVP: jugular venous pressure;LVEF: left ventricular ejection fraction; NT-proBNP: N-terminal pro B-type natriuretic peptide;NYHA class: New York Heart Association class; SBP: systolic blood pressure

241

Table S16: Demographics of poLCA clusters (Chapter 6) in the validation cohort, with per-centages (numbers), mean ± SD, or median (IQR), and % of missing values

Clusters 1 2 3 4 p-valueNumber of patients 181 1079 268 203Sex (male) 90 % (163) 71 % (768) 25 % (66) 70 % (142) <0.00001Age 80 (±7.4) 71 (±11.1) 80 (±7.4) 76 (±8.6) 0.00004Race (Caucasian) 99 % (179) 100 % (1072) 100 % (267) 99 % (200) 0.27Smoking

Past 42 % (76) 37 % (394) 24 % (64) 34 % (68) <0.00001Currently 8 % (15) 15 % (163) 7 % (19) 19 % (39)

Alcohol use 47 % (82) 50 % (532) 30 % (77) 49 % (99) <0.00001BMI 27 (±5.4) 29 (±6.3) 29 (±7) 29 (±6.9) 0.58Heart rate 74 (±15.3) 72 (±15.9) 75 (±17) 82 (±20) <0.00001NYHA class

I 1 % (1) 1 % (15) 0% (0) 0% (1) <0.00001II 11 % (20) 55 % (592) 21 % (56) 21 % (42)III 55 % (100) 38 % (406) 55 % (147) 57 % (115)IV 33 % (60) 6 % (65) 24 % (65) 22 % (45)

LVEF 42 (±13.3) 39 (±12.6) 48 (±12) 42 (±13.2) 0.00009HF hospitalization inyear before inclusion 63 % (114) 30 % (328) 43 % (116) 42 % (86) <0.00001Ischemic etiology 46 % (83) 43 % (467) 41 % (110) 32 % (64) 0.011AF 54 % (97) 40 % (424) 48 % (127) 54 % (109) 0.00001DM 43 % (78) 31 % (338) 30 % (81) 31 % (62) 0.01COPD 26 % (45) 16 % (176) 21 % (55) 20 % (41) 0.02Peripheral artery disease 28 % (49) 20 % (216) 22 % (56) 24 % (48) 0.14Pulmonary congestion

Single base 9 % (15) 5 % (52) 8 % (19) 5 % (9) <0.00001Bi-basilar 70 % (124) 25 % (251) 52 % (132) 66 % (132)

Peripheral edema 87 % (146) 48 % (453) 79 % (194) 86 % (160) <0.00001Rales 1⁄3 lung fields 4 % (8) 3 % (28) 4 % (10) 2 % (4) 0.37JVP 43 % (77) 18 % (195) 29 % (77) 49 % (100) <0.00001Hepatomegaly 9 % (15) 3 % (28) 3 % (8) 5 % (9) 0.002Hypertension 62 % (111) 54 % (580) 76 % (202) 54 % (109) <0.00001SBP (mmHg) 119 (±22.2) 127 (±22.2) 130 (±22.8) 123 (±23.3) 0.10Hemoglobin (g/dL) 12 (±2) 16 (±18.8) 13 (±6.6) 13 (±2) 0.07Sodium (mmol/L) 138 (±3.9) 139 (±5.1) 139 (±3.8) 138 (±3.5) 0.96eGFR (MDRD formula)(mL/ min /1.73 m2) 50 (±19.8) 82 (±98.3) 78 (±32) 74 (±28) 0.14

Potassium (mmol/L) 4.25 (±0.54) 4.94 (±15.47) 4.12 (±0.48) 4.08 (±0.47 0.47Alkaline phosphatase (µg/L) 113 (82-156.5) 85 (69-109) 91 (73.2-115) 101 (82.5-138.5) <0.00001Total bilirubin (µmol/L) 13 (9-20) 10 (7-13) 9 (7-14) 14 (9-21) <0.00001HDL (mmol/L) 0.99 (±0.35) 1.19 (±0.43) 1.33 (±0.45) 1.23 (±0.84) <0.00001Albumin (g/L) 34 (±5.9) 39 (±5.8) 37 (±6) 36 (±5.9) <0.00001ASAT (U/L) 28 (22-43) 22 (16-28) 25 (21-32.5) 28 (23-40) <0.00001NT-proBNP (pg/mL) 5402 (2552-10535) 952 (362-2305) 1916 (717-4627) 2239 (1218-5455) <0.00001Use of beta-blocker at base-line

67 % (121) 74 % (795) 59 % (159) 66 % (134) 0.00003

Use of ACE-inhibitor/ARBat baseline 54 % (97) 76 % (819) 57 % (154) 62 % (126) <0.00001

AF: atrial fibrillation; ASAT: aspartate aminotransferase; BMI: body mass index;COPD: chronic obstructive pulmonary disease; DM: diabetes mellitus; eGFR: estimated glomerular filtration rate;HDL: high density lipoprotein-cholesterol; HF: heart failure; JVP: jugular venous pressure;LVEF: left ventricular ejection fraction; NT-proBNP: N-terminal pro B-type natriuretic peptide;NYHA class: New York Heart Association class; SBP: systolic blood pressure

242 Supplementary dataTa

ble

S17:

Dem

ogra

phic

sof

first

10PA

Mcl

uste

rs(C

hapt

er6)

inth

ein

dex

coho

rt,w

ithpe

rcen

tage

s(n

umbe

rs),

mea

n±

SD,o

rm

edia

n(I

QR

),an

d%

ofm

issin

gva

lues

Clu

ster

s1

23

45

67

89

10p

-val

ue

Num

berof

patients

160

104

29157

82168

276

161

76483

Sex(m

ale)

87%

(139)

63%

(66)

72%

(21)

83%

(131)

55%

(45)

71%

(119)

71%

(195)

88%

(142)

82%

(62)

79%

(382)

<0.00001

Age

72(±

10.8)

68(±

12.9)

64(±

13.6)

65(±

11.1)

67(±

11.8)

70(±

10.6)

68(±

12.2)

64(±

13.1)

57(±

11.5)

71(±

10.5)

0.0002

Race(C

aucasian

)99

%(159)

97%

(101)

100%

(29)

98%

(154)

99%

(81)

99%

(166)

99%

(273)

99%

(160)

100%

(76)

99%

(479)

0.37

Smok

ing

<0.00001

Past

59%

(94)

39%

(41)

34%

(10)

50%

(78)

43%

(35)

45%

(76)

44%

(122)

50%

(81)

51%

(39)

60%

(289)

Currently

9%

(15)

16%

(17)

21%

(6)

20%

(32)

11%

(9)

11%

(18)

13%

(37)

20%

(33)

28%

(21)

10%

(49)

Alcoh

oluse

26%

(42)

25%

(26)

38%

(11)

31%

(48)

13%

(11)

22%

(37)

32%

(88)

39%

(62)

42%

(32)

28%

(137)

0.0001

BMI

27(±

4.4)

27(±

5)26

(±4.6)

28(±

4.4)

28(±

4.8)

28(±

5.5)

26(±

4.5)

29(±

5.6)

30(±

5.4)

29(±

5.2)

0.002

Heart

rate

75(±

15.8)

80(±

19.2)

84(±

22.4)

80(±

23.1)

77(±

17.2)

77(±

16.4)

76(±

16.7)

81(±

22)

80(±

20.5)

76(±

15.1)

<0.00001

NYHA

class

<0.00001

I0%

(0)

55%

(56)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

II18

%(28)

7%

(7)

14%

(4)

75%

(114)

88%

(71)

77%

(124)

95%

(256)

57%

(89)

60%

(43)

9%

(45)

III

75%

(118)

29%

(29)

68%

(19)

25%

(39)

12%

(10)

23%

(38)

5%

(13)

43%

(67)

40%

(29)

90%

(430)

IV7%

(11)

9%

(9)

18%

(5)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

1%

(1)

0%

(0)

0%

(1)

LVEF

32(±

9.9)

34(±

11.5)

26(±

12.3)

31(±

10.8)

30(±

7.3)

33(±

9.2)

30(±

8.7)

29(±

8.5)

29(±

8.5)

30(±

9.2)

0.03

HFho

spitalization

inyear

before

inclusion

45%

(72)

19%

(20)

34%

(10)

19%

(30)

22%

(18)

31%

(52)

24%

(67)

25%

(41)

41%

(31)

39%

(188)

<0.00001

Ischem

icetiology

84%

(135)

33%

(34)

17%

(5)

64%

(101)

37%

(30)

48%

(80)

42%

(115)

31%

(50)

43%

(33)

92%

(445)

<0.00001

AF

49%

(78)

36%

(37)

52%

(15)

34%

(54)

38%

(31)

43%

(72)

40%

(111)

43%

(69)

22%

(17)

48%

(230)

<0.00001

DM

55%

(88)

35%

(36)

21%

(6)

21%

(33)

16%

(13)

29%

(48)

9%

(25)

14%

(22)

22%

(17)

50%

(242)

<0.00001

COPD

19%

(30)

11%

(11)

14%

(4)

7%

(11)

6%

(5)

20%

(34)

9%

(24)

19%

(31)

9%

(7)

19%

(92)

<0.00001

Peripheralartery

Ddisease

50%

(80)

6%

(6)

3%

(1)

15%

(23)

4%

(3)

1%

(1)

3%

(7)

1%

(2)

4%

(3)

15%

(73)

<0.00001

Pulmon

arycong

estion

<0.00001

Sing

leba

se21

%(32)

10%

(10)

7%

(2)

9%

(14)

6%

(5)

7%

(11)

11%

(28)

5%

(8)

3%

(2)

14%

(65)

Bi-ba

silar

48%

(74)

35%

(36)

59%

(17)

20%

(30)

26%

(21)

13%

(22)

24%

(62)

17%

(26)

22%

(16)

46%

(216)

Peripheraledem

a68

%(108)

41%

(43)

66%

(19)

32%

(50)

29%

(24)

27%

(45)

26%

(72)

34%

(54)

36%

(27)

55%

(267)

<0.00001

Rales

1 ⁄3lung

fields

22%

(23)

27%

(12)

21%

(4)

9%

(4)

12%

(3)

24%

(8)

13%

(12)

17%

(6)

11%

(2)

18%

(50)

0.03

JVP

42%

(50)

35%

(22)

37%

(7)

20%

(22)

4%

(2)

10%

(11)

18%

(33)

21%

(26)

13%

(7)

32%

(110)

<0.00001

Hepatom

egaly

25%

(40)

8%

(8)

17%

(5)

6%

(9)

2%

(2)

2%

(4)

4%

(11)

7%

(11)

11%

(8)

13%

(64)

<0.00001

Hyp

ertension

74%

(118)

60%

(62)

55%

(16)

66%

(104)

67%

(55)

71%

(120)

50%

(137)

53%

(86)

61%

(46)

71%

(344)

<0.00001

SBP

(mm

Hg)

122(±

19.1)

129(±

24.5)

123(±

25.1)

126(±

21.2)

130(±

20.6)

129(±

20.2)

121(±

18.2)

130(±

22.5)

