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ALCOHOL ABSTINENCE IN PATIENTS SURVIVING AN EPISODE OF ALCOHOLIC
HEPATITIS: PREDICTION AND IMPACT ON LONG-TERM SURVIVAL
José Altamirano1,§, Hugo López-Pelayo2§, Javier Michelena1, Patricia D. Jones5,
Lluisa Ortega2, Pere Ginès1,3, Juan Caballería1,3, Antoni Gual2, Ramón Bataller4,6*,
Anna Lligoña2*
Institutions:
1) Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona,
Spain. 2) Grup Recerca Addiccions Clinic (GRAC-GRE) Psychiatry Department,
Neurosciences Institute, Hospital Clínic of Barcelona, Red de Trastornos Adictivos
(RTA),Spain. 3) Liver Unit, CIBER de Enfermedades Hepáticas y Digestivas
(CIBERehd), Institució Catalana de Recerca i Estudis Avançats (ICREA), Universitat
de Barcelona, Barcelona, Spain. 4) Division of Gastroenterology and Hepatology.
Departments of Medicine and Nutrition. University of North Carolina at Chapel Hill,
Chapel Hill, NC. 5) Division of Gastroenterology and Hepatology, University of Miami
Miller School of Medicine, Miami, FL. 6) Pittsburgh Liver Research Center, Division of
Gastroenterology, Hepatology and Nutrition, University of Pittsburgh Liver Center,
Pittsburgh, PA
§ Authors share first co-authorship.
* Authors share senior co-authorship.
Corresponding Authors:
Anna Lligoña, MD
Grup de Recerca Addiccions Clinic (GRAC-GRE)
Psychiatry Department, Neurosciences Institute,
Hospital Clínic, Barcelona, Spain
Email: [email protected]
Ramón Bataller, M.D., PhD.
University of Pittsburgh Medical Center (UPMC)
Division of Gastroenterology, Hepatology and Nutrition
Scaife Hall 8th floor, S844A
3550 Terrace St, Pittsburgh, PA 15261
+1(412)3834242
This article has been accepted for publication and undergone full peer review but has not beenthrough the copyediting, typesetting, pagination and proofreading process which may lead todifferences between this version and the Version of Record. Please cite this article asdoi: 10.1002/hep.29338
This article is protected by copyright. All rights reserved.
2
Main Manuscript Word Count: 4133 words
Number of Tables: 6
Number of Figures: 2
Conflict of interest: HLP has received honoraria as speaker from Lundbeck and
Janssen; and meeting grants from Lundbeck, Janssen, Pfizer, Otsuka, Esteve, Rovi
and Lilly. RB has received consulting fees from Echosens and Valyx. None of these
grants have relationship with the current manuscript. Other authors report no conflict
of interest.
Financial support: This work was supported by the National Institute on Alcohol Abuse
and Alcoholism (NIAAA)(1U01AA021908-01). JA wishes to express his gratitude to the
Mexican National Council of Science and Technology (CONACyT, Mexico City,
Mexico) for partially supporting his predoctoral stay at IDIBAPS.
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ABSTRACT :
Alcoholic hepatitis (AH) is the most severe form of alcoholic liver disease. Most studies
have focused on short-term prognosis, while factors associated with long-term survival
are largely unknown. The aims of our study were: 1) to determine the impact of
complete abstinence from alcohol on long-term survival and 2) to identify prognostic
factors at admission capable of predicting abstinence during long-term follow-up in
patients with AH. One hundred and forty-two patients with biopsy-proven AH that
survived the first episode were included. Demographic, psychiatric and biochemical
variables at admission and drinking status during follow-up were obtained. Cox
regression, logistic regression and classification and regression trees (CART) analyses
were used for statistical analysis. Overall mortality was 38% with a median follow-up of
55 months. During follow-up, complete abstinence was reported in 39% and was
associated with better long-term survival (HR 0.53; p=0.03). After adjustment for
baseline prognostic scoring systems (MELD and ABIC scores), complete abstinence
was independently associated with survival (p<0.05). Age and lack of prior alcoholism
treatments were independently associated with complete abstinence (p<0.001 and
p=0.02, respectively) during follow-up. CART analysis generated a simple and practical
algorithm based-on the combination of prior alcoholism treatments and age. Using
CART analysis we stratified 2 subgroups of patients with high (65%) and low (26-29%)
rates of complete abstinence after an episode of AH.
Conclusions: Complete abstinence after an episode of AH positively impacts long-
term survival. The combination of 2 variables easily obtained at admission might be
useful to predict long-term abstinence after an episode of AH. Strategies aimed at
promoting alcohol abstinence in these patients are mandatory.
Keywords: alcoholic liver disease; alcoholic hepatitis; survival; abstinence.
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INTRODUCTION
Alcoholic hepatitis (AH) is a severe clinical entity characterized by acute onset of
jaundice and liver-related complications in patients with severe alcohol use disorder. It
typically occurs in the setting of preexisting liver disease and most patients have
underlying cirrhosis.1 The short-term mortality of AH remains very high globally1-3 and
15-40% of patients die within the first 30 days.4 Short-term prognosis can be predicted
by prognostic models including Maddrey’s discriminant function (DF),5 Model for End-
Stage Liver Disease (MELD),6 Glasgow Alcoholic Hepatitis Score7 and the age-
bilirubin-INR-creatinine (ABIC).8 Moreover, the Lille model9 incorporates response to
prednisolone in determining the risk of death. The medical management of AH has not
evolved substantially in the last two decades. The first line therapy consists of
corticosteroids5,9-11. For patients that do not respond to first line therapy, there are no
effective alternative drugs 12-16. The only approach that improves survival in these
patients is "savage" liver transplantation.17-18 However, many patients with a severe
episode are unlikely to survive the six months of abstinence typically required prior to
consideration for transplant.
