mortality and survival in systemic sclerosis: systematic review and meta-analysis

Author's Accepted Manuscript

Mortality and Survival in Systemic Sclerosis.Systematic Review and Meta-Analysis

Manuel Rubio-Rivas, Cristina Royo, XavierCorbella, Vicent Fonollosa, Carmen PilarSimeón

PII: S0049-0172(14)00080-8DOI: http://dx.doi.org/10.1016/j.semarthrit.2014.05.010Reference: YSARH50817

To appear in: Seminars in Arthritis and Rheumatism

Cite this article as: Manuel Rubio-Rivas, Cristina Royo, Xavier Corbella, VicentFonollosa, Carmen Pilar Simeón, Mortality and Survival in Systemic Sclerosis.Systematic Review and Meta-Analysis, Seminars in Arthritis and Rheumatism, http://dx.doi.org/10.1016/j.semarthrit.2014.05.010

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Title: Mortality and survival in Systemic Sclerosis. Systematic review and meta-analysis Keywords: systemic sclerosis, mortality Corresponding Author: Dr. Manuel Rubio-Rivas, Corresponding Author's Institution: Bellvitge University Hospital First Author: Manuel Rubio-Rivas Order of Authors: Manuel Rubio-Rivas1; Cristina Royo1; Xavier Corbella1; Vicent Fonollosa2; Carmen Pilar Simeón2

Affiliations: 1. Bellvitge University Hospital. Autoimmune Diseases Unit 2.Vall d’Hebron University Hospital Contact information for the corresponding author: [email protected] Abstract: Objective: To determine the mortality, survival and causes of death in patients with Systemic Sclerosis (SSc) through the meta-analysis of the observational studies published up to 2013. Methods: We performed a systematic review and meta-analysis of the observational studies in patients with SSc and mortality data from entire cohorts, published in MEDLINE and SCOPUS up to July 2013. Results: 17 studies were included in the mortality meta-analysis from 1964 and 2005 (mid-cohort years), with data from 9239 patients. The overall SMR was 2.72 (CI 95% 1.93-3.83). 43 studies have been included in the survival meta-analysis, reporting data from 13529 patients. Cumulative survival from onset (first Raynaud) has been estimated in 87.6% at 5 years and 74.2% at 10 years, from onset (non-Raynaud's first symptom)84.1% at 5 years and 75.5% at 10 years and from diagnosis 74.9% at 5 years and 62.5% at 10 years. Pulmonary involvement represented the main cause of death. Conclusions: SSc presents a larger mortality than general population (SMR 2.72). Cumulative survival has been estimated from diagnosis in 74.9% at 5 years and 62.5% at 10 years. Pulmonary involvement represented the main cause of death.

Introduction

Systemic Sclerosis (SSc) represents one of the autoimmune systemic diseases

with worse prognosis. Several studies have been performed from the sixties of the last

century reflecting a higher mortality rate between 1.05-fold and 7.2-fold1,2 compared

with the general population. There have been changes in the pattern of death in the

latest decades after the introduction of new therapies, with an important reduction in the

number of deaths related to kidney involvement and being nowadays the pulmonary

involvement (interstitial lung disease or pulmonary hypertension) the leading causes of

death in the majority of patients3.

The most valuable parameter in order to compare mortality studies is the

assessment of the standardized mortality ratio (SMR), fundamental tool in the only 4

mortality meta-analyses reported in SSc4. The SMR is the ratio between observed

mortality and expected mortality in sex and age-matched general population. These 4

meta-analyses are based on the assessment of the SMR, Elhai et al. {9 studies, overall

SMR 3.53(3.03-4.11)}5, Ioannidis et al. (7 studies)2, Toledano et al. {7 studies, overall

SMR 3.51(2.74-4.50)}6 and Komócsi et al. (10 studies, overall SMR 3.24)7. One of the

goals of our systematic review and meta-analysis is to perform an actual assessment of

mortality in SSc, pointing out the changes of the ratio in the latest decades, and the

changes in the patterns of death.

Prior the assessment of survival of any cohort we must pay attention in the

methodology of the study, because of a huge variability among them, sometimes

assessing survival from diagnosis and sometimes from the onset of disease. This last

data is obviously a more imprecise data but certainly more real. Several survival and

mortality studies from single cohorts1,3,8-79 and reviews have been published from the

last mid-century, reporting data about cumulative survival at different times of follow-up

and measured sometimes from the onset of disease and sometimes from the time of

diagnosis. This is crucial at the time of meta-analyzing these data and avoid any bias of

selection. Risk factors for poor outcome are often reported in these studies, sometimes

from univariate and sometimes from multivariate analysis. In order to assess overall

survival and risk factors for poor outcome we have performed a systematic review and

posterior qualitative and quantitative meta-analysis from published articles. We have

also compared survival from studies before and after 1990.

Methods

The studies collected in this issue are studies from patients fulfilling ACR criteria

for SSc after 1980 and LeRoy criteria after 198880-1, except several studies before 1980.

At that time there were no standardized criteria and diagnosis was made according to

the presence of Raynaud’s phenomenon and skin characteristic changes according to

O’Leary and Waissman classification in 194382 and Tuffanelli and Winkelmann in

196283.

The search was performed through MEDLINE and SCOPUS databases between

January 1960 and July 2013, using the terms (systemic, scleroderma or systemic

sclerosis) [MesH] AND (death or mortality) and performed by two independents

investigators (R-R.M. and R.C.). The search was completed by the bibliography review

of every paper selected for full-text examination. No restriction related with language

was performed. First search found 1801 articles, being 1699 articles non-selected

assessing the title and/or abstract. 102 articles were full-text reviewed (Figure 1).

In order to perform the mortality meta-analysis, out of the mortality and survival

studies from entire cohorts reported, we have selected those reflecting the SMR.

Studies without data about SMR or raw data not enough to estimate were ruled out.