123(±

18.9)

122(±

19.4)

0.23

Hem

oglobin(g

/dL)

12(±

1.9)

13(±

1.9)

13(±

2.1)

14(±

1.8)

14(±

1.5)

13(±

1.8)

13(±

1.6)

14(±

1.5)

14(±

1.9)

13(±

1.9)

0.70

Sodium

(mm

ol/L)

138(±

5.6)

139(±

4.2)

138(±

5.8)

139(±

3.6)

140(±

3.4)

140(±

3.2)

140(±

3.1)

140(±

3)139(±

3.3)

139(±

4)0.52

eGFR

(MDRD

form

ula)

(mL

/m

in/

1.73

m2)

46(±

20.4)

80(±

50.7)

50(±

27.6)

78(±

27.4)

88(±

29.3)

76(±

28.6)

79(±

28.3)

74(±

25.2)

90(±

26.5)

65(±

24.1)

0.06

Potassium

(mm

ol/L)

4.44

(±0.73)

4.25

(±0.52)

4.47

(±0.49)

4.33

(±0.5)

4.25

(±0.55)

4.38

(±0.55)

4.31

(±0.48)

4.45

(±0.59)

4.28

(±0.45)

4.27

(±0.54)

<0.00001

104

7997

8479

7682

7674

83Alkalineph

osph

atase(µ

g /L)

(82-142)

(64-126)

(71-142)

(64-108)

(63-130)

(62-111)

(66-109)

(59-108)

(62-116)

(67-111)

0.0003

Total

bilirub

in(µ

mol

/L)

15(10-22)

13(10-21)

32(17-50)

14(10-19)

11(9-17)

13(9-17)

12(9-18)

12(10-19)

14(10-18)

14(10-20)

<0.00001

HDL(m

mol

/L)

0.98

(±0.32)

1.27

(±0.67)

0.83

(±0.39)

1.14

(±0.37)

1.26

(±0.33)

1.15

(±0.36)

1.27

(±0.39)

1.03

(±0.27)

0.99

(±0.25)

1.05

(±0.35)

<0.00001

Album

in(g

/L)

29(±

9.2)

33(±

8.4)

29(±

9.2)

35(±

8.3)

35(±

9)34

(±8.6)

34(±

8.9)

34(±

8.1)

35(±

7.9)

33(±

8.2)

<0.00001

2323

497

3024

2225

2833

23ASA

T(U

/L)

(16-32)

(17-32)

(24-1336)

(22-41)

(16-35)

(15-34)

(17-42)

(20-44)

(24-46)

(16-34)

7408

4820

35000

3661

3198

3181

3136

2874

3448

3975

NT-proBNP

3092

2451

8384

2240

2494

1836

1620

1247

1744

2439

(pg /

mL)

--

--

--

--

--

( 16214)

( 7542

)( 59

882)

( 5670

)( 54

24

)( 53

38

)( 57

85

)( 57

18

)( 51

56

)( 78

37

)<0.00001

Use

ofbe

ta-blocker

atba

selin

e74

%(119)

77%

(80)

62%

(18)

85%

(134)

88%

(72)

74%

(124)

78%

(216)

78%

(125)

88%

(67)

77%

(371)

<0.00001

Use

ofACE-inh

ibitor/A

RB

atba

selin

e51

%(81)

63%

(66)

62%

(18)

73%

(115)

84%

(69)

65%

(109)

66%

(181)

77%

(124)

76%

(58)

65%

(313)

<0.00001

AF:atrial

fibrilla

tion

;ASA

T:aspa

rtateam

inotransferase;BMI:bo

dymassindex;

COPD:chronicob

structivepu

lmon

arydisease;

DM:diab

etes

mellitus;

eGFR:estimated

glom

erular

filtrationrate;HDL:high

densitylip

oprotein-cho

lesterol;HF:heartfailu

re;JV

P:jugu

larveno

uspressure;LV

EF:left

ventricularejection

fraction

;NT-proBNP:N-terminal

proB-typ

ena

triureticpe

ptide;

NYHA

class:

New

YorkHeart

Association

class;

SBP:systolic

bloo

dpressure

243Ta

ble

S18:

Dem

ogra

phic

sofs

econ

d10

PAM

clus

ters

(Cha

pter

6)in

the

inde

xco

hort

,with

perc

enta

ges(

num

bers

),m

ean

±SD

,orm

edia

n(I

QR

),an

d%

ofm

issin

gva

lues

1112

1314

1516

1718

1920

p-v

alu

eNum

berof

patients

103

52107

9471

95141

6773

17Sex(m

ale)

81%

(83)

77%

(40)

77%

(82)

72%

(68)

63%

(45)

81%

(77)

55%

(77)

27%

(18)

60%

(44)

59%

(10)

<0.00001

Age

73(±

9.4)

73(±

8.9)

73(±

11.1)

72(±

10.9)

68(±

13.1)

64(±

13.8)

70(±

12)

73(±

11.7)

73(±

9.9)

69(±

13.6)

0.0002

Race(C

aucasian

)100%

(103)

98%

(51)

98%

(105)

97%

(91)

99%

(70)

98%

(93)

100%

(141)

100%

(67)

100%

(73)

100%

(17)

0.37

Smok

ing

<0.00001

Past

45%

(46)

42%

(22)

54%

(58)

44%

(41)

51%

(36)

42%

(40)

38%

(54)

48%

(32)

27%

(20)

35%

(6)

Currently

6%

(6)

10%

(5)

15%

(16)

12%

(11)

11%

(8)

22%

(21)

23%

(32)

12%

(8)

11%

(8)

6%

(1)

Alcoh

oluse

27%

(28)

27%

(14)

30%

(32)

15%

(14)

34%

(24)

31%

(29)

22%

(31)

16%

(11)

26%

(19)

24%

(4)

0.0001

BMI

27(±

4.2)

28(±

5.2)

27(±

6.8)

27(±

4.9)

28(±

5.3)

33(±

9.2)

28(±

5.1)

26(±

5)28

(±6.5)

27(±

4.1)

0.002

Heart

rate

77(±

14.2)

79(±

15.7)

80(±

18)

81(±

20)

94(±

23)

84(±

19.6)

96(±

26.7)

84(±

19.7)

85(±

21.5)

90(±

19.2)

<0.00001

NYHA

class

<0.00001

I0%

(0)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

0%

(0)

II21

%(22)

30%

(14)

8%

(8)

6%

(6)

6%

(4)

9%

(9)

5%

(6)

11%

(7)

15%

(11)

0%

(0)

III

79%

(81)

63%

(29)

38%

(38)

28%

(26)

29%

(20)

79%

(75)

33%

(43)

83%

(55)

75%

(53)

100%

(16)

IV0%

(0)

7%

(3)

54%

(54)

66%

(61)

66%

(46)

12%

(11)

62%

(81)

6%

(4)

10%

(7)

0%

(0)

LVEF

32(±

11.2)

33(±

14)

28(±

12)

30(±

10.7)

28(±

10.2)

27(±

9)33

(±13.4)

39(±

11.6)

39(±

14.5)

33(±

12.5)

0.03

HF

hospitalization

inbe

fore

inclusion

48%

(49)

54%

(28)

41%

(44)

48%

(45)

28%

(20)

19%

(18)

26%

(36)

21%

(14)

11%

(8)

18%

(3)

<0.00001

Ischem

icetiology

53%

(55)

63%

(33)

67%

(72)

60%

(56)

37%

(26)

22%

(21)

28%

(39)

21%

(14)

11%

(8)

35%

(6)

<0.00001

AF

64%

(66)

60%

(31)

52%

(56)

50%

(47)

46%

(33)

36%

(34)

57%

(80)

46%

(31)

60%

(44)

41%

(7)

<0.00001

DM

49%

(50)

48%

(25)

39%

(42)

39%

(37)

31%

(22)

27%

(26)

34%

(48)

24%

(16)

26%

(19)

24%

(4)

<0.00001

COPD

30%

(31)

27%

(14)

32%

(34)

24%

(23)

11%

(8)

7%

(7)

26%

(37)

21%

(14)

25%

(18)

6%

(1)

<0.00001

Peripheralartery

disease

2%

(2)

46%

(24)

12%

(13)

16%

(15)

10%

(7)

2%

(2)

8%

(11)

0%

(0)

0%

(0)

0%

(0)

<0.00001

Pulmon

arycong

estion

<0.00001

Sing

leba

se17

%(17)

12%

(6)

15%

(16)

18%

(17)

16%

(11)

22%

(21)

12%

(17)

22%

(14)

14%

(10)

29%

(5)

Bi-ba

silar

47%

(47)

49%

(24)

62%

(65)

70%

(65)

51%

(36)

52%

(49)

69%

(97)

43%

(28)

56%

(40)

53%

(9)

Peripheraledem

a75

%(77)

56%

(29)

71%

(76)

68%

(64)

61%

(43)

72%

(68)

64%

(90)

61%

(41)

64%

(47)

71%

(12)

<0.00001

Rales

1 ⁄3lung

fields

9%

(6)

17%

(5)

29%

(23)

24%

(20)

32%

(15)

14%

(10)

25%

(28)

24%

(10)

10%

(5)

14%

(2)

0.03

JVP

56%

(42)

48%

(16)

59%

(46)

61%

(39)

49%

(22)

36%

(24)

44%

(43)

33%

(16)

27%

(15)

8%

(1)

<0.00001

Hepatom

egaly

65%

(66)

29%

(15)

32%

(34)

34%

(32)

6%

(4)

20%

(19)

10%

(14)

3%

(2)

11%

(8)

12%

(2)

<0.00001

Hyp

ertension

67%

(69)

77%

(40)

56%

(60)

56%

(53)

54%

(38)

45%

(43)

54%

(76)

57%

(38)

73%

(53)

65%

(11)

<0.00001

SBP

(mm

Hg)

122(±

18.2)

125(±

25.5)

118(±

19.7)

123(±

19.7)

129(±

26.8)

120(±

17.9)

130(±

31.4)

132(±

27.4)

132(±

26.7)

133(±

23.3)

0.23

Hem

oglobin(g

/dL)

13(±

2)13

(±1.8)

12(±

2)13

(±2.1)

13(±

1.8)

14(±

1.8)

13(±

1.8)

13(±

1.5)

13(±

1.7)

14(±

2.1)

0.70

Sodium

(mm

ol/L)

139(±

3.3)

140(±

3.4)

137(±

4.9)

138(±

4)139(±

3.6)

138(±

5.3)

139(±

3.3)

140(±

3.7)

139(±

3.9)

137(±

5.4)

0.52

eGFR

(MDRD

form

ula)

(mL

/m

in/

1.73

m2)

59(±

23)

60(±

22.5)

57(±

25.6)

63(±

28.1)

80(±

27.8)

66(±

23.2)

73(±

25.5)

92(±

30.3)

75(±

33.4)

76(±

27.3)

0.06

Potassium

(mm

ol/L)

4.18

(±0.53)

4.24

(±0.55)

4.2(±

0.55)

4.04

(±0.57)

3.97

(±0.59)

4.25

(±0.66)

4.09

(±0.5)