The recent STOPAH19 trial only showed a beneficial effect of prednisolone at day 28,
while neither prednisolone nor pentoxifylline was effective after that period. Importantly,
half of the patients died in one year and only one third remained abstinent. This high
rate of recidivism has been confirmed in other studies.20 This seminal study suggests
that alcohol abstinence is only achieved in a minority of patients and that persistent
alcohol intake could influence long-term survival. There are no studies assessing the
predictors of alcohol abstinence in this patient population, and there is limited data on
the influence of alcohol intake on patient outcome. The current study was undertaken
to fill this gap.
Although abstinence from alcohol is routinely recommended after an episode of AH,
there are no studies assessing motivational or pharmacological therapies to promote
abstinence. Similarly, no studies have identified parameters at admission that predict
long-term abstinence. The risks of resuming alcohol use should not be understated. In
one study, a significant proportion of patients with recidivism developed a subsequent
episode of AH that was more severe than the index episode with ≈60% mortality.21
Identification of patients with high risk of recidivism is relevant because it can be used
to select patients for salvage transplantation and to identify those patients needing
more intense alcohol therapy.22-23 However, there are no studies evaluating factors
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associated with long-term abstinence after an episode of AH. We hypothesize that
persistent alcohol use is associated with poorer long-term survival. The aims of our
study were: 1) to determine impact of complete abstinence from alcohol on long-term
survival and 2) to investigate the predicting factors associated with long-term
abstinence in patients with AH.
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PATIENTS AND METHODS
Study Cohort
We included patients admitted to the Liver Unit (Hospital Clínic, Barcelona, Spain) from
1999 to 2012 with biopsy-proven AH included in several prospective studies 2,4,8,24. The
inclusion criteria were presence of heavy drinking (alcohol consumption >60 g/day for
more than 1 year) prior to admission, moderately elevated aminotransferases,
aspartate aminotransferase (AST) levels higher than alanine aminotransferase (ALT),
high gamma-glutamyl transpeptidase (GGT) and abrupt arise in bilirubin serum levels.
In all cases, AH was confirmed histologically by the presence of hepatocellular damage
(hepatocellular ballooning and presence of Mallory bodies), inflammatory infiltrate
(predominantly polymorphonuclear cells) and pericellular fibrosis. Patients with
hepatocellular carcinoma, any other potential cause of liver disease and those who
died during index hospitalization were excluded from the study. In our hospital, the vast
majority of physicians use the ABIC score to stratify patients with severe AH, given that
it was generated in our center and accurately identifies patients with high short-term
mortality Accordingly, severe AH was defined as Maddrey’s discriminant function (DF)
>32 and/or ABIC score >6.71 at admission. All patients with AH received general
support measures and severe cases were treated with 40 mg of prednisone orally
every 24 hours for 4 weeks followed by a taper period of 2 weeks. Treatment was
discontinued in non-responding patients as assessed by Lille score >0.45, according to
the center’s guidelines during the patients’ admission. All patients underwent bacterial
infection screening at admission. During hospitalization, patients with clinical
complications, such as ascites, spontaneous bacterial peritonitis, renal dysfunction,
overt hepatic encephalopathy or gastrointestinal bleeding associated with portal
hypertension, as well as bacterial infections non-related to portal hypertension, were
diagnosed and treated according to international guidelines and the clinical protocol of
the Liver Unit in effect when the patients were admitted. As a part of the protocol for
patients with alcoholic liver disease admitted to our liver unit, a team composed of a
psychiatrist, psychologist, and social worker carefully evaluated patients. After hospital
discharge, patients were referred to the Addiction Unit (AU) and the liver unit of our
center for subsequent evaluation and follow-up. The Ethics Committee of the Hospital
Clinic approved the study and all patients gave written informed consent (CEIC
2011/707).
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Clinical and Psychosocial Evaluations at Admission
The demographic and analytical parameters, assessed within 48 hours from hospital
admission, included: age, gender, serum glucose, creatinine, sodium, bilirubin, AST,
ALT, GGT, albumin, international normalized ratio (INR), leukocyte count, platelet
count, hematocrit and hemoglobin levels. The different AH scoring systems were
calculated based on the laboratory values at admission and or within 48 hours of
admission. For purposes of this study, a psychiatrist from our AU performed a full
interview of every included patient and, when needed to close relatives. This interview
included: psychiatric and social parameters, such as alcohol dependency (DSM IV-
TR), cognitive deficits (Mini Mental State Examination), presence/absence of an
underlying psychiatric disease (DSM IV-TR), tobacco consumption, amount of alcohol
consumption, years of heavy alcohol consumption and previous treatments for
alcoholism. When reports of alcohol consumption variables conflicted, the highest
estimate was used. Diagnosis of alcohol abuse and dependence was made according
to the criteria detailed in the Diagnostic and Statistical Manual of Mental Disorders, IV
Edition. For each patient, alcohol consumption was classified using the High-Risk
Alcoholism Relapse (HRAR) scale. The HRAR scale was originally developed from a
cohort of male US Veterans and includes 3 parameters (duration of heavy drinking,
usual number of daily drinks, and number of prior alcoholism treatment experiences)
empirically evaluated to estimate the risk of alcoholism recidivism.25 The HRAR scale
has recently shown good accuracy to predict harmful drinking in patients undergoing
liver transplantation for alcoholic cirrhosis.25 We adapted the number of drinks to the
amount of alcohol of one standard drink (SD) in Europe (e.g. 1 SD=10 g of pure
ethanol). Each item can be scored 0, 1, or 2 for a total possible score ranging from 0 to
6 (Supplementary Table 1).