Seventeen articles reported the SMR and were finally selected for the meta-analysis

(Figure 1). Two articles were at that time ahead of print but they were also included after

full-text review66,77. Some articles show observed and expected survival data and one

might be tempted to extract SMR from them26-9. We decided to rule out these studies in

order to avoid any sort of selection bias. Several articles report SMR from same

cohorts, so we decided to choose the larger of every one of them. For instance, the

study by Geirsson et al.47 shows SMR data from 100 prospective patients, but it is in

fact the same cohort than the study by Hesselstrand et al.49. The studies by Simeón et

al.42 and Pérez-Bocanegra et al.57 belong to same cohort as well. Joven et al.60 and

Alba et al.66 proceed also from Spain but from different cohorts. Two studies from

Canada (Abu-Shakra et al.35 and Lee et al.37) belong to same cohort. Another study was

made also in Canada (Scussel-Lonzetti et al.)56 but belongs to a different cohort. The

studies from UK (Bryan et al.45 and Strickland et al.77) belong to different cohorts.

In order to perform the survival meta-analysis we ruled out several studies from

mortality records without follow-up and those belonging to same cohorts and times of

study. Two studies from the EUSTAR71,79 are suspicious to content patients from other

reported cohorts so they have been ruled out as well. Eventually, 43 articles were

included in the survival meta-analysis (Figure 1). In order to avoid further bias about the

assessment of survival, we selected those articles with survival from the onset (first

Raynaud and non-Raynaud’s first symptom) and those from diagnosis.

For the assessment of risk factors we selected those described in multivariate

analysis when cited or just from univariate analysis if there weren’t alternative. We did

initially a qualitative meta-analysis. Those studies with cited Cox regression and results

referred as hazard ratio were quantitatively meta-analyzed as well. For this purpose, we

assessed the main risk factors cited as pulmonary hypertension, pulmonary fibrosis,

heart involvement, renal involvement (including sclerodermic renal crisis), male gender,

diffuse subset (dcSSc), high eritrosedimentation rate and age/year. Those studies

reflecting the HR without confidence interval have been ruled out .

In order to assess the different SSc-related causes of death, 40 studies

describing this condition have been included (Figure 1). However, several studies define

the cause of death as definitive, probably or possibly SSc-related. Only those cases

described as definitive have been interpreted as SSc-related. We have pointed out

those deaths due to pulmonary involvement, cardiac involvement, renal and

gastrointestinal. Pulmonary involvement has been described as the presence of

interstitial lung disease or pulmonary hypertension. Renal crisis is defined by the

presence of renal function impairment in a short time period in the absence of other

renal diseases, with normal urine sediment sample and accompanied by malignant

hypertension. Gastrointestinal involvement includes esophageal hypomotility, gastric

hypomotility, gastric antral vascular ectasia, intestinal dysmotility, malabsortion and

intestinal pseudo-obstruction. Finally, cardiac involvement is defined by the presence of

pericarditis, ischemic cardiomyopathy of unknown cause, electrocardiographic

abnormalities and left or right heart failure.

We have found in some studies deaths due to cardiopulmonary involvement in a

same group without differentiation. We are aware that sometimes is hard to differentiate

the immediate cause of death in a patient with both conditions, but nevertheless these

cases have been ruled out and not counted into the pulmonary nor cardiac deaths. Only

those cases reflecting that both conditions at a time have led to death have been

included into the analysis in both categories. Although it’s been described a larger

incidence of cancer related to SSc, it hasn’t been considered into the SSc-related

causes of death.

Quality assessment was performed by mean of the Newcastle-Ottawa Scale84 for

observational studies.

Statistical analysis

Categorical variables are described as absolute number and percentage.

Continuous variables are described as mean and standard deviation. For the survival

and causes of death assessment, univariate analysis has been performed by Student’s t

for independent groups (before and after 1990) for quantitative variables. Linear

regression was performed to assess changes at 5 and 10-year survival over time and

lung and kidney SSc-related causes of death. Several outlier studies (>1.5*first or third

quartile) have been ruled out for this purpose to avoid the assessment of those studies

that due to different reasons might not belong to the same group of studies85.

SMR was the parameter chosen for the mortality statistical analysis. In those

studies reflecting the SMR but without confidence interval, it has been estimated by the

formula SMR ± 1.96 (SMR/√N), where N is the number of deaths86. We performed the

inverse variance-weighted method, initially by the fixed effects model. Between-study

variability has been measured by I2 parameter87, and when confirmed (p ≤ 0.05) then

we performed the random effects model. In fact, random effects model assumpts that

there is an underlying effect for each study which varies randomly across studies and

the true overall effect is an average of these. Heterogeneity has been evaluated by the

performance of a meta-regression.

Publication bias has been ruled out by mean of the Begg’s method (tau=0.333;

p= 0.602)88. Statistical analysis has been performed by SPSS 15.0.

Results

Mortality meta-analysis

Eventually 17 studies were included in the meta-analysis (Table 1). These are 16

cohort studies and 1 transversal observational study from mortality records. No study

was excluded because of the quality assessment. These 17 studies report data from

9239 patients. They were 7150 women (80.2%), with a mean age at onset of 44.5 years

(SD 2.9) and at enrolment 48 years (SD 3.5). Limited subset (lcSSc) was diagnosed in

3277 patients (63.2%) and diffuse (dcSSc) in 1459 patients (28.1%). The mid-cohort

years of every study ranged from 1964 to 2005.

SMR ranged between 1.05 and 5.40 in the different studies included. Overall

SMR has been estimated in 2.72 (CI 95% 1.93-3.83). In order to compare mortality from

older studies and recent studies we performed the assessment of studies before 1990

and after 1990 (mid-cohort year). Before 1990 we conducted the meta-analysis of 6

studies, with an overall SMR 3.35 (1.57-7.11) and after 1990 we conducted the meta-

analysis of 11 studies showing a SMR 2.42 (1.89-3.11). Both assessments were

performed by the random effects model because of the presence of between-study

variability detected in the fixed effects model. Meta-regression was performed to

evaluate changes in SMR over time, showing a decreasing SMR in recent series but

without significance (coefficient b=-0.055 p 0.064), but it achieved statistical significance

when we ruled out the outlier study (> first or third percentile x1.5) from Walsh et al.