4.06

(±0.49)

4.1(±

0.53)

4.05

(±0.73)

<0.00001

8899

9694

9878

8572

8494

Alkalineph

osph

atase(µ

g /L)

(70-121)

(67-147)

(70-121)

(80-122)

(70-144)

(60-109)

(68-120)

(61-84)

(63-98)

(76-133)

0.0003

Total

bilirub

in(µ

mol

/L)

15(10-23)

20(12-24)

17(12-26)

15(10-28)

16(12-27)

19(14-28)

14(10-24)

13(9-15)

15(9-27)

12(10-26)

<0.00001

HDL(m

mol

/L)

1.07

(±0.32)

1.15

(±0.48)

0.9(±

0.31)

1.01

(±0.4)

1(±

0.25)

0.95

(±0.35)

1.15

(±0.32)

1.33

(±0.42)

1.21

(±0.35)

1.42

(±0.7)

<0.00001

Album

in(g

/L)

31(±

9.4)

28(±

10)

28(±

9)27

(±9.9)

31(±

8.1)

34(±

6.6)

31(±

7.6)

30(±

8.2)

32(±

8.8)

35(±

8.1)

<0.00001

1922

2323

3032

2825

2420

ASA

T(U

/L)

(13-25)

(15-35)

(16-33)

(15-34)

(17-62)

(19-63)

(18-40)

(16-37)

(17-39)

(16-58)

4339

5428

10995

8500

3949

7000

4462

4292

3719

3205

NT-proBNP

2360

3077

6232

4450

2355

3900

2560

2303

2615

2098

(pg /

mL)

--

--

--

--

--

( 8489

)( 12

128)

( 21280)

( 12793)

( 6085

)( 10

781)

( 8118

)( 88

50

)( 64

80

)( 99

98

)<0.00001

Use

ofBeta-blocker

atba

selin

e59

%(61)

69%

(36)

78%

(83)

77%

(72)

61%

(43)

78%

(74)

61%

(86)

72%

(48)

58%

(42)

76%

(13)

<0.00001

Use

ofACE-inh

ibitor/A

RB

atba

selin

e56

%(58)

56%

(29)

57%

(61)

65%

(61)

54%

(38)

74%

(70)

61%

(86)

51%

(34)

60%

(44)

71%

(12)

<0.00001

AF:atrial

fibrilla

tion

;ASA

T:aspa

rtateam

inotransferase;BMI:bo

dymassindex;

COPD:chronicob

structivepu

lmon

arydisease;

DM:diab

etes

mellitus;

eGFR:estimated

glom

erular

filtrationrate;HDL:high

densitylip

oprotein-cho

lesterol;HF:heartfailu

re;JV

P:jugu

larveno

uspressure;LV

EF:left

ventricularejection

fraction

;NT-proBNP:N-terminal

proB-typ

ena

triureticpe

ptide;

NYHA

class:

New

YorkHeart

Association

class;

SBP:systolic

bloo

dpressure

244 Supplementary dataTa

ble

S19:

Dem

ogra

phic

sof

first

10PA

Mcl

uste

rs(C

hapt

er6)

inth

eva

lidat

ion

coho

rt,

with

perc

enta

ges

(num

bers

),m

ean

±SD

,or

med

ian

(IQ

R),

and

%of

miss

ing

valu

es

12

34

56

78

910

p-v

alu

eNum

berof

patients

3551

7564

5183

107

114

123

156

Sex(m

ale)

63%

(22)

55%

(28)

55%

(41)

72%

(46)

39%

(20)

59%

(49)

66%

(71)

69%

(79)

70%

(86)

67%

(105)

0.00005

Age

75(±

9.4)

75(±

9.3)

76(±

10.9)

74(±

9)76

(±9.8)

75(±

10.1)

75(±

9.4)

72(±

9.6)

71(±

10.3)

73(±

11)

0.55

Race(C

aucasian

)100%

(35)

100%

(51)

100%

(75)

100%

(64)

100%

(50)

100%

(83)

100%

(107)

100%

(114)

99%

(122)

100%

(156)

0.69

Smok

ing

0.0002

Past

44%

(15)

31%

(16)

36%

(27)

56%

(36)

33%

(17)

39%

(32)

30%

(32)

31%

(35)

33%

(40)

29%

(46)

Currently

12%

(4)

24%

(12)

15%

(11)

9%

(6)

12%

(6)

5%

(4)

19%

(20)

22%

(25)

10%

(12)

10%

(15)

Alcoh

oluse

44%

(15)

58%

(29)

74%

(55)

71%

(45)

33%

(17)

28%

(23)

46%

(49)

49%

(55)

47%

(57)

47%

(70)

<0.00001

BMI

31(±

8.8)

28(±

6.2)

28(±

6.2)

28(±

5.4)

31(±

8.6)

30(±

6.8)

30(±

6.1)

29(±

5.4)

28(±

5.4)

29(±

5.1)

0.88

Heart

rate

78(±

16.1)

87(±

23.7)

84(±

19.7)

74(±

15.1)

76(±

13.4)

76(±

17.3)

72(±

16.3)

70(±

16.4)

69(±

13.7)

70(±

16.8)

0.02

NYHA

class

<0.00001

I0

00%

(0)

0%(0)

0%(0)

0%(0)

0%(0)

0%(0)

0%(0)

3%

(4)

II20

%(7)

12%

(6)

20%

(15)

53%

(34)

37%

(19)

57%

(47)

30%

(32)

57%

(65)

80%

(98)

68%

(106)

III

57%

(20)

47%

(24)

53%

(40)

34%

(22)

43%

(22)

25%

(21)

68%

(73)

41%

(47)

15%

(18)

19%

(30)

IV23

%(8)

41%

(21)

27%

(20)

12%

(8)

20%

(10)

18%

(15)

2%

(2)

2%

(2)

6%

(7)

10%

(15)

LVEF

44(±

15.6)

44(±

13.5)

46(±

13.4)

37(±

11.6)

43(±

12.9)

43(±

13.2)

42(±

13.8)

36(±

11.5)

41(±

12.2)

41(±

13.8)

0.88

HFho

spitalizationin

before

inclusion

23%

(8)

43%

(22)

41%

(31)

25%

(16)

41%

(21)

66%

(55)

42%

(45)

34%

(39)

25%

(31)

25%

(39)

<0.00001

Ischem

icetiology

49%

(17)

43%

(22)

49%

(37)

38%

(24)

35%

(18)

43%

(36)

49%

(52)

49%

(56)

50%

(61)

43%

(67)

0.04

AF

50%

(17)

47%

(24)

45%

(33)

39%

(25)

41%

(20)

60%

(50)

43%

(46)

47%

(53)

29%

(35)

36%

(56)

0.006

DM

35%

(12)

42%

(21)

15%

(11)

19%

(12)

46%

(23)

41%

(34)

47%

(50)

25%

(28)

24%

(29)

32%

(50)

<0.00001

COPD

18%

(6)

37%

(19)

23%

(17)

31%

(20)

16%

(8)

19%

(15)

21%

(22)

19%

(21)

4%

(5)

7%

(11)

<0.00001

Peripheralartery

disease

21%

(7)

19%

(9)

19%

(14)

28%

(18)

22%

(11)

22%

(18)

30%

(31)

23%

(26)

15%

(17)

17%

(25)

0.37

Pulmon

arycong

estion

<0.00001

Sing

leba

se0%

(0)

6%

(3)

7%

(5)

6%

(4)

10%

(5)

7%

(6)

9%

(9)

7%

(8)

5%

(6)

5%

(7)

Bi-ba

silar

59%

(19)

72%

(36)

57%

(41)

35%

(22)

42%

(21)

46%

(38)

32%

(33)

23%

(25)

19%

(22)

18%

(27)

Peripheraledem

a94

%(29)

83%

(38)

70%

(48)

67%

(40)

74%

(31)

67%

(51)

78%

(77)

53%

(51)

37%

(37)

33%

(46)

<0.00001

Rales

1 ⁄3lung

fields

17%

(6)

0%(0)

1%

(1)

6%

(4)

4%

(2)

2%

(2)

3%

(3)

2%

(2)

2%

(2)

1%

(1)

<0.00001

JVP

23%

(8)

41%

(21)

27%

(20)

39%

(25)

47%

(24)

39%

(32)

20%

(21)

18%

(20)

15%

(19)

16%

(25)

<0.00001

Hepatom

egaly

3%

(1)

2%

(1)

0%(0)

0%(0)

7%

(3)

5%

(4)

1%

(1)

2%

(2)

3%

(3)

3%

(4)

<0.00001

Hyp

ertension

44%

(15)

61%

(30)

57%

(43)

47%

(30)

49%

(25)

57%

(47)

72%

(76)

56%

(64)

60%

(73)

78%

(121)

<0.00001

SBP

(mm

Hg)

121(±

23.8)

129(±

24.2)

133(±

23.4)

123(±

20.7)

117(±

18.5)

119(±

21.7)

131(±

23.7)

131(±

23)

126(±

21.1)

132(±

21.8)

0.11

Hem

oglobin(g

/dL)

16(±

22)

13(±

2.1)

17(±

23.4)

17(±

20.8)

17(±

24.5)

20(±

31.2)

18(±

25.3)

13(±

1.9)

15(±

13.9)

15(±

11.4)

0.005

Sodium

(mm

ol/L)

140(±

2.8)

138(±

4.1)

139(±

3.7)

139(±

3.3)

139(±

2.9)

139(±

3.3)

139(±

3.2)

140(±

3)139(±

3.1)

139(±

3)0.24

eGFR

(MDRD

form

ula)

285

7677

7880

6668

7676

75(m

L/

min

/1.