Follow-Up and Definitions
After hospital discharge from the index AH episode, patients were referred to the AU
for regular follow-up. Our AU has extensive experience in the psychological and
psychiatric treatments of patients with alcoholic liver disease.26-28 Data about prior
alcohol consumption, consumption of psychotropic drugs, alcohol abstinence, time
since last alcohol consumption and the number of previous alcohol detoxifying
treatments were carefully collected. All collected data from patients was always
compared with reports from with relatives or accompanying persons. In the event
of recidivism, information about the number of standard drinks consumed was
collected. For the purpose of this study, data about long-term abstinence and alcohol
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recidivism were retrospectively collected by: a) telephone survey to the patient and/or
patient’s relatives (See Supplementary Information for Survey) (n=98), b) in-person
interviews (n=15) and/or c) review of clinical records from hospital and primary care
medicine units (n=29). All data recorded from the telephonic interviews were also
contrasted with data from electronic charts of the primary care centers (shared
electronic charts). Data about clinical decompensations after index admission for AH
and liver transplantation during follow-up were also recorded retrospectively. Alcohol
abstinence was evaluated on the basis of patient's self-report, family member
interviews, and/or the presence of alcohol in the urine in those attending the hospital
AU. Alcohol recidivism was defined as any amount of regular alcohol use (consumption
at least once a week) after index hospitalization for AH. Overall survival was calculated
from the date of hospitalization for the initial episode of AH until the date of death or the
date the patient was last known to be alive. Those undergoing LT were censored alive
at the date of transplantation. Current hospital protocols for LT consider only those
patients having >6 months of alcohol abstinence to candidates. None of the patients in
this cohort underwent "salvage liver transplantation".
Statistical Analysis
Continuous variables were described as median (25-75 interquartile range).
Categorical variables were described by means of counts and percentages.
Comparisons between groups were performed using the Student´s t-test or Mann-
Whitney U test, when appropriate. Differences between categorical variables were
assessed by the chi-square test or Fisher´s exact test, when necessary. To investigate
variables with prognostic information for long-term survival and alcohol recidivism,
those that were statistically significant (p<0.05), and those considered clinically
relevant at univariate analyses were entered into multivariate analysis. The p-values for
the univariate tests were not corrected for multiple testing, because those tests were
exploratory. The results of the multivariate logistic regression and Cox regression
analyses (odds ratios -OR- and hazard ratios –HR-, respectively) determined those
variables independently associated with the main outcomes survival and recidivism
(after adjusting for the contributions of other variables). In order to avoid co-linearity,
those variables included in a prognostic score (e.g. ABIC score and MELD score) were
not included separately in the multivariate models. To avoid over-fitting, a pre-defined
ratio of candidate prognostic variables to the number of observed events (eg. deaths or
alcohol recidivism [y/n]) was set at 1:10. In order to evaluate the influence of
abstinence in long-term survival, comparative risk analysis using the Kaplan-Meier
method compared by the log-rank test was performed. The SPSS statistical package
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(SPSS Inc., version 15.0, Chicago, IL.) was used for all analyses. A p-value <0.05 was
required for significance. Finally, to evaluate the interaction of variables independently
associated with alcohol recidivism after an index episode of AH a classification and
regression tree (CART) analysis was performed. We used the CART Pro v6.0 software
(Salford systems, San Diego, CA), based on the original Breinman´s code. See
Supplementary Data for detailed explanation on CART analysis.
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RESULTS
Clinical Characteristics of the Study Cohort
One hundred and sixty two patients comprised the original cohort admitted for AH, with
one hundred forty two patients surviving index hospitalization of AH and finally included
in this study. Study participants were predominantly male (69%) and the median age at
admission was 50 years. Almost one-third of patients (30%) had a psychiatric
comorbidity, predominantly depression, however some patients had anxiety and/or
personality disorders. Median reported daily alcohol intake at time of admission was
100 g/day (25-75 IQR: 80-130 g/day). Most patients were long-time drinkers and 28 out
of 142 (20%) of patients reported over twenty daily alcoholic drinks. From the whole
cohort, 46% patients had previously been diagnosed with liver disease and 81% were
cirrhotic at admission. Patients had severe liver disease on presentation, with a median
MELD of 16, Maddrey DF of 35 and ABIC score of 7.2. As expected, total median
bilirubin was elevated at admission (7 mg/dL), AST was elevated and median AST/ALT
ratio at admission was 2.7. Median platelet count was 120 x 109/L and median INR
1.57. The majority of patients presented with jaundice, hepatomegaly, ascites and
edema. Infection at admission was present in 18% of patients and 30% of patients
developed an infection during the index hospitalization. Fifteen percent of patients
developed acute kidney injury (AKI, according to AKIN criteria2) during admission,
10.6%, and 17% of patients required admission to the intensive care unit. Clinical,
demographic and biochemical data at admission are shown in Supplementary Table 2.
Factors Associated with Long-Term Survival after Index Admission
Overall, median follow-up was 55 months (IQR 17-84 months). At the end of follow up,
62% of the patients were alive (n= 88) and 38% were deceased (n= 54). The specific
cause of death during follow-up was obtained in 95% of the 54 deceased patients.