(coefficient b=-0.064 p 0.02). SMR for different subsets was assessed. For patients with

dcSSc we estimated a SMR 4.73(3.69-6.07) and for those with lcSSc a SMR 2.04 (1.55-

2.68). The SMR for male gender was 3.14 (2.62-3.76) and for female gender 2.93 (2.36-

3.64). Results are shown in Figure 2-3.

Survival and risk factors for poor outcome meta-analysis

Forty-three studies have been included in the survival meta-analysis (Table 2)

reporting data from 13529 patients, 10436 (82.9%) of them were female. 5943(53.4%)

were classified as lcSSc and 3501 (30.7%) as dcSSc. The mean age at the onset of the

disease was 44.4 years (SD 3.0) and 47.8 years (SD 4.3) at the enrolment. Anti-

centromere antibodies were present in 2308 patients (30.2%) and anti-topoisomerase I

in 1659 patients (26.7%).

Cumulative survival from the onset (first Raynaud) has been estimated in 87.6%

(SD 9.1) at 5 years, 74.2% (SD 10.9) at 10 years and 55.8% (SD 21.1) at 20 years

(there were no cases reported at 1 year to be evaluated). Cumulative survival from the

onset (non-Raynaud’s first symptom) has been estimated in 93.5% (SD 2.1) at 1 year,

84.1% (SD 8.5) at 5 years, 75.5% (SD 6.3) at 10 years and 48.5% (SD 9.2) at 20 years.

From diagnosis it’s been estimated in 86.5% (SD 9.4) at 1 year, 74.9% (SD 13.6) at 5

years, 62.5% (SD 14.5) at 10 years and 41.8% (SD 16.2) at 20 years.

We have also assessed survival for two major subtypes when reported. For

lcSSc subtype cumulative survival has been estimated from diagnosis in 90.9% (SD

4.9) at 5 years and 78.2% (SD 8.9) at 10 years. From onset (first Raynaud) has been

estimated in 83.2% (SD 11.5) at 10 years. From onset (non-Raynaud’s first symptom)

has been estimated in 100% at 1 year, 93.7% (SD 4.9) at 5 years and 86.9% (SD 8.6)

at 10 years. For the diffuse subtype cumulative survival has been estimated from

diagnosis in 69.6% (SD 12.8) at 5 years and 55.6% (SD 20.3) at 10 years. From the

onset (first Raynaud) has been estimated in 66.3% (SD 21) at 10 years. From the onset

(non-Raynaud’s first symptom) has been estimated in 60% at 1 year, 68.3% (SD 20.8)

at 5 years and 50.5% (SD 17) at 10 years.

We compared the studies prior to 1990 (according to the mid-cohort year) and

after 1990. Prior to 1990 we assessed 27 studies and 16 studies after 1990. Survival

has been assessed from diagnosis and from onset (first Raynaud or non-Raynaud’s first

symptom). Different survival in both cohorts is described in Table 3, showing an

increasing survival in recent series at all times (1, 5, 10 and 20-year follow-up).

However, only improvement at 5-year survival from diagnosis achieves statistical

significance. Linear regression shows this very same trend, at 5-year (coefficient

B=0.595 p<0.001) and 10-year (Coefficient B= 0.536 p=0.025) follow-up survival from

diagnosis, but this time achieving statistical significance. Results are shown in Figure 4.

Main risk factors for poor outcome are reflected in figure 5. Thus, interstitial lung

disease (overall HR 2.89, CI95% 2.24-3.72), pulmonary hypertension (overall HR 2.62,

CI95%1.64-4.17), dcSSc (overall HR 2.28, CI95% 1.69-3.08), older age (age/year

overall HR 1.05, CI95%1.04-1.06), kidney involvement (overall HR 4.22, CI95% 3.42-

5.19), heart involvement (overall HR 3.43, CI95% 1.35-8.70), male gender (overall HR

1.88, CI95% 1.48-2.38) and high eritrosedimentation rate (overall HR 2.77, CI95% 2.06-

3.71) have been reported as the main risk factors for poor outcome.

Causes of death meta-analysis

Forty studies report SSc-related or SSc-non related causes of death, so they

have been included for the present assessment (table 4). They report data from 13679

patients. 3058 deaths (22.7%) were reported. SSc-related death was reported in 1445

patients (47.6%). Among them, 539 deaths (47.8%) were attributed to lung involvement,

288 (25.6%) to heart involvement, 209 (18.5%) to kidney involvement and 86 (7.6%) to

gastrointestinal involvement. Among SSc-non related causes of death, cancer were

described in 356 patients (12.2%), infection in 216 patients (7.5%) and atherosclerosis

in 216 patients (11.9%).

We compared the studies prior to 1990 (according to the mid-cohort year) and

after 1990. Prior to 1990 we assessed 22 studies reporting data from 6096 patients.

1747 deaths (28.7%) were reported. SSc-related death was reported in 752 patients

(43.6%). Among them, 191 deaths (37.5%) were attributed to lung involvement, 122

(24%) to heart involvement, 133 (26%) to kidney involvement and 52 (10.2%) to

gastrointestinal involvement.

After 1990 we analyzed data from 18 studies representing 7583 patients. 1311

deaths (17.7%) were reported. SSc-related death was reported in 693 patients (52.9%).

Among them, 348 deaths (56.3%) were attributed to lung involvement, 166 (26.9%) to

heart involvement, 76 (12.3%) to kidney involvement and 34 (5.5%) to gastrointestinal

involvement.

We found significant differences in the patterns of death in these two cohorts, mainly

with increasing rate of death attributable to lung involvement and a decreasing rate of

death due to renal involvement (Table 5). Linear regression was performed in order to

show this change in the pattern of death over time for lung and kidney related death

(Figure 6).