73m

2)

(±481.4)

(±39)

(±26.9)

(±28.5)

(±39.3)

(±35.5)

(±33.4)

(±29.3)

(±24.4)

(±26.4)

<0.00001

Potassium

(mm

ol/L)

4.16

(±0.6)

4.97

(±5.6)

4.18

(±0.5)

4.19

(±0.4)

4.17

(±0.62)

4.3(±

0.59)

4.35

(±0.49)

4.98

(±5.22)

4.34

(±0.4)

4.35

(±0.49)

0.25

8890

9592

99107

9586

8182

Alkalineph

osph

atase(µ

g /L)

(74-117)

(76-110)

(74-121)

(72-120)

(80-139)

(79-149)

(69-110)

(67-120)

(65-101)

(63-103)

0.00001

Total

bilirub

in(µ

mol

/L)

9(7-13.5)

11(7-17)

11(8-17.5)

11(7.5-16)

9(6-13.5)

11(7-15.5)

11(8-14)

10(7-13)

10(7-14)

9(7-13)

0.16

HDL(m

mol

/L)

1.16

(±0.37)

1.14

(±0.48)

1.23

(±0.4)

1.23

(±0.42)

1.43

(±1.36)

1.26

(±0.51)

1.11

(±0.41)

1.28

(±0.51)

1.24

(±0.43)

1.2(±

0.41)

0.0003

Album

in(g

/L)

35(±

7.1)

35(±

6.6)

36(±

6.2)

37(±

6.9)

37(±

5.9)

37(±

6.6)

38(±

5.8)

39(±

5.9)

40(±

4.7)

40(±

5)<0.00001

2225

2427

2423

2423

2423

ASA

T(U

/L)

(17-36)

(18-40)

(19-30)

(20-36)

(19-34)

(18-32)

(19-28)

(18-30)

(19-31)

(18-28)

2203

2393

1627

1197

1888

1513

1278

1448

1079

819

NT-proBNP

854

888

653

367

762

687

416

419

364

301

(pg /

mL)

--

--

--

--

--

( 4310

)( 71

39

)( 40

30

)( 39

32

)( 38

18

)( 32

02

)( 36

50

)( 29

54

)( 18

94

)( 19

63

)<0.00001

Use

ofbe

ta-blocker

atba

se-

line

71%

(25)

65%

(33)

60%

(45)

77%

(49)

53%

(27)

59%

(49)

74%

(79)

90%

(103)

85%

(105)

65%

(101)

<0.00001

Use

ofACE-inh

ibitor/A

RB

atba

selin

e49

%(17)

49%

(25)

67%

(50)

70%

(45)

63%

(32)

52%

(43)

80%

(86)

89%

(102)

82%

(101)

67%

(105)

<0.00001

AF:atrial

fibrilla

tion

;ASA

T:aspa

rtateam

inotransferase;BMI:bo

dymassindex;

COPD:chronicob

structivepu

lmon

arydisease;

DM:diab

etes

mellitus;

eGFR:estimated

glom

erular

filtrationrate;HDL:high

densitylip

oprotein-cho

lesterol;HF:heartfailu

re;JV

P:jugu

larveno

uspressure;LV

EF:left

ventricularejection

fraction

;NT-proBNP:N-terminal

proB-typ

ena

triureticpe

ptide;

NYHA

class:

New

YorkHeart

Association

class;

SBP:systolic

bloo

dpressure

245Ta

ble

S20:

Dem

ogra

phic

sof

seco

nd10

PAM

clus

ters

(Cha

pter

6)in

the

valid

atio

nco

hort

,with

perc

enta

ges

(num

bers

),m

ean

±SD

,or

med

ian

(IQ

R),

and

%of

miss

ing

valu

es

1112

1314

1516

1718

1920

p-v

alu

eNum

berof

patients

174

7465

8352

77112

6266

107

Sex(m

ale)

74%

(128)

82%

(61)

66%

(43)

69%

(57)

67%

(35)

60%

(46)

59%

(66)

53%

(33)

76%

(50)

68%

(73)

0.00005

Age

71(±

12)

73(±

11.8)

75(±

10.2)

75(±

10.9)

76(±

10.3)

72(±

12)

73(±

11.3)

73(±

11.9)

75(±

10.1)

76(±

9.7)

0.55

Race(C

aucasian

)97

%(168)

99%

(73)

98%

(64)

100%

(81)

98%

(51)

100%

(77)

100%

(112)

100%

(62)

100%

(66)

100%

(107)

0.69

Smok

ing

0.0002

Past

30%

(53)

41%

(30)

36%

(23)

43%

(36)

38%

(20)

38%

(29)

25%

(27)

33%

(20)

42%

(28)

38%

(40)

Currently

18%

(32)

20%

(15)

9%

(6)

22%

(18)

6%

(3)

14%

(11)

15%

(16)

11%

(7)

8%

(5)

8%

(8)

Alcoh

oluse

31%

(53)

47%

(34)

41%

(26)

52%

(43)

52%

(26)

59%

(45)

28%

(30)

29%

(17)

66%

(43)

56%

(58)

<0.00001

BMI

30(±

7)29

(±5.4)

27(±

5.1)

29(±

5.7)

28(±

6.4)

27(±

6.4)

30(±

7.7)

31(±

7.8)

29(±

6.7)

29(±

6.3)

0.88

Heart

rate

73(±

14)

75(±

14.9)

73(±

15.9)

74(±

16.8)

76(±

17.7)

74(±

15.7)

78(±

19)

70(±

15.3)

75(±

17.1)

74(±

15.6)

0.02

NYHA

class

<0.00001

I3%

(5)

3%

(2)

3%

(2)

0%(0)

0%(0)

0%(0)

0%(0)

0%(0)

3%

(2)

2%

(2)

II34

%(60)

45%

(33)

43%

(28)

33%

(27)

25%

(13)

34%

(26)

15%

(17)

23%

(14)

41%

(27)

34%

(36)

III

32%

(56)

38%

(28)

43%

(28)

51%

(42)

69%

(36)

61%

(47)

55%

(62)

77%

(48)

56%

(37)

63%

(67)

IV30

%(53)

15%

(11)

11%

(7)

17%

(14)

6%

(3)

5%

(4)

29%

(33)

0%(0)

0%(0)

2%

(2)

LVEF

40(±

11.9)

40(±

14.1)

41(±

12.4)

43(±

12.3)

42(±

9.9)

36(±

11.4)

43(±

13.4)

42(±

12.1)

46(±

13.5)

42(±

14.3)

0.88

HFho

spitalizationin

year

before

inclusion

41%

(72)

43%

(32)

38%

(25)

30%

(25)

37%

(19)

45%

(35)

42%

(47)

44%

(27)

41%

(27)

26%

(28)

<0.00001

Ischem

icetiology

37%

(64)

36%

(27)

37%

(24)

39%

(32)

37%

(19)

43%

(33)

28%

(31)

52%

(32)

50%

(33)

36%

(39)

0.04

AF

41%

(71)

44%

(32)

40%

(26)

40%

(33)

45%

(23)

57%

(44)

46%

(52)

55%

(34)

50%

(32)

48%

(51)

0.006

DM

47%

(81)

36%

(27)

40%

(26)

39%

(32)

27%

(14)

21%

(16)

27%

(30)

23%

(14)

30%

(20)

27%

(29)

<0.00001

COPD

23%

(39)

14%

(10)

18%

(12)

44%

(36)

20%

(10)

17%

(13)

20%

(22)

8%

(5)

8%

(5)

20%

(21)

<0.00001

Peripheralartery

disease

21%

(35)

16%

(12)

18%

(12)

25%

(20)

17%

(9)

30%

(22)

25%

(27)

27%

(17)

19%

(12)

26%

(27)

0.37

Pulmon

ary

cong

estion

<0.00001

Sing

leba

se5%

(8)

4%

(3)

13%

(8)

5%

(4)

4%

(2)

1%

(1)

5%

(5)

5%

(3)

2%

(1)

7%

(7)

Bi-ba

silar

26%

(43)

58%

(40)

50%

(31)

44%

(36)

40%

(20)

35%

(24)

52%

(56)

38%

(23)

40%

(25)

56%

(57)

Peripheraledem

a49

%(75)

69%

(46)

47%

(26)

61%

(46)

60%

(28)

67%

(44)

85%

(89)

72%

(39)

60%

(36)

78%

(76)

<0.00001

Rales

1 ⁄3lung

fields

0%(0)

8%

(6)

0%(0)

2%

(2)

2%

(1)

8%

(6)

2%

(2)

0%(0)

2%

(1)

8%

(9)

<0.00001

JVP

20%

(35)

38%

(28)

15%

(10)

13%

(11)

21%

(11)

31%

(24)

31%

(35)

23%

(14)

29%

(19)

44%

(47)

<0.00001

Hepatom

egaly

3%

(4)

3%

(2)

25%

(15)

5%

(4)

6%

(3)

3%

(2)

1%

(1)

7%

(4)

7%

(4)

2%

(2)

<0.00001

Hyp

ertension

58%

(101)

54%

(40)

58%

(37)

68%

(56)

37%

(19)

34%

(26)

55%

(62)

73%

(45)

67%

(44)

45%

(48)

<0.00001

SBP

(mm

Hg)

125(±

23.2)

123(±

25.6)

121(±

18.6)

126(±

23.3)

117(±

19.6)

124(±

20.9)

128(±

22.6)

133(±

25.5)

125(±

18.2)

119(±

20.9)

0.11

Hem

oglobin(g

/dL)

13(±

2.1)

15(±

12.6)

15(±

14.5)

13(±

2)13

(±1.7)

17(±

20.4)

15(±

16)

13(±

1.7)

13(±

1.9)

13(±

2.1)

0.005

Sodium

(mm

ol/L)

138(±

3.8)

137(±

15)

139(±

3.2)

139(±

4)139(±

3.6)

139(±

2.8)

139(±

3.5)

139(±

3.4)

138(±

4.1)

138(±

4.2)

0.24

eGFR

(MDRD

form

ula)

7271

6573

7374

7267

7174

(mL

/m

in/

1.73

m2)

(±35)

(±32.5)

(±25.1)

(±35.9)

(±30.5)

(±28.1)

(±27.3)

(±28)

(±32.5)

(±31.2)

<0.00001

Potassium

(mm

ol/L)

4.29

(±0.47)

4.34

(±0.53)

4.31

(±0.56)

4.28

(±0.43)

4.25

(±0.48)

4.31

(±0.44)

4.18

(±0.48)

12.52(±

64.24)

4.27

(±0.52)

4.26

(±0.48)

0.25

8992

9487

9183

8691

9091

Alkalineph

osph

atase(µ

g /L)

(71-112)

(72-124)

(79-126)

(76-124)

(80-116)

(66-111)

(74-122)

(74-120)

(68-112)

(78-120)

0.00001

Total

bilirub

in(µ

mol

/L)

10(7-14)

11(8-15)

10(8-14)

9(6-16)

11(7.5-13)

10(7-13)

11(8-16)

10(7-15)

11(8-17)

11(8-16)

0.15

HDL(m

mol

/L)

1.04

(±0.29)

1.05

(±0.32)

1.24

(±0.47)

1.24

(±0.41)

1.25

(±0.46)

1.32

(±0.7)

1.2(±

0.43)

1.14

(±0.48)

1.15

(±0.44)

1.17

(±0.52)

0.0003

Album

in(g

/L)

39(±

5.9)

36(±

6.5)

38(±

5.9)

36(±

5.5)

36(±

6)38

(±6.4)

37(±

6.8)

37(±

6.5)

37(±

5.7)

36(±

5.3)

<0.00001

2324

2222

2325

2422

2324

ASA

T(U

/L)

(18-29)

(19-31)

(17-32)

(18-28)

(18-32)

(21-34)

(17-30)

(16-30)

(18-28)

(18-33)

1093

1644

1126

1485

2067

1915

1988

1674

1508

1605

NT-proBNP

522

530

436

556

751

713

562

427

516

729

(pg /

mL)

--

--

--

--

--

( 3477

)( 34

66

)( 41

11

)( 31

56

)( 38

92

)( 46

46

)( 49

23

)( 39

08

)( 47

29

)( 48

11

)<0.00001

Use

ofbe

ta-blocker

atba

selin

e80

%(140)

69%

(51)

66%

(43)

36%

(30)

60%

(31)

70%

(54)

62%

(70)

76%

(47)

76%

(50)

72%

(77)

<0.00001

Use

ofACE-inh

ibitor

/ARB

atba

selin

e74

%(129)

61%

(45)

58%

(38)