Main causes of death were liver related causes in 47 patients (80%), non-liver related
in 11 (15%) and unknown in 3 (4%). From liver-unrelated death, 3 patients had an
upper aerodigestive tract cancer, 4 lethal cardiovascular events and 1 perforated
appendicitis. Patients deceased at follow-up were older at baseline, median age of 52
years compared to 48 years in those alive at follow-up (p<0.05). Gender was
associated with survival and of those deceased at follow-up, 80% were men compared
to 62% of those alive at follow-up (p=0.02). Importantly, a higher proportion of those
deceased at follow-up had a long duration of heavy drinking (>11 years)(Table 1)
There were no significant differences in the number of patients with psychiatric
comorbidities or current smokers or cirrhosis when comparing those alive vs. deceased
at follow-up. Importantly, complete abstinence after the index admission was
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associated with better survival. Of those alive at follow-up, 55% had resumed active
drinking, compared to 70% of those deceased at follow-up.
In order to explore those factors associated with long-term survival we conducted
univariate and multivariate Cox survival analyses. In univariate analysis, age (p=0.01),
gender (p=0.02), duration of heavy drinking ≥25 years (p=0.01), INR (p=0.004),
baseline ABIC score (p=0.001), MELD score (p=0.03), and presence of liver
decompensations during follow-up (p<0.001) were associated with poor survival.
Conversely, WBC (p=0.03) and complete abstinence (p=0.03) were associated with
improved long-term survival (Table 2). After adjusting for all variables by univariate
analysis and stratifying by the presence of decompensations during follow-up, 2
multivariate Cox survival models were fitted. On separate multivariate analyses,
baseline ABIC score with complete abstinence, and age along with baseline MELD and
complete abstinence, were independently associated with long-term survival (Table 3).
Finally, we analyzed the subset of patients with a serum bilirubin >4.7 mg/dL at
admission (n=88), confirming that complete abstinence was the main factor influencing
long-term survival (Supplementary Tables 3, 4 and 5).
Impact of Alcohol Abstinence on Long-Term Survival
We next compared the impact of alcohol recidivism on long-term survival. The overall
mortality of patients with alcohol recidivism vs those that remain completely abstinent
was 44% vs. 29% (p=0.06), respectively. The Kaplan-Meier analysis shows that the
presence of alcohol recidivism after an episode of AH negatively influenced long-term
survival (Figure 1). As expected, the median follow-up of patients with alcohol
recidivism was significantly shorter when compared with those completely abstinent
(46 vs 63 months; p=0.008). When analyzing time frames, we did not found significant
differences on survival between abstinent and patients that recidivate at 3, 6 and 12
months of follow-up (p>0.05, for all cases). However, differences in survival became
significant after 18 months of follow-up (p=0.045; Supplementary Figure 1). Finally,
36% of patients with complete abstinence presented at least 1 liver decompensation
requiring admission during follow-up, compared with 58% of patients with alcohol
recidivism (p=0.009, Supplementary Figure 2).
Factors Influencing Long-Term Abstinence after the Index Admission.
Based on our criteria to define recidivism (see Methods), 60% were considered
recidivists during the follow-up. Recidivist patients were younger at admission (47 vs
51 years; p=0.004), reported a higher number of daily drinks (p=0.03) and more prior
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alcoholism treatments before the index hospitalization (p=0.006) (Table 4). Importantly,
patients that achieved complete abstinence during follow-up had a lower median
HRAR scale (2 vs 3 points; p=0.007). However, when comparing the proportion of
patients with HRAR scale >3 points (e.g. high risk for alcohol recidivism) at baseline
between the 2 groups, no significant differences were found (p=0.08). In addition, there
were no significant differences in the proportion of smokers, presence and type of
psychiatric comorbidity and baseline MELD score when comparing abstinent patients
vs. those that reported recidivism. We found a significantly higher baseline ABIC score
among abstinent patients (p=0.009). However, we found that this difference was
related to the inclusion of age as a variable of the ABIC scoring system. Time to
recidivism was available for 120 patients; 62 (52%) recidivated 1 year after the index
episode and 85 (71%) after 24 months.
In order to identify factors associated with long-term abstinence, we next performed
univariate and multivariate logistic regression analyses including variables obtained at
the index hospitalization. In univariate analysis, age (p=0.005), number of daily drinks
≥11 (p=0.02), no prior alcoholism treatments (p=0.007), HRAR scale (p=0.006) and
ABIC score (p=0.01) were associated with complete abstinence during follow-up.
Importantly, when categorizing HRAR scale we did not find any significant association
with long-term abstinence. This last finding likely reflects the lack of associative effect
of one of the parameters included in this scale (e.g. duration of heavy drinking) with
long-term abstinence (Table 5). After including variables significant after univariate
analysis and adjusting for baseline liver function (e.g. baseline ABIC and MELD
scores), 4 multivariate logistic regression models for predict abstinence were fitted. On
multivariate models, only age and lack of prior alcoholism treatments were
independently associated with long-term abstinence (Table 6). We also analyzed the
subset of patients with serum bilirubin >4.7 mg/dL at admission (n=88), confirming the
association of age and lack of previous alcoholism treatments with complete
abstinence (Supplementary Tables 6, 7 and 8).