Conclusions

The present study constitutes the largest meta-analysis ever done before in SSc

for the assessment of mortality (data from 17 studies for the SMR meta-analysis and 40

for the meta-analysis of causes of death) and survival (data from 43 studies). To date,

only 4 meta-analysis in the medical literature had focused in SSc mortality from the

assessment of SMR (Elhai, Ioannidis, Toledano and Komócsi)2, 5, 6,7, reporting data from

9, 7 ,7 and 10 studies respectively. We have also focused in the SMR for the

assessment of mortality ever since it is the ratio between observed and expected

deaths related to sex and aged-matched population. It represents a more reliable

parameter than the raw mortality or survival from a cohort. Overall mortality in our

cohort is 2.72, being the larger the older studies, in special the first one, Zarafonetis et

al.15 with SMR 5.40. The minor mortality in the last decades might be due to different

causes but specially related with an earlier visceral involvement diagnosis and better

management and treatment of these patients, even more in case of renal involvement3.

Further stratification of studies before and after 1990 and meta-regression shows

a trend of less mortality in modern series but without statistical significance, even more

if we take into account that the study from Walsh et al. is a clear outlier and acts as a

modifier factor, getting better the mortality before 1990. It is in fact a real different study

so it is focused in mortality records from scleroderma patients.

One of the largest meta-analysis to date, Elhai et al.5, failed to demonstrate this

change of mortality over time. Our study shows data from 7 more studies and avoid a

possible bias showing data from two Swedish studies (Hesselstrand and Geirsson et

al)47,49 belonging to same cohort as in Elhai et al.5 study is reported. We have ruled out

two studies without SMR reported (Ferri et al and Arias-Núñez et al)27,64 but included in

Elhai et al.5 meta-analysis with SMR calculated presumably from Kaplan-Meyer survival

curves. Although approximated, this is not the real SMR and constitutes a selection

bias. By the other hand, in Komócsi et al.7 meta-analysis, they do demonstrate a

change in mortality over time, including 10 studies with SMR detailed but certainly they

also include Ferri et al.27 study with SMR measured presumably from Kaplan-Meyer

curves.

SSc-related death has been estimated in our study in 47.6% of all deaths. It is

noteworthy that cardiopulmonary involvement has been the leading cause of death,

representing about 73% of all SSc-related deaths. These data might suggest screening

pulmonary and cardiological involvement even much more often than we do today and

maybe to be more aggressive with the treatment of pulmonary hypertension/fibrosis and

cardiological involvement. Perhaps, a more accurate diagnosis of pulmonary and

cardiac disease with better images devices in the latest decades might be part of the

explanation for these changes. By the other hand, renal and gastrointestinal ratio has

suffered a decline in the latest 2 decades and today they represent only an 18% of all

deaths. It is thought to be related with new therapies since the introduction of ACE

inhibitors and maybe with early renal crisis diagnosis. These changes in the patterns of

death had been described before in two single cohorts3,59, but never before meta-

analyzed from all mortality studies.

A similar ratio of dcSSc subtype has been described in oldies and modern

studies. Therefore, it seems that lcSSc subtype is more present after 1990. We can’t

assure that because of the fact that in some of the papers published before 1990 they

defined a supplementary category with intermediate cutaneous involvement with

thickening of arms and legs but sparing the trunk. If the involvement was up or below

elbows and knees wasn’t described, so we don’t know if those cases today would

represent lcSSc or dcSSc subsets.

Among SSc-non related causes of death cancer must be pointed out. Several

studies have focused in this topic and show a higher incidence in these patients. A

recent meta-analysis describes a standardized incidence ratio (SIR) 1.41 (1.18-1.68)89.

Mortality due to cancer is not detailed in every study included in the present meta-

analysis. We found 356 deaths (12.2%) from cancer when reported.

In order to assess SSc survival, the whole cohort has been divided in 3 groups,

those studies describing survival from the time of diagnosis and those from onset (from

first Raynaud and from non-Raynaud’s first symptom). The measure of survival from the

time of onset is a more real parameter so it is part of the disease but sometimes is hard

for the patients to remember the accurate date. By the other hand, measure from the

time of diagnosis is better methodologically but discounts the first years of the disease.

In these 3 groups survival tends to be better but only 5-year survival achieves statistical

significance and only in those studies evaluated from diagnosis (from onset we find a

trend) when calculated by Student’s t (larger number of studies with survival data from

onset are required). When calculated by meta-regression, significant differences are

found at 5 and 10-year survival from diagnosis and also at 10-year survival from onset

(from non-Raynaud’s first symptom). It is true that at 1 and 20-year follow-up, survival

can’t be properly compared in both cohorts because just a few number of studies report

this data. When we compare those studies before and after 1990, 10-year survival,

although better, is far to achieve the statistical significance we find at 5-year follow-up. It

hasn’t been reported previously in the literature and we can hypothesize if new

treatments have changed the early mortality of SSc but not as much the late mortality.

The two great advances in treatment from 1990 have been the introduction of ACE

inhibitors for renal crisis and new treatments for pulmonary hypertension and interstitial

lung disease. We suggest that maybe we have improved early manifestations in the

curse of the disease (renal crisis) and maybe new treatments for pulmonary

hypertension and interstitial lung disease have provide a longer life-expectancy

improving this way 5-year survival, but we finally fail maintaining this effect no longer.

Risk factors have been measured in a recent meta-analysis7 quantifying the

accumulated risk over time. We are very sceptic of their results as they lack in our

opinion of proper methodology. They put together as association measure results

reported as risk ratio, odds ratio and hazard ratio. Results from a Cox regression can be

cited as hazard ratio for time-dependent variables or as risk ratio. Both results are often

the same or approximated. However, odds ratio is a result from a logistic regression and

can’t be measured into the same meta-analysis. Even they assess in a same group

different definitions of organ involvement. It is not the same the ratio for a generic heart

involvement and that for a specific abnormal EKG. We can’t put them together in a

same meta-analysis so therefore the results can’t be evaluated. They also include one

meta-analysis but it is not fair to be measured as one single series. We found this same

problem of heterogeneity of the risk factors definition. It is not correct to include all of

them in a same quantitative meta-analysis in order to avoid selection bias. We decided

to choose main risk factors and just those described as hazard ratio.