43%

(36)

81%

(42)

75%

(58)

71%

(79)

81%

(50)

71%

(47)

62%

(66)

<0.00001

AF:atrial

fibrilla

tion

;ASA

T:aspa

rtateam

inotransferase;BMI:bo

dymassindex;

COPD:chronicob

structivepu

lmon

arydisease;

DM:diab

etes

mellitus;

eGFR:estimated

glom

erular

filtrationrate;HDL:high

densitylip

oprotein-cho

lesterol;HF:heartfailu

re;JV

P:jugu

larveno

uspressure;LV

EF:left

ventricularejection

fraction

;NT-proBNP:N-terminal

proB-typ

ena

triureticpe

ptide;

NYHA

class:

New

YorkHeart

Association

class;

SBP:systolic

bloo

dpressure

246 Supplementary data

Table S21: Demographics of Hclust clustering (Chapter 6) in the index cohort, with percent-ages (numbers), mean ± SD, or median (IQR), and % of missing values

Clusters 1 2 3 4 p-valueNumber of patients 1433 989 80 14Sex (male) 68 % (972) 82 % (810) 69 % (55) 64 % (9) <0.00001Age 68 (±12.7) 71 (±10.3) 71 (±12.5) 60 (±10) <0.00001Race (caucasian) 99 % (1422) 100 % (987) 100 % (80) 0 % (0) <0.00001Smoking <0.00001

Past 41 % (589) 60 % (589) 46 % (37) 36 % (5)Currently 15 % (222) 11 % (111) 18 % (14) 43 % (6)

Alcohol use 30 % (430) 25 % (244) 28 % (22) 29 % (4) 0.04BMI 28 (±5.9) 28 (±4.7) 25 (±4.7) 27 (±8.9) 0.0007Heart rate 83 (±21) 75 (±16) 81 (±19.1) 85 (±19.7) <0.00001NYHA class <0.00001

I 3 % (38) 2 % (17) 1 % (1) 0 % (0)II 38 % (528) 34 % (326) 13 % (10) 33 % (4)III 48 % (663) 53 % (515) 56 % (44) 50 % (6)IV 11 % (156) 12 % (113) 29 % (23) 17 % (2)

LVEF 31 (±11.3) 31 (±9.5) 30 (±9.9) 29 (±11.3) 0.10Heart failure hospitalizationin year before inclusion 27 % (383) 37 % (370) 44 % (35) 43 % (6) <0.00001Ischemic etiology 27 % (383) 93 % (922) 60 % (48) 36 % (5) <0.00001AF 47 % (675) 44 % (431) 42 % (34) 21 % (3) 0.09DM 25 % (363) 44 % (434) 21 % (17) 36 % (5) <0.00001COPD 17 % (246) 18 % (174) 18 % (14) 14 % (2) 0.98Peripheral artery disease 2 % (25) 24 % (242) 8 % (6) 0 % (0) <0.00001Pulmonary congestion 0.005

Single base 12 % (173) 13 % (125) 14 % (11) 14 % (2)Bi-basilar 39 % (550) 39 % (376) 62 % (48) 43 % (6)

Peripheral edema 50 % (723) 47 % (461) 78 % (62) 71 % (10) <0.00001Rales 1⁄3 lung fields 18 % (133) 20 % (101) 22 % (13) 12 % (1) 0.74Elevated JVP 32 % (311) 30 % (211) 47 % (29) 33 % (3) 0.002Hepatomegaly 14 % (199) 14 % (140) 24 % (19) 0 % (0) 0.04Hypertension 57 % (813) 71 % (700) 60 % (48) 57 % (8) <0.00001SBP (mmHg) 126 (±23.3) 123 (±19.6) 123 (±22.7) 121 (±15.5) 0.0004Hemoglobin (g/dL) 13 (±1.9) 13 (±1.9) 12 (±1.9) 14 (±2) <0.00001Sodium (mmol/L) 139 (±3.9) 139 (±3.9) 136 (±6.3) 140 (±3) <0.00001eGFR (MDRD formula)(mL/ min /1.73 m2) 76 (±30.5) 65 (±26) 42 (±26.1) 70 (±24.6) <0.00001

Potassium (mmol/L) 4.24 (±0.57) 4.28 (±0.54) 4.36 (±0.63) 4.11 (±0.43) 0.10Alkaline phosphatase (µg/L) 82 (64-117) 88 (67-116) 98 (71-134) 71 (67-72) 0.03Total bilirubin (µmol/L) 14 (10-21.88) 14 (9.5-20) 20 (11.8-29.19) 14 (10.1-20.19) 0.001HDL-cholesterol (mmol/L) 1.12 (±0.37) 1.08 (±0.39) 0.97 (±0.37) 1.35 (±0.79) 0.05Albumin (g/L) 33 (±8.4) 32 (±9.1) 29 (±9.9) 37 (±9.1) 0.0002ASAT (U/L) 26 (17-41.77) 23 (16-33.5) 25 (15.6-53.5) 31 (15-36) 0.001NT-proBNP 4055 3975 30975 1272(pg/mL) (2303-7391) (2327-8130) (26489-35000) (931-4199) <0.00001

Use of beta-blocker at baseline 72 % (1038) 78 % (771) 79 % (63) 86 % (12) 0.01Use of ACE-inhibitor/ARBat baseline 67 % (957) 62 % (610) 60 % (48) 86 % (12) 0.02

AF: atrial fibrillation; BMI: body mass index; COPD: chronic obstructive pulmonary disease; DM: diabetes mellitus;eGFR: estimated glomerular filtration rate; HDL: high density lipoprotein-cholesterol; JVP: jugular venous pressure;LVEF: left ventricular ejection fraction; NT-proBNP: N-terminal pro B-type natriuretic peptide;NYHA class: New York Heart Association class; SBP: systolic blood pressure

247

Table S22: Demographics of Hclust clusters (Chapter 6) in the validation cohort, with per-centages (numbers), mean ± SD, or median (IQR), and % of missing values

Clusters 1 2 3 4 p-valueNumber of patients 988 712 22 9Sex (male) 63 % (627) 69 % (489) 73 % (16) 78 % (7) 0.11Age 73 (±10.5) 74 (±10.9) 78 (±9.1) 72 (±10.8) 0.05Race (Caucasian) 100 % (985) 100 % (711) 100 % (22) 0% (0) <0.00001Smoking 0.23

Past 34 % (337) 36 % (255) 41 % (9) 11 % (1)Currently 14 % (134) 13 % (95) 27 % (6) 11 % (1)

Alcohol use 49 % (473) 43 % (304) 55 % (11) 22 % (2) 0.03BMI 29 (±6.6) 29 (±6.2) 25 (±4.5) 28 (±4.8) 0.01Heart rate 75 (±17.1) 73 (±16.5) 77 (±16.1) 71 (±12.2) 0.04NYHA class 0.14

I 1 % (9) 1 % (8) 0% (0) 0% (0)II 42 % (418) 40 % (286) 9 % (2) 44 % (4)III 44 % (439) 44 % (310) 68 % (15) 44 % (4)IV 12 % (121) 15 % (108) 23 % (5) 11 % (1)

LVEF 41 (±12.9) 42 (±13.1) 34 (±9.7) 41 (±14.7) 0.63HF hospitalization inyear before inclusion 33 % (328) 42 % (299) 64 % (14) 33 % (3) 0.0001Ischemic etiology 27 % (268) 63 % (446) 36 % (8) 22 % (2) <0.00001AF 44 % (430) 45 % (316) 41 % (9) 22 % (2) 0.57DM 28 % (276) 39 % (276) 9 % (2) 56 % (5) <0.00001COPD 19 % (189) 18 % (126) 5 % (1) 11 % (1) 0.28Peripheral Artery Disease 16 % (156) 30 % (206) 29 % (6) 11 % (1) <0.00001Pulmonarycongestion 0.0007

Single base 5 % (45) 7 % (50) 0% (0) 0% (0)Bi-basilar 40 % (377) 36 % (242) 81 % (17) 38 % (3)

Peripheral edema 63 % (552) 60 % (380) 95 % (19) 22 % (2) 0.005Rales 1⁄3 lung fields 3 % (26) 3 % (23) 5 % (1) 0% (0) 0.80JVP 27 % (269) 24 % (168) 41 % (9) 33 % (3) 0.32Hepatomegaly 4 % (34) 3 % (21) 24 % (4) 12 % (1) 0.0002Hypertension 57 % (562) 60 % (423) 59 % (13) 44 % (4) 0.61SBP (mmHg) 126 (±22.5) 126 (±22.6) 123 (±27.7) 128 (±30.3) 0.87Hemoglobin (g/dL) 16 (±18.9) 14 (±7.9) 13 (±2.7) 12 (±1.8) 0.0007Sodium (mmol/L) 139 (±3.4) 139 (±3.6) 134 (±27.2) 140 (±3.5) 0.004eGFR (MDRD formula)(mL/ min /1.73 m2) 83 (±102.1) 70 (±30.9) 54 (±45.1) 85 (±33.4) 0.002Potassium (mmol/L) 4.82 (±16.09) 4.4 (±2.11) 4.1 (±0.77) 4.17 (±0.58) 0.47Alkaline phosphatase(µg/L) 88 (71-117) 91 (72-115) 116 (75-180) 76 (66-85) 0.09Total bilirubin(µmol/L) 10 (7-15) 10 (7-15) 14 (8.2-31.25) 9 (5-12) 0.14HDL (mmol/L) 1.21 (±0.46) 1.18 (±0.56) 0.95 (±0.35) 0.93 (±0.21) 0.002Albumin (g/L) 38 (±6) 37 (±6) 31 (±7.6) 38 (±5.4) 0.001ASAT (U/L) 24 (19-32) 23 (17-29) 43 (26.2-259.5) 22 (14.8-32.25) 0.00001NT-proBNP (pg/mL) 1295 (462-3080) 1444 (546-4617) 22060 (6932-36814) 1404 (568-4741) <0.00001Use of beta-blockerat baseline 66 % (657) 74 % (528) 73 % (16) 89 % (8) 0.004Use of ACE-inhibitor/ARB at baseline 70 % (696) 69 % (490) 27 % (6) 44 % (4) 0.00008

AF: atrial fibrillation; BMI: body mass index; COPD: chronic obstructive pulmonary disease; DM: diabetes mellitus;eGFR: estimated glomerular filtration rate; HDL: high density lipoprotein-cholesterol; JVP: jugular venous pressure;LVEF: left ventricular ejection fraction; NT-proBNP: N-terminal pro B-type natriuretic peptide;NYHA class: New York Heart Association class; SBP: systolic blood pressure

248 Supplementary data

Table S23: Variables used for indication-bias correction (Chapter 7), with number (percent-age), mean ±SD, or median (IQR)

Description of baseline patient characteristicsN 2174 LaboratoryDemographics eGFR (CKD-EPI) (mL/ min /1.73 m2) 66.7 ± 23.66Sex (Male) 1593 (73%) Hematocrit (%) 40 ± 5.3Age (years) 69 ± 12 Blood urea nitrogen (mmol/L) 11.1 (7.5-17.9)Country NT-proBNP (pg/mL) 4148 (2330-8136)