Finally, in order to evaluate the interactions between the two significant variables and
aiming to generate a more intuitive and practical model for accurate prediction of long-
term abstinence, we fitted a CART model. The generated decision tree discriminated
two sub-populations with different rates of long-term abstinence: a high-rate abstinence
group (65% complete abstinence rate at follow-up) composed by those patients without
history of prior alcoholism treatments and greater than 48 years old at baseline and a
low-rate abstinence group (26-29% complete abstinence rate at complete follow-up)
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composed by those with prior alcoholism treatments and those without prior alcoholism
treatments but 48 years old or less (Figure 2). This CART model showed good
usefulness estimated by an AUROC of 0.71.
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DISCUSSION
Most clinical and translational research on AH focuses on short-term prognosis,
while studies assessing the main determinants of long-term prognosis are scarce.
Based on our clinical experience, we hypothesized that the alcohol drinking status
heavily determines the long-term outcome of patients surviving an episode of AH. We
followed-up a cohort of well characterized biopsy-proven cohort of patients with AH for
4.6 years. We confirmed that the main parameter influencing mortality in the long term
was resuming alcohol consumption. Interestingly, we found that alcohol recidivism after
the index episode of AH strongly predicted survival. Whether the pattern of drinking or
occasional drinking (i.e. “slips”) also influence survival was not assessed in our study
and deserves further investigation. Likewise, the prognostic value of previous
admissions to hospitalization and parameters at discharge have not been assessed in
this study. Other scoring systems such as the alcoholic hepatitis histological score or
the presence of systemic inflammatory response syndrome predicted short-term
survival in our series of patients with AH4,24, but not alcohol relapse or long-term
survival, indicating that parameters from the index hospitalization other than age, do
not play a role in the long-term outcome of patients surviving an episode of AH. Larger
studies should investigate if genetic factors or ethnicity (given that 95% of our cohort
was Caucasian) influence the deleterious effects of alcohol intake on long-term
outcome.
Our results strongly indicate that maneuvers aimed at promoting alcohol
abstinence should be initiated as early as possible in patients hospitalized with AH.
Ideally, multidisciplinary teams including addiction therapists should contribute in the
integral treatment of these patients. According to previous research, alcohol recidivism
prevention in patients with cirrhosis caused by ALD depends on multidisciplinary
collaboration including psychological treatment based on Cognitive-Behavior Therapy
(CBT), Motivational Enhancement Therapy (MET), Comprehensive Medical Care
(CMC) and pharmacological treatments. 29-32 In addition, a recent open-label study
using baclofen (a GABA receptor agonist) seems promising in the prevention of alcohol
recidivism of patients with AH 33. Other psychological treatments (e.g. CBT, MET, CMC
or their combination) have not been prospectively evaluated for abstinence
maintenance in the treatment of patients with AH.
Besides determining the key role for alcohol consumption in the outcome of these
patients, our study attempted to identify factors that predict alcohol recidivism. In our
center, addiction specialists assess all patients during the index hospitalization as part
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of the clinical protocol. We routinely collect data on the type and amount of alcohol
consumption and previous detoxification attempts. These parameters are included in
the HRAR score, which was initially designed to predict the recidivism in patients
undergoing a liver transplantation. We have also data on smoking status and use of
illicit drugs, however employment status and other psychosocial variables were not
collected. Interestingly, we found that neither the amount of daily consumption nor the
duration of alcohol intake, current smoking status and use of illicit drugs predicted
recidivism in patients that survive an episode of AH. This can be partially explained
because all these patients were heavy drinkers (defined as > 60 g / day) constituting a
homogeneous sample with only slight differences in daily amount of alcohol intake
(IQR 80-130 and < 20% taking > 20 SDU) which do not allow predict any change in the
recidivism risk in this population. In contrast, age and previous detoxification attempts
heavily predicted alcohol recidivism. By combining these two parameters we were able
to build a simple algorithm to identify patients with high and low risk of recidivism. In
this study we found that age greater than 48 years was associated with higher rate of
abstinence, which goes in line with previous literature. In previous studies, age has
been inversely associated with lower response to alcohol treatment because of lack of
adherence, and was also inversely associated with more relapse in alcohol use
disorders (AUD)34. The reason for this might be the presence of higher craving in
younger people. In fact, there are studies demonstrating that some anticraving drugs
such as ondansertron were successfully tested in adolescents and adults with early-
onset of AUD, being ineffective in adults with late-onset AUD35-36. In this context, it
seems that two types of alcoholism exist according to age, and craving plays a role as
mediator. Finally, age at onset is an essential element to differentiate two types of
alcoholism according to the classical classification of Cloninger37. However, a
physiological explanation of increased craving in young alcohol dependants is still
lacking; further prospective studies in patients with AH, taking into account craving,
tools for craving assessment, and other psychological phenomena, are required.
With regards to the importance of previous AUD treatments, our algorithm shows
that those patients with previous AUD treatments had a higher risk for long-term
alcohol recidivism. Previous literature has shown that the probability of success of any
given treatment decreases with each previous failures38. This means that the patient’s
expectancy to achieve treatment goals decreases as the number of treatments
increases, suggesting an altered role in self-efficacy39-40.
Of note, our study was done in the Barcelona area and it is well know that
alcohol consumption varies among different geographical areas and is influenced by
socioeconomic and cultural factors. Traditionally, two cultural patterns have been
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proposed: 1) that based on binge drinking (e.g UK or Ireland with > 30% prevalence of
heavy episodic drinkers among drinkers vs <20% in Sourthern countries such us Spain
or Italy) and 2) the regular drinking pattern (mainly seen in Southern Europe). Although
these patterns are quickly evolving due to globalization, our predicting algorithm should
be externally validated in these two populations.