As limitations of our study, there is between-study variability so random effects

model was chosen for the assessment of SMR meta-analysis. Several patients from

different studies have been lost of follow-up, but we consider they are just a few,

representing an overall of 2.2% of patients (range 0-10%). Another limitation of the

survival assessment is the great heterogeneity in the definition of onset disease when it

is a non-Raynaud’s first symptom. Although they all have been put together in a same

group, we suggest it is much more reliable to measure survival from diagnosis time as

they are homogeneous studies and more reliable data. Another limitation for the study

of causes of death is the great heterogeneity defining SSc-related causes of death in

the different studies, most of all about cardiovascular causes. It is a fact that

cardiovascular death related with atherosclerosis is sometimes hard to differentiate from

SSc-related. In our study only well-defined cardiovascular SSc-related cause of death

has been included in order to avoid some bias. We suggest it is paramount in the future

to get some homogeneity at the time of defining causes of death, based on objective

and reproducible parameters and not in subjective or clinical impression.

In conclusion, the present study constitutes the largest meta-analysis ever done

to date about mortality and survival in patients with SSc, reporting an overall SMR 2.72

(CI 95% 1.93-3.83) and supporting the evidence of a higher mortality compared with

general population but with a trend of improvement in SMR in the latest decades that

becomes significant excluding one outlier study. Survival is also improving over time, at

5-year follow-up more than 10 or 20-year follow-up. About 47% of all deaths were

related to SSc. Cardiopulmonary involvement represents the leading cause of death in

patients affected by SSc even more in the last two decades, with a decline of renal and

gastrointestinal causes. Lung involvement, skin extension, older age, kidney

involvement, heart involvement, male gender and high eritrosedimentation rate have

been the main risk factors related with poor outcome.

The authors declare no conflict of interests, no source of funding or sponsors or

any relationship with organizations that could potentially influence the present work.

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Figure 1: Flow-chart.

1801 articles searched

102 articles reviewed for full-text

No SSc data: 516

No mortality data: 605

Subgroup data: 284

Trials: 22

Infantile SSc: 32

43 articles included in the survival meta-analysis

Language unknown:8

Meta-analysis:4

17 articles included in the SMR meta-analysis

40 articles included in the causes of death meta-analysis

Figure 2. SMR meta‐analysis Forest plot: Overall SMR (discontinuous points) 2.72 (1.93‐3.83); SMR before 1990 (continuous line) 3.35 (1.57‐7.11); SMR after 1990(discontinuous lines) 2.42 (1.89‐3.11). Meta‐regression between SMR (lnSMR) with mid‐cohort year: Coefficient b – 0.055 p 0.064 and excluding the outlier study (US 1985 by Walsh et al) coefficient b ‐0.064 p 0.02.

Figure 3. SMR meta-analysis for different subsets.

Figure 4. Survival meta‐regression. From first Raynaud: 5‐year survival (Coefficient b 0.308 p 0.402) and 10‐year‐survival (Coefficient b 0.595 p 0.237). From non‐Raynaud’s first symptom: 5‐year survival (Coefficient b 0.612 p 0.113) and 10‐year‐survival (Coefficient b 0.590 p 0.037). From diagnosis: 5‐year survival (Coefficient b 0.595 p <0.001) and 10‐year‐survival (Coefficient b 0.536 p 0.025).

Figure 5. Quantitative meta‐analysis of the main risk factors related with mortality.

Figure 6. Meta‐regression of deaths due to lung involvement over time (coefficient b=0.935 p 0.005), and after removal of 4 outlier studies significance persists (coefficient b=0.604 p 0.05). Meta‐regression of deaths due to kidney involvement over time (coefficient b=‐0.206 p 0.352), and even though we removed 3 outlier studies changes over time don’t achieve significance (coefficient b=‐0.332 p 0.083) but shows a trend.

Study Country

Years

Mid‐cohort year

Lost of follow‐up

QA

Deads

Overall

SMR (95%CI

)

dcSScSMR (95%CI

)

lcSSc SMR (95%CI

)

MaleSMR (95%CI

)

Female

SMR (95%CI

) Zarafonetis10 US 1948

‐80 1964 40/390(10% 7 142 5.40

(4.51‐NA NA NA NA

) 6.29)

Jacobsen11 DEN 1960‐96

1978 0 8 160 2.90(2.50‐3.40)

4.50(3.50‐5.70)

2.30 (1.80‐2.80)

3.70(2.70‐5.10)

2.70(2.30‐3.30)

Abu‐Shakra12 CAN 1976‐90

1983 17/237(7%) 7 61 4.69(3.73‐5.65)

6.18(4.17‐8.81)

3.80 (2.58‐5.39)

4.18(2.09‐7.48)

4.81(3.65‐6.44)

Walsh1 US 1981‐90

1985 0 7 2123 1.05(1.01‐1.1)

NA NA NA NA

Bryan14 UK 1982‐92

1987 0 7 55 4.05(3.03‐5.22)

NA NA 3.22(1.85‐4.97)

4.59(3.22‐6.19)

Hesselstrand15

SWE 1983‐95

1989 0 7 49 4.59(3.48‐6.07)

6.06(4.09‐9.02)

3.72 (2.41‐5‐32)

4.77(3.21‐7.09)

4.44(2.87‐6.34)

Hashimoto16 JAP 1973‐08

1990 9/405(2.2%) 8 86 2.76(2.18‐3.35)

5.90(4.20‐7.61)

1.71 (1.18‐2.24)

3.31(1.15‐5.47)

2.71(2.10‐3.32)

Alamanos17 GRE 1981‐02

1991 2/109(2%) 7 36

2.0(1.2‐2.8)

NA NA NA NA

Scussel‐Lonzetti18

CAN 1984‐99

1991 0 8 66 2.69(2.10‐3.40)

6.17(2.80‐11.70)

2.71 (1.85‐3.80)

1.76(0.80‐3.30)

2.55(1.90‐3.30)

Pérez‐Bocanegra19

SPA 1976‐07

1991 NA 7 73

1.90(1.50‐2.30)

6.50(4.10‐9.80)

1.70 (1.20‐2.20)

1.80(0.80‐3.40)

2.50(1.90‐3.20)

Joven20 SPA 1980‐06

1993 10/204 (4.9%)

9 44 3.10(1.60‐6.10)

NA NA NA NA

Alba21 SPA 1986‐10

1998 0 8 151 3.80(3.18‐4.43)