Netherlands 392 (18%) Hemoglobin (g/L) 13.2 ± 1.90Germany 73 (3%) Sodium (mmol/L) 139.2 ± 3.95France 241 (11%) Potassium (mmol/L) 4.3 ± 0.56Greece 254 (11%) BNP (pg/mL) 667 (365-1281)Italy 263 (12%) Bilirubin (µmol/L) 14 (9.8-20.7)Norway 102 (5%) Total-cholesterol (mmol/L) 4.3 ± 1.33Poland 204 (9%) HDL-cholesterol (mmol/L) 1.1 ± 0.38Serbia 352 (16%) Hepcidin (nmol/L) 6.5 (2.2-16.6)Slovenia 44 (2%) STfR (mg/L) 1.5 (1.16-2.09)Sweden 97 (4%) FT4 (pmol/L) 16 (13.4-10.0)United Kingdom 152 (7%) HbA1c (%) 6.3 (5.79-7.11)

Smoking ASAT (U/L) 25 (16.6-38.0)No 795 (37%) ALAT (U/L) 25 (19-35)Past 1061 (49%) TSH (µU/L) 1.8 (1.15-2.92)Current 318 (15%) Gamma-GT (U/L) 55 (28-108)

Alcohol usage 616 (28%) Alkaline phosphatase (µg/L) 84 (65-117)Body mass index (kg/m2) 28 ± 5.5 TnI (pg/mL) 13 (7.0-28.4)NYHA class ET-1 (pg/mL) 5.3 (4.04-7.14)

I 45 (2%) Bio-ADM (pg/mL) 33.7 (22.6-53.8)II 762 (36%) Proteinuria (pg/dL) 5 (0-20)III 1039 (49%) Troponin (µg/L) 0.04 (0.01-0.10)IV 266 (13%)

Clinical ProfileLeft ventricular ejection fraction (%) 31 ± 11Heart Rate (beats/ min) 80 ± 20Systolic blood pressure (mmHg) 124 ± 22Diastolic blood pressure (mmHg) 75 ± 13Pulmonary congestion

Single base 262 (12%)Bi-basilar 873 (41%)

Peripheral oedema 1069 (49%)Elevated jugular venous pressure 579 (37%)Hepatomegaly 302 (14%)3rd heart tone 215 (100%)Rales >1⁄3 up lung fields 226 (20%)Orthopnea present 754 (35%)Medical HistoryIschemic heart disease 1156 (53%)HF-hospitalizationin year before inclusion 678 (31%)Heart failure duration (years) 8 (3.5-13.3)Diabetes mellitus 701 (32%)Atrial fibrillation 991 (46%)Myocardial infarction 801 (37%)Coronary artery bypass graft 367 (17%)Coronary artery disease 951 (44%)Percutaneous coronary intervention 449 (21%)Stroke 205 (9%)Peripheral arterial disease 240 (11%)COPD 373 (15%)

249

Table S24: Disease domains of all 92 biomarkers measured by Olink®

Biomarker A B C D E F G H I J K L MNAminopeptidase N X XAzurocidin X X X XBleomycin hydrolase XC-C motif chemokine 15 X X XC-C motif chemokine 16 X X XC-C motif chemokine 22 X X XC-C motif chemokine 24 X X X XC-X-C motif chemokine 16 XCadherin-5 XCarboxypeptidase A1 XCarboxypeptidase B XCaspase-3 X X X X XCathepsin D XCathepsin Z X XCD166 antigen X XChitinase-3-like protein 1 X X XChitoriosidase-1 XCollagen alpha-1 (I) chain X X X X X XComplement component C1q receptor X XContactin-1 XCystatin-B XE-selectin X XElafin XEphrin type-B receptor 4 X XEpidermal growth factor receptor X X XEpithelial cell adhesion molecule XFatty acid-binding protein, adipocyte X XGalectin-3 X XGalectin-4 XGranulins XGrowth/differentiation factor 15 XInsulin-like growth factor-binding protein 1 X XInsulin-like growth factor-binding protein 2 XInsulin-like growth factor-binding protein 7 XIntegrin beta-2 X X X XIntercellular adhesion molecule 2 XInterleukin-1 receptor type 1 XInterleukin-1 receptor type 2 XInterleukin-17 receptor A XInterleukin-18 binding protein XInterleukin-2 receptor subunit Alpha X X XInterleukin-6 receptor subunit Alpha X X XJunctional adhesion molecule A XKallikrein-6 X X XLow-density lipoprotein receptor XLympotoxin-beta receptor X XMonocypte chemotactic protein 1 XMatrix metalloproteinase-2 X X X XMatrix metalloproteinase-3 X XMatrix metalloproteinase-9 X XMetalloproteinase inhibitor 4 X X XMonocypte chemotactic protein 1 X X X X X X XMyeloblastin X X XMyeloperoxidase XMyoglobin XN-terminal pro B-type natriuretic peptide XNeurogenic locus notch homolog protein 3 XOsteopontin X XOsteoprotegerin XP-selectin X X X X XParaoxnase XPeptidoglycan recognition protein 1 X XPerlecan X XPlasminogen activator inhibitor 1 X X X X X X XPlatelet endothelial cell adhesion molecule X

TableS24– Continued on next page

250 Supplementary data

TableS24– Continued from previous pageBiomarker A B C D E F G H I J K L MPlatelet-derived growth factor subunit A X X X X X XProprotein convertase subtilisin/kexin type 9 X X XProtein delta homolog 1 XPulmonary surfactant-associated protein D X XResistin XRetinoic acid receptor responder protein 2 X X X X

Scavenger receptor cysteine-rich type 1 protein m130 XSecretoglobin family 3A member 2 XSpondin-1 X

XTartrate-resistant acid phosphatase type 5 X XTissue factor pathway inhibitor X XTissue-type plasminogen activator X X X XTrassferrin receptor protein 1 X XTrefoil factor 3 XTrem-like transcript 2 protein XTumor necrosis factor ligand superfamily member 13B XTumor necrosis factor receptor 1 XTumor necrosis factor receptor 2 X X X XTumor necrosis factor receptor superfamily member10C

X

Tumor necrosis factor receptor superfamily member 14 X X XTumor necrosis factor receptor superfamily member 6 X X X X X XTyrosine-protein kinase receptor UFO X X X X XTyrosine-protein phosphatase non-receptor type sub-strate 1

X

Urokinase plasminogen activator surface receptor X X XUrokinase-type plasminogen activator X X X X X X XVon Willebrand factor X X X XA: Wound healing; B: Response to peptide hormone; C: Hypoxia; D: Proteolysis; E: Platelet activation;F: MAPK cascade; G: Inflammation; H: Coagulation; I: Chemotaxis; J: Cell adhesion;K: Angiogenesis/blood vessel morphogenesis; L: Catabolic process; M: Other

251Ta

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3.9

4.4

4.1

4.8

4.0

4.3

4.2

<0.00

1(3.9-4.6)

(3.4-4.4)

(4.0-4.9)

(3.6-4.6)

(4.4-5.3)

(3.5-4.4)

(4.0-4.6)

(3.8-4.7)

1.9

1.5

2.8

1.5

2.2

2.1

1.7

1.8

AZU

1(1.5-2.5)

(1.5-1.8)

(2.0-4.1)

(1.5-1.8)

(1.7-2.8)

(1.5-3.1)

(1.5-2.2)

(1.5-2.2)

<0.00

1

4.5

4.1

4.7

4.1

4.7

4.9

4.5

4.4

BLM

hydrolase

(4.1-4.8)

(3.6-4.5)

(4.3-5.1)

(3.7-4.6)

(4.3-5.1)

(4.5-5.3)

(4.2-4.9)

(3.8-5.1)

<0.00

1

6.4

6.6

6.8

6.1

7.1

6.5

6.5

6.7

CCL1

5(6.0-6.8)

(6.1-7.2)

(6.3-7.2)

(5.7-6.5)

(6.8-7.7)

(5.9-7.0)

(6.0-6.9)

(6.2-7.3)

<0.00

1

CCL1

65.5

5.4

5.5

5.0

5.8

5.4

5.3

5.4

<0.00

1(5.0-6.0)

(4.7-6.0)

(5.0-6.0)

(4.6-5.5)

(5.3-6.2)

(4.9-5.9)

(4.8-5.8)

(4.9-6.1)

1.7

1.2

1.1

1.0

1.4

2.5

1.5

1.4

CCL2

2(1.2-2.3)

(0.7-1.8)

(0.7-1.5)

(0.6-1.5)

(1.0-1.9)

(1.8-3.1)

(1.1-1.9)

(0.9-2.0)

<0.00

1

CCL2

45.0

4.2

5.0

4.6

5.1

4.9

4.8

4.8

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1(4.3-5.7)

(3.5-5.1)

(4.5-5.8)

(3.8-5.3)

(4.4-5.7)

(4.1-5.6)

(4.3-5.5)

(4.0-5.7)

5.5

5.4

5.8

5.1

6.1

5.4

5.5

5.6

CXCL1

6(5.2-5.8)

(4.9-5.9)

(5.4-6.1)

(4.8-5.5)

(5.7-6.4)

(5.0-5.7)

(5.2-5.9)

(5.2-6.0)

<0.00

1

CDH5

2.7

2.4

2.7

2.4

3.2

2.6

2.9

2.6

<0.00

1(2.4-3.2)

(2.0-3.0)

(2.4-3.2)

(2.0-2.8)

(2.8-3.7)

(2.1-3.0)

(2.5-3.2)

(2.2-3.1)

3.8

3.6

3.4

3.7

4.3

3.5

3.3

3.7

CPA

1(3.3-4.4)

(2.9-4.3)

(2.8-4.0)

(3.1-4.4)

(3.7-5.2)

(3.0-4.3)

(2.8-3.9)

(3.1-4.4)

<0.00

1

CPB1

3.5

3.3

3.2

3.4

4.0

3.3

3.1

3.3

<0.00

1(3.0-4.1)

(2.5-4.1)

(2.6-3.7)

(2.7-4.1)

(3.4-4.7)

(2.7-3.9)

(2.5-3.6)

(2.6-4.0)

6.2

6.4

6.5

5.7

6.1

9.6

7.1

6.5

CASP

-3(5.4-7.0)

(5.2-7.6)

(5.6-7.5)

(4.8-6.8)

(5.4-7.2)

(8.6-10.4)

(6.1-8.3)

(5.3-8.1)

<0.00

1

CTSD

3.2

2.9

3.4

2.9

3.9

3.1

3.1

3.3

<0.00

1(2.8-3.6)

(2.4-3.4)

(2.9-3.8)

(2.5-3.4)

(3.4-4.3)

(2.7-3.6)

(2.7-3.5)

(2.7-3.9)

4.2

4.2

4.3

3.6

4.6

4.0

4.2

4.3

CTSZ

(3.8-4.5)

(3.8-4.7)

(3.9-4.7)

(3.3-4.0)

(4.2-5.0)

(3.5-4.5)

(3.8-4.6)

(3.8-4.6)