This study has important clinical and research implications. First, it highlights
the crucial role of alcohol consumption in the long-term prognosis of this disease.
Specialized liver centers should prioritize early interventions and close follow-up of
these patients to assist in the alcohol use disorder. Second, it suggests that any clinical
trial assessing the impact of medications on long-term survival after an episode of
alcoholic hepatitis should take into account the presence/absence of alcohol
consumption. This is important since medications aimed at improving liver function
could also affect alcohol behavior. This is a topic of recent interest in the field of alcohol
addiction since experimental and human data suggest that systemic inflammation
could play a role in alcohol use disorder (both in the etiology and prognosis)41-42.
Whether this link is present in patients with AH deserves future translational studies.
Finally, the identification of those with higher risk of recidivism might allow for testing
and implementation of specific pharmacological strategies to promote abstinence
during the follow-up of these patients.
In conclusion, the current study investigates the main determinants of long-term
prognosis in patients with biopsy-proven AH. We found that continued alcohol
consumption is associated with a poorer long-term survival after an episode of AH,
which has important implications in the management of these patients. Moreover, we
developed a simple algorithm capable of identifying patients with low and high risk of
alcohol recidivism. Future prospective studies including patients with more severe AH
should validate this system and, most importantly, test pharmacological and
psychological interventions to promote alcohol abstinence among these patients.
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FIGURE LEGENDS
FIGURE 1. Impact of Complete Alcohol Abstinence on Long-term Survival of
Patients that Survive an Episode of Alcoholic Hepatitis.
The Kaplan-Meier analysis shows that the presence of alcohol recidivism after an
episode of AH negatively influenced long-term survival
FIGURE 2. Prognostic Algorithm for Complete Abstinence Prediction on Long-
term Follow-up of Patients that Survived an Episode of AH.
The CART analysis discriminated two sub-populations: 1) a high-rate abstinence group
(65% complete abstinence rate at complete follow-up) including those patients without
prior alcoholism treatments and older than 48 years old and 2) a low-rate abstinence
group (26-29% complete abstinence rate at complete follow-up) composed by those
with prior alcoholism treatments and those without prior alcoholism treatments but
younger than 48 years old.
Page 17 of 43
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18
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Table 1. Baseline Characteristics of Patients with Alcoholic Hepatitis, Stratified by Outcome after
Index Hospitalization (n=142).
Variable Alive
n=88
Deceased
n=54 p value
Clinical and epidemiological variables
Age (years) 48 (40-53) 52 (47-57) 0.014
Gender (male) 62.5 (55) 79.6 (43) 0.032
Alcohol intake at admission (grams/day) 100 (80-130) 100 (80-130) 0.476
Duration of heavy drinking
≤11 years
12-24 years
≥25 years
19.3 (17)
64.8 (57)
15.9 (14)
3.7 (2)
70.4 (38)
25.9 (14)
0.019
Active smoking 67.0 (59) 74.1 (40) 0.442
Psychiatric comorbidity 27.3 (24) 33.3 (18) 0.486
Cirrhosis 78.4 (69) 85.2 (46) 0.318
Follow-up (months) 66 (46-99) 14 (6-50) <0.001
Biochemical variables at admission
Hemoglobin (g/dL) 11.2 (8.9-12.3) 11.1 (9.7-12.6) 0.552
WBC (x109/L) 8.7 (6.4-13.2) 7.8 (5.0-12.5) 0.091
Platelets (x109/L) 136 (86-213) 103 (56-167) 0.156
Creatinine (mg/dL) 0.8 (0.6-1.0) 0.8 (0.7-1.0) 0.520
Bilirubin (mg/dL) 6.6 (2.6-13.6) 8.8 (4.1-16.5) 0.384
AST (IU/L) 119 (78-172) 138 (92-202) 0.771
ALT (IU/L) 41 (31-57) 52 (36-73) 0.457
GGT (IU/L) 379 (149-799) 394 (166-655) 0.615
Albumin (g/L) 27 (23-30) 26 (23.5-31) 0.765
INR 1.56 (1.33-1.74) 1.63 (1.43-1.90) 0.180
Sodium (mEq/L) 134 (130-137) 134 (131-137) 0.561
Scoring systems
Baseline ABIC 7.02(5.94-8.04) 7.48 (6.85-8.48) 0.014
Baseline MELD 14.4 (9.8-20.9) 17.5 (13.5-22.1) 0.122 Data shown as median(interquartile range) or %(n). WBC, white blood cell; AST, aspartate aminotransferase; ALT, alanine
aminotransferase; GGT, gamma glutamyl transpeptidase; INR, international normalized ratio; ABIC, age, serum bilirubin,
INR and serium creatinine score; MELD, model for end-stage liver disease score. Psychiatric comorbidity defined as the
presence of at least one of the following: depressive syndrome, anxiety disorder, bipolar disorder, type A or B cluster
personality disorder.
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Table 2. Univariate Analysis of Variables Associated with Survival after Index Hospitalization in
Patients with Alcoholic Hepatitis.