NA NA NA NA

Hissaria22 AUS 1993‐07

2000 24/786(3%) 7 331

1.46(1.28‐1.69)

2.92(2.20‐3.89)

1.30 (1.11‐1.53)

NA NA

Mok23 CHI 1999‐08

2003 0 8 110 3.94(3.20‐4.68)

NA NA 2.59 (1.32‐3.87)

4.32 (3.45‐520)

Hoffmann‐Vold24

NOR 1999‐09

2004 0 8 43 2.03(1.40‐2.60)

5.33(3.90‐10.30)

1.62 (1.10‐2.50)

2.61(1.40‐3.90)

1.80(1.20‐2.70)

Strickland25 UK 1999‐10

2004 19/223(8.5%)

7 53 1.34(0.95‐1.74)

1.66(0.83‐2.97)

1.27 (0.92‐1.72)

1.54(0.67‐3.04)

1.30(0.95‐1.74)

Kuo26 TAIW 2002‐07

2005 0 8 204 3.24(2.82‐3.71)

NA NA 3.53(2.97‐4.16)

2.92(2.29‐3.66)

Table 1. Studies included in the SMR meta‐analysis. QA: Quality assessment (The Newcastle‐Ottawa Scale). NA: not available. SMR: standardized mortality ratio. dcSSc: diffuse cutaneous Systemic Sclerosis. lcSSc: limited cutaneous Systemic Sclerosis.

Study Country Years (mid‐cohort)

QA (stars)

1‐year survival

5‐year survival

10‐year survival

20‐year survival

From Onset/diagnosis

Tuffanelli8 US 1935‐58(46)

7 NA 70.3% 69% NA Diagnosis

Farmer9 US 1945‐52(48)

7 NA 53% NA NA Diagnosis

Bennet12 UK 1947‐70(58)

6 94% 73% 50% NA Diagnosis

Medsger13 US 1955‐70(62)

7 78% 48% NA NA Diagnosis

Zarafonetis15 US 1948‐80(64)

7 NA 81.4% 69.4% NA Diagnosis

Medsger17 US 1963‐70(66)

7 70% 44% NA NA Diagnosis

Rowell18 UK 1960‐75(67)

6 NA NA 74% NA Onset(first Raynaud)

Barnett19 AUS 1953‐83(68)

8 NA 83.6% 59.3% 27.1% Onset(first Raynaud)

Gouet20 FR 1960‐84(72)

7 88% 62.5% 50.5% NA Diagnosis

Giordano21 ITA 1965‐83(74)

7 NA 72% 32% NA Diagnosis

Altman22 US 1973‐77(75)


Eason23 NZ 1970‐80(75)


Wynn24 US 1970‐80(75)

6 98.4% 68.9% 51.2% 31.7% Diagnosis

Peters‐Golden26 US 1972‐83(77)


Ferri27 ITA 1955‐99(77)

7 NA 83% 69.2% 45.5% Diagnosis

Lally28 US 1972‐84(78)

7 NA 77% NA NA Diagnosis

Jacobsen30 DEN 1960‐96(78)

8 NA 81% 71% 42% Onset(non‐Raynaud’s first symptom)

Kuwana32 JAP 1971‐90(80)

7 NA NA NA NA Diagnosis

Geirsson34 ICE 1975‐90(82)


Kaburaki37 JAP 1976‐91(83)

7 NA 78% 68.2% NA Diagnosis

Nishioka39 JAP 1974‐94(84)

7 NA 93.7% 82% 56.7% Onset(first Raynaud)

Simeón41 SPA 1976‐96(86)

8 NA 71% 64% 62% Onset(first Raynaud)

Bulpitt44 US 1982‐92(87)

8 92% 68% NA NA Onset( non‐Raynaud’s first symptom )

Bryan46 UK 1982‐92(87)

7 NA 87% 75% NA Onset( non‐Raynaud’s first symptom )

Nagy47 HUN 1982‐93(87)

8 NA 82.9% 70.4% NA Onset( non‐Raynaud’s first symptom )

Hesselstrand50

SWE 1983‐95(89)

7 NA NA

92% 86%

78% 69%

NA NA

Onset( non‐Raynaud’s first symptom ) Diagnosis

Kim54 KOR 1972‐07(89)


Mayes55 US 1989‐91(90)

8 NA 77.9% 55.1% 26.8% Diagnosis

Hashimoto56 JAP 1973‐08(90)

8 NA NA 88% 77.4% Onset(first Raynaud)

Pérez‐Bocanegra58

SPA 1976‐07(91)

7 NA 89% 81% 63% Diagnosis

Alamanos59 GRE 1981‐02(91)


Nihtyanova60 UK 1990‐93(91) 2000‐03(01)

8 NA NA

84.2% 89.9%

NA NA

NA NA

Diagnosis Onset( non‐Raynaud’s first

symptom )

Joven61 SPA 1980‐06(93)

9 95% 85% 75% 55% Onset( non‐Raynaud’s first symptom )

Ruangjutipopan62 THAI 1987‐01(94)

6 NA 73% 67.4% NA Onset(no definition)

Czirják63 HUN 1983‐05(94)

7 NA 84% 72.6% NA Diagnosis

Arias‐Núñez65 SPA 1988‐06(97)


Alba67 SPA 1986‐10(98)

8 NA 90.7% NA NA Diagnosis

Al‐Dhaher68 CAN 1994‐04(99)


Sampaio‐Barros69 BRA 1991‐10(00)

7 NA 90% 84% NA Onset(no definition)

Hoffmann‐Vold75 NOR 1999‐09(04)

8 NA 95% 86% NA Onset( non‐Raynaud’s first symptom )

Vettori76 ITA 2000‐08(04)

6 NA 94.8 NA NA Onset (first Raynaud)

Kuo79 TAIW 2002‐07(05)

8 94.9% 83.2% NA NA Diagnosis

Table 2. Cumulative survival from studies. NA: not available. QA: Quality assessment (The Newcastle‐Ottawa Scale).