<0.00

1

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4.1

3.9

4.3

3.7

4.7

3.9

4.2

4.1

<0.00

1(3.8-4.4)

(3.5-4.4)

(3.9-4.6)

(3.4-4.1)

(4.3-5.0)

(3.5-4.3)

(3.9-4.5)

(3.7-4.6)

5.4

5.9

6.4

5.0

6.4

5.4

5.4

5.8

CHI3L1

(4.7-6.2)

(5.1-6.7)

(5.7-7.2)

(4.3-5.6)

(5.6-7.2)

(4.7-6.3)

(4.6-6.2)

(5.1-6.9)

<0.00

1

CHIT

12.4

2.4

2.3

1.7

2.8

2.6

2.4

-2.6

<0.00

1(1.7-3.0)

(1.6-3.1)

(1.7-3.0)

(0.9-2.3)

(2.0-3.3)

(2.0-3.4)

(1.9-3.2)

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1.5

1.6

1.5

1.4

2.2

1.4

1.7

1.7

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(1.1-1.9)

(1.1-2.1)

(1.1-2.0)

(0.9-1.8)

(1.7-2.5)

(1.1-1.8)

(1.3-2.0)

(1.2-2.0)

<0.00

1

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8.8

8.9

9.1

8.5

9.3

8.7

9.0

8.9

<0.00

1(8.4-9.1)

(8.5-9.4)

(8.7-9.4)

(8.1-8.9)

(9.0-9.7)

(8.3-9.2)

(8.6-9.4)

(8.5-9.3)

1.9

1.5

1.9

1.5

2.4

1.7

2.1

1.8

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(1.6-2.3)

(1.1-2.0)

(1.4-2.2)

(1.1-1.9)

(1.9-2.7)

(1.3-2.1)

(1.8-2.4)

(1.4-2.2)

<0.00

1

CST

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4.8

4.8

3.8

5.3

4.6

4.3

4.6

<0.00

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(4.0-5.4)

(4.3-5.5)

(3.8-4.3)

(4.9-6.0)

(4.0-5.3)

(3.8-4.8)

(3.9-5.2)

TableS

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252 Supplementary dataTa

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1.6

1.1

1.9

1.3

1.6

1.5

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(1.2-2.2)

(0.7-1.8)

(1.2-2.1)

(0.7-1.6)

(1.3-2.3)

(0.8-1.8)

(1.1-2.0)

(0.9-2.0)

<0.00

1

PI3

3.0

3.4

3.4

2.5

3.6

3.0

3.0

3.2

<0.00

1(2.5-3.5)

(2.8-4.4)

(2.9-4.2)

(2.5-2.9)

(3.1-4.3)

(2.5-3.7)

(2.5-3.5)

(2.7-3.7)

1.4

1.6

1.7

1.1

2.0

1.4

1.5

1.5

EPHB4

(1.1-1.7)

(1.2-2.1)

(1.4-2.1)

(0.8-1.4)

(1.6-2.3)

(1.1-1.7)

(1.2-1.8)

(1.1-1.9)

<0.00

1

EGFR

0.7

0.3

0.6

0.3

0.8

0.6

0.8

0.5

<0.00

1(0.5-1.0)

(-0.1-0.6)

(0.3-0.9)

(0.0-0.6)

(0.5-1.1)

(0.2-0.8)

(0.5-1.0)

(0.2-0.9)

2.8

2.5

2.7

2.3

3.3

2.7

3.3

2.8

Ep-Cam

(2.3-3.5)

(1.9-3.3)

(2.1-3.3)

(1.8-2.9)

(2.7-4.0)

(2.3-3.5)

(2.6-4.0)

(2.1-3.7)

<0.00

1

FABP4

5.3

5.6

5.5

4.7

6.8

4.8

4.7

5.4

<0.00

1(4.5-6.2)

(4.7-6.5)

(4.7-6.4)

(4.0-5.4)

(6.0-7.6)

(4.2-5.6)

(4.1-5.4)

(4.5-6.4)

2.9

3.0

3.1

2.5

3.6

3.0

3.1

3.0

Gal-4

(2.4-3.4)

(2.3-3.6)

(2.6-3.5)

(2.1-3.0)

(3.1-4.1)

(2.5-3.6)

(2.6-3.5)

(2.5-3.7)

<0.00

1

GRN

3.1

2.9

3.1

2.7

3.5

2.9

3.0

3.1

<0.00

1(2.7-3.3)

(2.4-3.3)

(2.8-3.4)

(2.3-3.1)

(3.2-3.9)

(2.6-3.3)

(2.7-3.3)

(2.7-3.3)

3.3

3.8

3.9

3.7

4.4

2.7

2.9

3.7

GDF-15

(2.7-3.9)

(3.1-4.7)

(3.1-4.7)

(3.0-4.5)

(3.5-5.5)

(2.3-3.4)

(2.4-3.6)

(2.9-4.6)

<0.00

1

IGFB

P-1

3.6

4.5

4.9

4.5

6.3

4.5

5.0

4.5

<0.00

1(2.7-4.4)

(3.6-5.3)

(3.9-5.9)

(3.9-5.2)

(5.6-6.9)

(3.8-5.4)

(4.2-5.6)

(3.6-5.6)

7.2

7.8

8.2

7.4

8.5

7.5

7.6

7.7

IGFB

P-2

(6.6-7.7)

(7.3-8.5)

(7.7-8.7)

(6.9-7.9)

(8.1-9.0)

(6.9-8.1)

(6.9-8.1)

(7.1-8.5)

<0.00

1

IGFB

P-7

3.5

3.4

3.8

3.4

4.7

3.4

3.6

3.7

<0.00

1(3.1-4.0)

(2.9-4.2)

(3.4-4.3)

(2.9-4.0)

(4.1-5.4)

(3.0-4.0)

(3.1-4.0)

(3.2-4.4)

4.6

4.1

4.5

4.0

4.8

4.4

4.6

4.3

ITGB2

(4.2-5.0)

(3.7-4.5)

(4.1-4.9)

(3.5-4.3)

(4.4-5.1)

(4.0-4.8)

(4.2-5.0)

(3.8-4.7)

<0.00

1

ICAM-2

4.2

4.1

4.4

3.9

4.8

4.1

4.3

4.3

<0.00

1(3.9-4.6)

(3.6-4.6)

(4.0-4.8)

(3.6-4.3)

(4.5-5.2)

(3.7-4.6)

(3.9-4.7)

(3.8-4.8)

5.8

5.7

6.0

5.5

6.5

5.6

5.9

5.9

IL-1RT

1(5.5-6.1)

(5.2-6.2)

(5.7-6.5)

(5.2-5.9)

(6.1-6.9)

(5.2-6.1)

(5.5-6.2)

(5.4-6.4)

<0.00

1

IL-1RT

24.2

3.6

4.2

3.8

4.3

3.9

4.1

4.0

<0.00

1(3.8-4.5)

(3.2-4.0)

(3.9-4.7)

(3.4-4.2)

(4.0-4.7)

(3.4-4.2)

(3.8-4.4)

(3.5-4.5)

3.3

3.0

3.4

2.9

3.7

3.6

3.3

3.2

IL-17R

A(2.9-3.6)

(2.4-3.5)

(2.9-3.7)

(2.5-3.2)

(3.2-4.0)

(3.2-4.0)

(2.9-3.7)

(3.0-3.6)

<0.00

1

IL-18B

P5.6

5.8

5.8

5.1

6.2

5.5

5.7

5.7

<0.00

1(5.2-6.0)

(5.3-6.5)

(5.4-6.4)

(4.7-5.5)

(5.8-6.7)

(5.0-6.0)

(5.3-6.1)

(5.3-6.3)

3.5

3.8

4.0

3.1

4.2

3.4

3.6

3.7

IL2-RA

(3.1-3.9)

(3.2-4.4)

(3.5-4.5)

(2.6-3.6)

(3.7-4.7)

(2.9-3.9)

(3.2-4.0)

(3.1-4.2)

<0.00

1

IL6-RA

10.2

9.9

10.2

9.6

10.3

10.5

10.1

10.1

<0.00

1(9.9-10.6)

(9.4-10.3)

(9.8-10.5)

(9.2-10.1)

(9.9-10.6)

(10.0-10

.7)

(9.8-10.5)

(9.9-10.6)

4.2

4.4

4.4

3.8

4.8

7.1

4.5

4.7

JAM-A

(3.7-4.7)

(3.8-5.1)

(3.9-5.0)

(3.3-4.4)

(4.3-5.3)

(6.3-7.8)

(3.9-5.3)

(3.8-5.5)

<0.00

1

KLK

62.5

2.6

2.7

2.4

3.0

2.5

2.7

2.7

<0.00

1(2.4-2.9)

(2.4-3.1)

(2.4-3.1)

(2.4-2.5)

(2.7-3.4)

(2.4-2.9)

(2.4-3.0)

(2.4-2.9)

TableS

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253Ta

bleS

25–

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dfr

ompr

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uspa

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ypes

12

34

56

78

p-v

alue

3.4

2.5

3.0

2.4

3.0

3.2

3.2

2.9

LDL-receptor

(2.9-4.0)

(2.1-3.1)

(2.5-3.5)

(1.9-2.8)

(2.6-3.5)

(2.6-3.6)

(2.8-3.7)

(2.3-3.4)

<0.00

1

MEPE

2.2

2.2

2.3

1.7

2.6

2.1

2.3

2.2

<0.00

1(1.8-2.6)

(1.7-2.7)

(1.9-2.7)

(1.3-2.1)

(2.2-3.0)

(1.7-2.6)

(1.9-2.6)

(1.8-2.8)

2.6

2.4

3.0

2.7

3.5

2.5

2.8

2.8

MMP-2

(2.2-3.1)

(1.9-2.9)

(2.6-3.5)

(2.2-3.2)

(3.2-3.9)

(2.1-3.1)

(2.4-3.3)

(2.3-3.4)

<0.00

1

MMP-3

6.5

6.6

7.3

6.4

7.2

6.6

6.7

6.8

<0.00

1(6.0-7.0)

(5.9-7.3)

(6.6-8.2)

(5.8-7.0)

(6.6-7.8)

(6.1-7.2)

(6.1-7.2)

(6.2-7.3)

3.5

2.4

4.0

2.6

3.5

3.2

3.0

2.9

MMP-9

(2.8-4.1)

(1.7-3.0)

(3.3-4.6)

(1.9-3.2)

(2.8-4.1)

(2.6-3.9)

(2.5-3.6)

(2.2-3.6)

<0.00

1

TIM

P4

4.4

4.3

4.7

4.1

5.1

4.6

4.4

4.5

<0.00

1(3.9-4.8)

(3.8-4.9)

(4.3-5.3)

(3.6-4.6)

(4.7-5.6)

(4.1-5.1)

(3.9-4.8)

(4.1-5.0)

6.1

6.2

6.6

5.6

6.8

5.9

6.1

6.2

MB

(5.5-6.6)

(5.6-6.9)

(6.0-7.4)

(5.1-6.2)

(6.3-7.6)

(5.3-6.6)

(5.6-6.6)

(5.6-6.7)