Variable HR 95% CI p value
Clinical and epidemiological variables
Age (years) 1.04 1.00 – 1.10 0.014
Gender (male) 2.13 1.10 – 4.16 0.026
Alcohol intake at admission (grams/day) 1.00 0.99 – 1.00 0.716
Duration of heavy drinking
≤11 years
12-24 years
≥25 years
Ref
3.94
6.03
-
0.95 – 16.32
1.36 – 26.62
-
0.059
0.018
Active smoking 1.37 0.75 – 2.51 0.310
Psychiatric comorbidity 1.12 0.64 – 1.96 0.701
Cirrhosis 0.97 0.75 – 1.26 0.820
Biochemical variables at admission
Hemoglobin (g/dL) 1.02 0.92 – 1.14 0.679
WBC (x109/L) 0.94 0.88 – 1.00 0.036
Platelets (x109/L) 0.99 0.99 – 1.00 0.134
Creatinine (mg/dL) 0.99 0.73 – 1.34 0.926
Bilirubin (mg/dL) 1.02 0.99 – 1.04 0.193
AST (IU/L) 1.00 0.99 – 1.00 0.822
ALT (IU/L) 1.00 0.99 – 1.01 0.547
GGT (IU/L) 1.00 1.00 – 1.00 0.598
Albumin (g/L) 0.99 0.94 – 1.04 0.712
INR 1.39 1.11 – 1.75 0.004
Sodium (mEq/L) 0.99 0.94 – 1.04 0.682
Scoring systems at admission
Baseline ABIC 1.34 1.13 – 1.58 0.001
Baseline MELD 1.03 1.00 – 1.07 0.031
Follow-up variables
Decompensations during follow-up 4.45 2.34 – 8.49 <0.001
Complete abstinence during follow-up 0.53 0.29 – 0.95 0.034
HR, hazard ratio; 95% CI, 95% confidence interval; WBC, white blood cell; AST, aspartate aminotransferase; ALT, alanine
aminotransferase; GGT, gamma glutamyl transpeptidase; INR, international normalized ratio; ABIC, age, serum bilirubin,
INR and serium creatinine score; MELD, model for end-stage liver disease score. Psychiatric comorbidity defined as the
presence of at least one of the following: depressive syndrome, anxiety disorder, bipolar disorder, type A or B cluster
personality disorder.
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Table 3. Multivariate Cox Regression Analyses of Variables Associated with Survival after Index
Hospitalization in Patients with Alcoholic Hepatitis.
Model #1 Multivariate Cox regression analysis
HR (95% CI) p value
Baseline ABIC 1.35 (1.14 – 1.59) <0.001
Complete abstinence during follow-up 0.51 (0.27 – 0.96) 0.038
Model #2 Multivariate Cox regression analysis
HR (95% CI) p value
Age (years) 1.06 (1.02 – 1.09) 0.002
Baseline MELD 1.04 (1.01 – 1.07) 0.015
Complete abstinence during follow-up 0.43 (0.22 – 0.82) 0.011
HR, hazard ratio; 95% CI, 95% confidence interval. ABIC, age, serum bilirubin, INR and serum
creatinine score.
Variables included in Model #1 were high-risk alcoholism relapse scale, ABIC at admission,
abstinence during follow-up, gender and white blood cell count. Variables included in Model #2 were
high-risk alcoholism relapse scale, MELD at admission, age, abstinence during follow-up, gender and
white blood cell count. Analysis was stratified by the presence of decompensations during follow-up
for both models.
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Table 4. Baseline Characteristics of Patients with Alcoholic Hepatitis, Stratified by Abstinence
during Follow-up (n=142).
Variable Complete Abstinence
n=56
Alcohol Recidivism
n=86 p value
Clinical, epidemiological and psychiatric variables
Age (years) 51 (47 – 56) 47 (41 – 54) 0.004
Male gender 66.1 (37) 70.9 (61) 0.541
Follow-up (months) 63 (37-104) 46 (14-71) 0.008
Duration of heavy drinking
≤11 years
12-24 years
≥25 years
16.1 (9)
66.1 (37)
17.9 (19)
11.6 (10)
67.4 (58)
20.9 (18)
0.446
Number of daily drinks
≤11
12-19
≥20
39.3 (22)
44.6 (25)
16.1 (9)
20.9 (18)
57 (49)
22.1 (19)
0.039
Prior alcoholism treatments
0
1
>1
73.2 (41)
19.6 (11)
7.1 (4)
50 (43)
31.4 (27)
18.6 (16)
0.006
HRAR 2 (1 - 3) 3 (2 - 4) 0.007
HRAR
0-2
3-4
5-6
62.5 (35)
32.1 (18)
5.4 (3)
46.5 (40)
41.9 (36)
11.6 (10)
0.049
HRAR (>3 points) 9 (16) 26 (30) 0.08
Active smoking 66.1 (37) 72.1 (62) 0.445
Psychiatric comorbidity 30.4 (17) 30.2 (26) 0.987
Type of psychiatric comorbidity (n=43)
Anxiety and depression
Personality disorders
82.4 (14)
17.6 (3)
73.1 (19)
26.9 (7)
0.714
0.714
Biochemical variables at admission
Haemoglobin (g/dL) 11.2(9.2-12.8) 11.2(9.1-12.4) 0.214
WBC (x109/L) 8.7(6.4-13.2) 8.4(6.1-12.8) 0.687
Platelets (x109/L) 134(84-204) 115(69-181) 0.528
Creatinine (mg/dL) 0.80(0.62-1.00) 0.80(0.60-0.96) 0.991
Bilirubin (mg/dL) 8.0(3.1-15.0) 6.1(3.0-10.9) 0.161
AST (IU/L) 117(82-175) 132(85-195) 0.359
ALT (IU/L) 45(32-57) 46(33-67) 0.259
GGT (IU/L) 376(147-671) 432(162-834) 0.253
Albumin (g/L) 26(24-30) 27(23-31) 0.800
INR 1.59(1.41-1.89) 1.57(1.35-1.80) 0.897
Sodium (mEq/L) 134(130-137) 135(131-137) 0.882
Scoring systems at admission
Baseline ABIC 7.69 (6.76 – 8.74) 7.03 (6.09 – 7.81) 0.009
Baseline MELD 17.87 (12.53 – 22.28) 15.38 (10.35 – 20.77) 0.450 Data shown as median(interquartile range) or %(n). 1 daily drink = 10 grams of alcohol. Alcoholism treatments refer to any outpatient or inpatient
treatment for alcoholism. HRAR, high-risk alcoholism relapse scale; ABIC, age, serum bilirubin, INR and serium creatinine score; MELD, model
for end-stage liver disease score. Psychiatric comorbidity defined as the presence of at least one of the following: depressive syndrome, anxiety
disorder, bipolar disorder, type A or B cluster personality disorder.