Survival from onset

(first Raynaud)

Survival from onset

(non‐Raynaud’s first symptom)

Survival from diagnosis

Before 1990

(5 studies)

After 1990

(3 studies)

p

Before 1990

(4 studies)

After 1990

(3 studies)

p

Before 1990

(18 studies)

After 1990

(8 studies) p

Number of patients

840 1693 846 802 4365 3476

1‐year survival % mean (SD)

‐ ‐ ‐ 92 (NA) 95 (NA) ‐ 85.3(9.5) 94.9(NA) 0.384


85.1(10.4) 92.8(2.9) 0.385 79.7 (8.2)

90 (5.0) 0.118 70.6(14.3) 84.4(3.8) 0.001


71.5(9.5) 88(NA) 0.189 72.1 (2.5)

80.5 (7.8) 0.358 58.8(14.8) 70.9(10.1) 0.086


48.6(18.8) 77.4(NA) 0.316 42 (NA) 55 (NA) ‐ 38.6(9.8) 44.9(25.6) 0.790

Table 3. Student’s t for independent groups among studies before and after 1990 (mid‐cohort year). NA: not available (there isn’t confidence interval because just 1 study reported 1‐year survival from diagnosis after 1990). The number of patients don’t add up so several studies don’t report survival data.

Study Country

Years (mid‐cohort)

dcssc/lcssc/icSSc/other

Deads/n

SSc‐related death

Lungdeath

Heart

death

Kidney death

GI death

Cancer

death

Infection death

Athero

Sclerosis death

Farmer2 US 1945‐52(48

)

3%/48.7%/7%/41.3%

115/271(49%)

17(14.8%)

5(29.4%)

6(35.3%)

1(5.9%)

1(5.9%)

6(5.2%)

4(3.5%)

20(17.4%)

Bennet5 UK 1947‐70(58

)

NA 26/67 (38.8%)

1(9.1%)

0 (0%)

1(9.1%)

0 (0%)

0 (0%)

2(18.2%)

3(27.3%)

5(45.5%)

Rowell11 UK 1960‐75(67

)

NA/14.3%/NA/NA 22/84(26.2%)

NA NA NA NA NA 0 (0%)

NA 1(4.5%)

Barnett12 AUS 1953‐83(68

)

14.1%/48.6%/37.3%

86/177(48.6%)

42(48.8%)

8(19%)

10(11.6%)

16(38.1%)

8(9.3%)

NA NA NA

Altman15 US 1973‐77(75

)

24%/NA/NA/NA 131/264(49.6%)

89(68%)

19(21.3%)

19(21.3%)

35(39.3%)

13(14.6%)

9(6.9%)

3(2.3%)

17(13%)

Eason16 NZ 1970‐80(75

)

38.3%/36.2%/NA/25.5%

24/47(51%)

18(75%)

7(38.9%)

4(22.2%)

5(27.8%)

2(11.1%)

2(8.3%)

2(8.3%)

2(8.3%)

Wynn17 US 1970‐80(75

)

NA 25/64(39.1%)

17(68%)

7(41.2%)

6(35.3%)

4(23.5%)

0(0%) 3(12%)

0(0%) 3(12%)

Ferri20 ITA 1955‐99(77

)

17%/56%/27%/0%

279/1012(27.6%)

61(35.9%)

NA NA NA NA 25(14.7%)

NA NA

Lally20 US 1972‐84(78

)

67%/23%/0%/10%

17/91(18.7%)

14(82.4%)

0 (0%)

8(57.1%)

6(42.9%)

0 (0%)

1(5.9%)

2(11.8%)

0 (0%)

Jacobsen23 DEN 1960‐96(78

)

34%/66%/0%/0% 160/344(46.5%)

41 (25.6%

)

13(31.7%)

1(2.4%)

17(41.5%)

9(22%)

30(18.8%)

19(11.9 %)

43/160

Kuwana25 JAP 1971‐90(80

)

25.8%/40.7%/0%/33.5%

51/275(18.5%)

32(62.7%)

23(71.9%)

4(12.5%)

5(15.6%)

0 (0%)

5(9.8%)

1(2%) 5(9.8%)

Geirsson27 ICE 1975‐90(82

)

27.8%/72.2%/0%/0%

5/23(21.7%)

2(40%)

0 (0%)

1(50%)

1(50%)

0 (0%)

1(20%)

0 (0%) 2(40%)

Abu‐Shakra29

CAN 1976‐90(83

)

NA 61/237(25.7%)

44(77.1%)

13(29.5%)

5(11.4%)

5(11.4%)

0(0%) 6(9.8%)

0(0%) NA

Nishioka32 JAP 1974‐94(84

)

33.1%/24.6%/38.1%

90/496 (18.1%)

64(71.1%)

44(68.8%)

31(48.4%)

12(18.8%)

13(20.3%)

21(23.3%)

5(5.6%)

NA

Steen33 US 1972‐96(84

)

45.9%/NA/NA/NA 364/1508(24.1%)

182(50%)

NA NA NA NA 63(17.3%)

32(8.8%)

30(8.2%)

Simeón37 SPA 1976‐96(86

)

28%/72%/0%/0% 12/79(15.2%)

11(91.7%)

4(36.4%)

0(0%) 7(63.6%)

0(0%) 1(8.3%)

0(0%) 0 (0%)

Bulpitt38 US 1982‐92(87

)

NA 15/48(31.3%)

9(60%)

4(44.4%)

1(11.1%)

4(44.4%)

0 (0%)

1(6.7%)

1(6.7%)

0 (0%)

Bryan40 UK 1982‐92(87

)

46%/54%/0%/0% 55/283(19.4%)

34(61.8%)

15(44.1%)

5(14.7%)

5(14.7%)

3(8.8%)

1(1.8%)

4(7.3%)

11(20%)

Geirsson42 SWE 1982‐ 34%/66%/0%/0% 30/100(30 10(33. 5(50 4(40 1(10 0 9(30 6(20%) 3(10

95(88)

%) 3%) %) %) %) (0%) %) %)

Hesselstrand44

SWE 1983‐95(89

)

25%/75%/0%/0% 49/249(19.7%)

15(30.6%)

10(66.7%)

1(6.7%)

1(6.7%)

3(20%)