<0.00

1

NOTCH3

3.1

3.0

3.3

3.1

3.9

3.0

3.3

3.1

<0.00

1(2.7-3.5)

(2.5-3.5)

(2.9-3.7)

(2.6-3.4)

(3.5-4.3)

(2.6-3.4)

(2.8-3.6)

(2.7-3.6)

4.7

4.9

5.3

4.5

5.7

4.5

4.7

4.9

OPN

(4.2-5.2)

(4.3-5.5)

(4.8-5.8)

(3.9-5.1)

(5.4-6.1)

(3.9-5.0)

(4.2-5.2)

(4.4-5.5)

<0.00

1

OPG

2.5

2.5

2.9

2.3

3.3

2.5

2.7

2.7

<0.00

1(2.2-2.9)

(2.0-3.0)

(2.5-3.3)

(1.9-2.7)

(2.9-3.8)

(2.0-2.9)

(2.3-3.0)

(2.3-3.1)

8.0

7.8

8.2

7.4

8.3

10.1

8.3

8.1

SELP

(7.6-8.5)

(7.1-8.5)

(7.7-8.7)

(6.9-8.0)

(7.7-8.8)

(9.3-10.8)

(7.8-8.9)

(7.5-8.8)

<0.00

1

PON3

4.4

3.6

4.3

3.6

4.3

4.4

4.8

4.0

<0.00

1(3.8-5.0)

(3.0-4.4)

(3.6-4.9)

(2.9-4.3)

(3.7-4.9)

(3.7-5.0)

(4.3-5.4)

(3.4-4.6)

6.6

6.7

7.0

5.9

7.0

6.6

6.4

6.5

PGLY

RP1

(6.2-7.1)

(6.1-7.2)

(6.6-7.5)

(5.5-6.4)

(6.7-7.5)

(6.2-7.3)

(5.9-6.8)

(6.1-7.1)

<0.00

1

PLC

6.3

6.7

6.6

6.0

7.1

6.5

6.3

6.4

<0.00

1(6.0-6.7)

(6.0-7.1)

(6.1-7.0)

(5.5-6.4)

(6.7-7.5)

(6.0-7.0)

(5.9-6.7)

(6.0-6.9)

5.0

4.3

4.6

4.2

5.5

6.0

5.0

5.0

PAI

(4.3-5.8)

(3.5-5.0)

(3.8-5.5)

(3.6-5.1)

(4.7-6.1)

(5.5-6.6)

(4.2-5.8)

(4.0-5.9)

<0.00

1

PECAM-1

4.1

3.8

4.1

3.8

4.4

6.0

4.3

4.2

<0.00

1(3.7-4.5)

(3.2-4.4)

(3.8-4.6)

(3.3-4.1)

(4.0-4.9)

(5.2-6.8)

(3.8-4.8)

(3.5-4.7)

1.8

1.3

1.4

1.1

1.8

3.4

2.2

1.5

PDGF

(0.9-2.6)

(0.6-2.1)

(0.8-2.3)

(0.5-1.8)

(1.2-2.5)

(2.7-4.0)

(1.4-2.9)

(0.9-2.5)

<0.00

1

PCSK

91.9

1.6

1.9

1.5

2.0

1.9

1.9

1.8

<0.00

1(1.6-2.3)

(1.2-2.0)

(1.6-2.2)

(1.2-1.8)

(1.6-2.4)

(1.5-2.3)

(1.6-2.2)

(1.4-2.2)

4.1

4.5

4.2

3.5

4.8

3.9

4.3

4.4

DLK

-1(3.7-4.6)

(3.8-5.2)

(3.7-4.8)

(3.1-3.9)

(4.3-5.4)

(3.4-4.4)

(3.8-4.8)

(3.9-4.9)

<0.00

1

PSP

-D2.0

1.8

2.4

1.9

2.3

1.7

2.1

2.1

<0.00

1(1.5-2.6)

(1.1-2.5)

(1.9-3.0)

(1.3-2.4)

(1.7-2.8)

(1.2-2.5)

(1.6-2.7)

(1.4-2.6)

5.9

6.1

6.5

5.4

6.4

6.4

5.8

6.1

RETN

(5.5-6.4)

(5.6-6.6)

(6.0-6.9)

(4.9-5.7)

(6.0-6.8)

(5.8-6.9)

(5.3-6.2)

(5.4-6.5)

<0.00

1

RARRES2

11.1

11.0

11.0

10.5

11.3

11.3

11.1

11.1

<0.00

1(10.8-11

.4)

(10.6-11

.4)

(10.7-11

.3)

(10.2-10

.8)

(10.9-11

.5)

(11.0-11

.6)

(10.7-11

.4)

(10.7-11

.4)

TableS

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254 Supplementary dataTa

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p-v

alue

6.8

6.6

7.0

6.4

7.4

6.5

6.8

7.0

CD16

3(6.4-7.2)

(6.1-7.1)

(6.5-7.5)

(5.9-6.9)

(6.9-7.9)

(6.1-7.0)

(6.4-7.2)

(6.3-7.5)

<0.00

1

SCGB3A

21.8

2.0

2.4

1.7

2.9

2.0

2.3

2.4

<0.00

1(1.2-2.3)

(1.4-2.6)

(1.8-3.0)

(1.2-2.3)

(2.4-3.5)

(1.5-2.6)

(1.7-2.9)

(1.7-2.9)

1.5

1.5

1.9

1.4

2.4

1.4

1.6

1.6

SPON1

(1.2-1.9)

(1.1-1.9)

(1.5-2.3)

(1.2-1.8)

(2.0-2.8)

(1.1-1.8)

(1.3-1.9)

(1.3-2.1)

<0.00

1

ST2

6.3

8.4

23.9

14.2

19.9

4.7

4.9

9.8

<0.00

1(3.3-11.8)

(4.0-19.6)

(11.1-47

.5)

(7.7-27.1)

(9.7-36.4)

(2.4-9.5)

(2.4-11.3)

(4.3-21.3)

4.5

4.1

4.4

3.8

4.3

4.4

4.5

4.4

TR-A

P4(4.1-4.9)

(3.6-4.6)

(4.0-4.8)

(3.4-4.1)

(4.0-4.8)

(4.1-4.9)

(4.1-4.9)

(3.8-4.7)

<0.00

1

TFP

I7.8

7.4

8.0

7.3

8.0

7.9

7.9

7.7

<0.00

1(7.4-8.2)

(6.9-7.8)

(7.5-8.3)

(6.8-7.7)

(7.6-8.4)

(7.3-8.2)

(7.4-8.2)

(7.3-8.1)

5.3

4.0

5.0

4.5

5.6

7.0

4.6

5.0

t-PA

(4.5-6.3)

(3.3-4.6)

(4.4-5.7)

(3.8-5.4)

(5.0-6.3)

(5.6-8.1)

(4.1-5.3)

(4.1-5.9)

<0.00

1

TR

5.0

4.8

5.3

4.8

5.6

4.8

4.9

5.1

<0.00

1(4.5-5.4)

(4.3-5.5)

(4.8-5.8)

(4.3-5.4)

(5.2-6.2)

(4.2-5.3)

(4.4-5.5)

(4.5-5.8)

5.0

5.6

5.5

4.7

6.1

5.0

5.0

5.3

TFF

3(4.5-5.4)

(4.8-6.2)

(5.0-6.1)

(4.3-5.1)

(5.6-6.7)

(4.4-5.5)

(4.6-5.5)

(4.7-5.8)

<0.00

1

TLT

-23.5

3.5

3.6

2.8

3.8

3.8

3.6

3.4

<0.00

1(3.1-3.9)

(3.0-4.1)

(3.1-4.0)

(2.4-3.2)

(3.3-4.2)

(3.3-4.2)

(3.3-4.0)

(3.0-3.9)

5.3

5.1

5.5

5.1

5.9

5.1

5.4

5.4

TNFS

F13B

(4.9-5.7)

(4.6-5.7)

(4.9-6.0)

(4.7-5.6)

(5.5-6.4)

(4.6-5.5)

(5.0-5.8)

(4.9-5.9)

<0.00

1

TNF-R1

4.6

5.3

5.2

4.3

5.7

4.5

4.6

4.9

<0.00

1(4.2-5.0)

(4.6-5.9)

(4.7-5.8)

(4.1-4.6)

(5.2-6.2)

(4.1-5.2)

(4.2-5.1)

(4.3-5.4)

4.2

4.7

4.6

3.7

5.1

4.1

4.2

4.5

TNF-R2

(3.8-4.6)

(4.1-5.3)

(4.1-5.3)

(3.3-4.1)

(4.6-5.6)

(3.5-4.7)

(3.8-4.7)

(3.9-4.9)

<0.00

1

5.3

5.3

5.6

4.7

5.6

5.1

5.4

5.3

<0.00

1TNFR

SF10

C(4.9-5.7)

(4.8-5.8)

(5.3-6.1)

(4.2-5.1)

(5.3-6.0)

(4.6-5.6)

(4.9-5.8)

(4.7-5.8)

3.9

4.5

4.4

3.6

4.8

4.5

4.1

4.3

TNFR

SF14

(3.6-4.3)

(4.0-5.1)

(3.9-4.9)

(3.1-3.9)

(4.3-5.3)

(4.0-5.1)

(3.7-4.5)

(3.7-4.7)

<0.00

1

FAS

4.1

4.1

4.3

3.7

4.6

4.3

4.2

4.2

<0.00

1(3.8-4.4)

(3.6-4.6)

(4.0-4.7)

(3.3-4.0)

(4.2-5.0)

(3.8-4.6)

(3.9-4.5)

(3.7-4.6)

7.1

7.0

7.3

6.7

7.7

7.0

7.1

7.1

AXL

(6.7-7.5)

(6.5-7.5)

(6.9-7.7)

(6.3-7.1)

(7.3-8.1)

(6.6-7.3)

(6.8-7.5)

(6.7-7.6)

<0.00

1

SHPS-1

2.9

2.9

3.1

2.5

3.5

2.7

3.0

3.0

<0.00

1(2.5-3.3)

(2.5-3.4)

(2.7-3.5)

(2.1-2.9)

(3.1-4.0)

(2.4-3.3)

(2.6-3.4)

(2.5-3.6)

4.0

4.2

4.4

3.6

4.8

3.9

3.9

4.1

U-PAR

(3.6-4.3)

(3.7-4.7)

(4.0-4.9)

(3.3-4.0)

(4.5-5.2)

(3.5-4.5)

(3.6-4.3)

(3.6-4.7)

<0.00

1

uPA

3.9

3.5

3.8

3.6

4.3

4.1

3.9

3.9

<0.00

1(3.6-4.3)

(3.0-4.0)

(3.4-4.1)

(3.2-4.0)

(4.0-4.7)

(3.7-4.5)

(3.6-4.3)

(3.4-4.3)

6.5

5.3

5.9

5.7

6.2

7.9

5.6

5.8

vWF

(5.7-7.4)

(4.5-6.0)

(5.2-6.9)

(4.9-6.6)

(5.5-7.1)

(6.9-8.6)

(5.0-6.3)

(5.1-6.9)

<0.00

1