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Table 5. Univariate Logistic Regression Analysis of Variables Associated with Alcohol Recidivism
in Patients with Alcoholic Hepatitis.
Variable OR 95% CI p value
Clinical, epidemiological and psychiatric variables
Age (years) 0.94 0.90 – 0.98 0.005
Male gender 1.25 0.61 – 2.58 0.541
Duration of heavy drinking
≤11 years
12-24 years
≥25 years
Ref
1.41
1.62
-
0.52 – 3.80
0.49 – 5.31
-
0.496
0.426
Number of daily drinks
≤11
12-19
≥20
Ref
2.40
2.58
-
1.09 – 5.27
0.94 – 7.07
-
0.030
0.065
Number of daily drinks (≥11 daily drinks) 2.44 1.16 – 5.16 0.019
Prior alcoholism treatments
0
1
>1
Ref
2.34
3.81
-
1.03 – 5.32
1.18 – 12.37
-
0.042
0.026
Prior alcoholism treatments (≥ 1 treatment) 2.73 1.32 – 5.66 0.007
HRAR (points) 1.46 1.12 – 1.91 0.006
HRAR (points)
0-2
3-4
5-6
Ref
1.75
2.92
-
0.85 – 3.61
0.74 – 11.45
-
0.130
0.125
Modified HRAR (>3 points) 2.26 0.97 – 5.29 0.06
Active smoking 1.33 0.64 – 2.74 0.446
Psychiatric comorbidity 1.08 0.52 – 2.27 0.832
Scoring systems at admission
Baseline ABIC 0.72 0.56 – 0.93 0.013
Baseline MELD 0.99 0.95 – 1.03 0.449 OR, odds ratio; CI, confidence interval. 1 daily drink = 10 grams of alcohol. Alcoholism treatments refer to any outpatient or
inpatient treatment for alcoholism. HRAR, high-risk alcoholism relapse scale; ABIC, age, serum bilirubin, INR and serium
creatinine score; MELD, model for end-stage liver disease score. Psychiatric comorbidity defined as the presence of at least
one of the following: depressive syndrome, anxiety disorder, bipolar disorder, type A or B cluster personality disorder.
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Table 6. Multivariate Logistic Regression Analyses of Variables Associated with Alcohol
Recidivism in Patients with Alcoholic Hepatitis.
Model #1 Multivariate logistic regression analysis
OR (95% CI) p value
Baseline ABIC 0.71 (0.54 – 0.94) 0.015
Number of daily drinks
≤11
12-19
≥20
-
1.97 (0.86 – 4.52)
1.59 (0.53 – 4.75)
0.275
0.108
0.404
Number of prior alcohol treatments
0
1
>1
-
2.23 (0.93 – 5.32)
3.90 (1.14 – 13.37)
0.038
0.072
0.030
Model #2 Multivariate logistic regression analysis
OR (95% CI) p value
Baseline ABIC 0.72 (0.55 – 0.95) 0.019
Number of daily drinks (≥11 daily drinks) 1.89 (0.86 – 4.17) 0.114
Number of prior alcohol treatments (≥ 1
treatment) 2.59 (1.21 – 5.57) 0.015
Model #3 Multivariate logistic regression analysis
OR (95% CI) p value
Baseline MELD 0.98 (0.93 – 1.02) 0.257
Age (years) 0.94 (0.90 – 0.98) 0.008
Number of daily drinks
≤11
12-19
≥20
-
1.99 (0.87 – 4.59)
1.75 (0.58 – 5.30)
0.263
0.105
0.322
Number of prior alcohol treatments
0
1
>1
-
2.20 (0.91 – 5.30)
3.61 (1.04 – 12.52)
0.054
0.079
0.043
Model #4 Multivariate logistic regression analysis
OR (95% CI) p value
Baseline MELD 0.97 (0.94 – 1.02) 0.293
Age (years) 0.94 (0.90 – 0.99) 0.008
Number of daily drinks (≥11 daily drinks) 1.95 (0.88 – 4.33) 0.101
Number of prior alcohol treatments (≥ 1
treatment) 2.51 (1.16 – 5.47) 0.020
Model #1 AUROC: 0.71 (95% CI 0.63 – 0.80); Model #2 AUROC: 0.71 (95% CI 0.63 – 0.80); Model #3
AUROC: 0.71 (95% CI 0.62 – 0.80); Model #4 AUROC: 0.72 (95% CI 0.63 – 0.81).
OR, odds ratio; 95% CI, 95% confidence interval; AUROC, area under the receiving operator characteristics
curve.
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254x190mm (300 x 300 DPI)
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254x190mm (300 x 300 DPI)
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