12(24.5%)

9(18.4%)

9(18.4%)

Bond45 AUS 1983‐96(89

)

22.8%/52%/0%/25.2%

123/123(100%)

43(35%)

13(30.2%)

14(32.6%)

6(14%)

NA 10(8.1%)

6(4.9%)

17(13.8%)

Vlachoyiannopoulos46

GRE 1982‐96(89

)

45%/49%/0%/6% 7/254(2.8%)

6(85.7%)

2(33.3%)

2(33.3%)

2(33.3%)

0 (0%)

0 (0%)

0 (0%) 0 (0%)

Hashimoto5

0 JAP 1973‐

08(90)

32.6%/67.4%/0%/0%

86/405(21.2%)

NA NA NA NA NA 19(22.1%)

14(16.3%)

NA

Scussel‐Lonzetti51

CAN 1984‐99(91

)

9.4%/49.2%/25.2%/16.2%

66/309(21.4%)

35(53%)

6(17.1%)

4(11.4%)

7(20%)

3(8.6%)

13(19.7%)

NA 10(15.2%)

Alamanos53 GRE 1981‐02(91

)

25%/75%/0%/0% 36/109(33%)

23(63.9%)

21(58.3%)

21(58.3%)

2(5.6%)

0(0%) 4(11.1%)

1(0.2%)

6(16.7%)

Joven55 SPA 1980‐06(93

)

31%/59%/0%/10%

44/204(21.6%)

36(82%)

20(55.6%)

8(22.2%)

1(2.8%)

3(8.3%)

3(6.8%)

2(4.5%)

5(11.4%)

Ruangjutipopan56

THAI 1987‐01(94

)

57.2%/42.8%/0%/0%

31/222(26.7%)

18(58.1%)

NA NA NA 0 (0%)

0 (0%)

13(42%)

0 (0%)

Czirják57 HUN 1983‐05(94

)

27.6%/72.4%/0%/0%

93/366(25.4%)

86(92.5%)

30(34.9%)

29(33.7%)

16(18.6%)

8(9.3%)

12(12.9%)

2(2.2%)

NA

Derk58 US 1985‐07(96

)

71.3%/21.8%/0%/6.9%

87/87(100%)

67(77%)

65(97%)

55(82.1%)

2(3%) 0 (0%)

3(4.5%)

4.6% 0 (0%)

Arias‐Núñez59

SPA 1988‐06(97

)

29.5%/70.5%/0%/0%

20/78(25.6%)

11(55%)

10(90.9%)

1(9.1%)

0 (0%)

0 (0%)

1(5%) 3(15%) 2(10%)

Alba61 SPA 1986‐10(98

)

26%/60.1%/0%/13.9%

151/1037(14.6%)

61(78.2%)

NA 13(16.7%)

0(0%) 5(4.1%)

61(78.2%)

18(14.8%)

NA

Al‐Dhaher62 CAN 1994‐04(99

)

37%/63%/0%/0% 42/185(23%)

NA 15(45.5%)

9(27.3%)

9(27.3%)

0 (0%)

NA NA NA

Sampaio‐Barros63

BRA 1991‐10(00

)

31%/56.4%/0%/12.6%

168/947(17.7%)

110(65.5%)

53(48.2%)

27(24.5%)

12(10.9%)

5(4.5%)

8(4.8%)

24(14.3%)

8(4.8%)

Assassi67 US 1998‐08(03

)

57.4%/42.6%/0%/0%

52/250(20.8%)

29(55.8%)

10(34.5%)

4(13.8%)

NA 2 (6.9%)

NA NA NA

Mok68 CHI 1999‐08(03

)

NA 110/449(24.5%)

26(24%)

11(42.3%)

NA 5(19.2%)

2(7.7%)

11(10%)

19(17.3%)

NA

Hoffmann‐Vold69

NOR 1999‐09(04

)

22%/67%/0%/11%

43/312(13.8%)

13(54.2%)

0(0%) 5(20.8%)

6(25%)

2(4.7%)

13(54.2%)

6(14%) 4(9.3%)

Vettori70 ITA 2000‐08(04

)

20.3%/79.7%/0%/0%

20/251(8%)

12(60%)

5(41.7%)

4(33.3%)

1(8.3%)

2(16.7%)

2(10%)

1(5%) 2(10%)

Hachulla71 FR 2002‐06(04

)

27.5%/NA 47/546(8.6%)

24(51.1%)

19(79.2%)

0 (0%)

3(12.5%)

2(8.3%)

8(17%)

4(8.5%)

2(4.3%)

Strickland72 UK 1999‐10(04

)

19.6%/80.4%/0%/0%

53/204(26%)

19(35.9%)

9(47.4%)

4(21.1%)

0(0%) 1(5.3%)

10(18.9%)

13(24.5%)

12(22.6%)

Kuo73 TAIW 2002‐07(05

)

NA 204/1479(13.8%)

57(27.9%)

9(4.4%)

29(0.1%)

14(6.9%)

10(5%)

30(14.7%)

12(5.9%)

29(14.2%)

Table 4. Causes of death. Lung, heart, kidney and GI are deads related to SSc. NA: not available. icSSc: intermediate cutaneous Systemic Sclerosis. Subtypes: we report dcSSc, lcSSc subtypes and a 3rd subtype icSSc when reported. We add a 4th subtype “others” when reported, including sine scleroderma, pre‐scleroderma, overlap and unknown classification.

Before 1990

(22 studies)

After 1990

(18 studies)

p

SSc‐related deaths % (mean and SD) 52.5 (24.7) 56.7 (17.4) 0.544

Lung % (mean and SD) 34.5 (21.3) 57.0 (24.7) 0.008

Heart % (mean and SD) 29.3 (23.8) 28.2 (28.1) 0.905

Kidney % (mean and SD) 26.4 (17.6) 11.7 (7.9) 0.003

GI % (mean and SD) 6.8 (8.7) 6.4 (7.0) 0.881

Table 5. SSc‐related causes of death. Student’s t for independent groups among studies before and after 1990 (mid‐cohort year).

mortality and survival in systemic sclerosis: systematic review and meta-analysis

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