Systematic review with meta-analysis: coffee consumption and
the risk of cirrhosis
O. J. Kennedy*, P. Roderick*, R. Buchanan*, J. A. Fallowﬁeld†
, P. C. Hayes†
& J. Parkes*
*Primary Care & Population Sciences,
Faculty of Medicine, University of
Southampton, Southampton, UK.
†
MRC Centre for Inﬂammation
Research, University of Edinburgh,
Edinburgh, UK.
Correspondence to:
Dr. O. J. Kennedy, Primary Care &
Population Sciences, Faculty of
Medicine, University of Southampton,
Southampton, UK.
E-mail: ok4g13@soton.ac.uk
Publication data
Submitted 27 October 2015
First decision 10 November 2015
Resubmitted 3 December 2015
Resubmitted 17 December 2015
Accepted 20 December 2015
EV Pub Online 25 January 2016
As part of AP&T’s peer-review process, a
technical check of this meta-analysis
was performed by Dr Y. Yuan. This
article was accepted for publication after
full peer-review.
SUMMARY
Background
Liver cirrhosis is a large burden on global health, causing over one million
deaths per year. Observational studies have reported an inverse association
between coffee and cirrhosis.
Aims
To perform a systematic review and meta-analysis to characterise the relationship
between coffee consumption and cirrhosis.
Methods
We searched for studies published until July 2015 that reported odds ratios,
relative risks (RR) or hazard ratios for cirrhosis stratiﬁed by coffee consumption.
We calculated RRs of cirrhosis for an increase in daily coffee
consumption of two cups for each study and overall. We performed analyses
by study design, type of cirrhosis and mortality. We assessed the risk of
bias in each study and the overall quality of evidence for the effect of coffee
on cirrhosis.
Results
We identiﬁed ﬁve cohort studies and four case–control studies involving
1990 cases and 432 133 participants. We observed a dose–response in most
studies and overall. The pooled RR of cirrhosis for a daily increase in coffee
consumption of two cups was 0.56 (95% CI 0.44–0.68; I2
83.3%). The RR
pooled from cohort studies for a daily increase of two cups was 0.58 (95%
CI 0.41–0.76; I2
91.1%) and from case–control studies it was 0.52 (95% CI
0.40–0.63; I2
0.0%). The pooled RR of alcoholic cirrhosis for a daily
increase of two cups was 0.62 (95% CI 0.51–0.73; I2
0%) and of death from
cirrhosis it was 0.55 (95% CI 0.35–0.74; I2
90.3%).
Conclusion
This meta-analysis suggests that increasing coffee consumption may substantially
reduce the risk of cirrhosis.
Aliment Pharmacol Ther 2016; 43: 562–574
ª 2016 John Wiley & Sons Ltd
doi:10.1111/apt.13523
562
Alimentary Pharmacology and Therapeutics
INTRODUCTION
Liver cirrhosis is a signiﬁcant burden on global health.
Between 1980 and 2010, the number of deaths worldwide
from cirrhosis increased from around 676 000
(1.54% of total) to over one million (1.95% of total).1
Cirrhosis is also an important cause of disability and
morbidity, and in 2010 was responsible for 31 million
disability-adjusted life years (1.2% of the total).
Although the absolute number of deaths from cirrhosis
has increased, the global age-adjusted mortality rate
decreased by 22% between 1980 and 2010. Trends in
mortality rates vary markedly between countries, however,
due to varying exposure to risk factors and the
availability of vaccinations and treatments. In some
countries, such as India and the UK, mortality rates
are increasing.1
The risk factors and aetiologies of cirrhosis
are diverse, but those traditionally considered as
important include alcohol-related liver disease and
chronic viral hepatitis. More recently, and as a result
of increases in obesity and diabetes mellitus, non-alcoholic
fatty liver disease (NAFLD) has also emerged as
a signiﬁcant aetiological factor.2, 3
Irrespective of aetiology,
cirrhosis develops by a common mechanistic
pathway involving chronic inﬂammation of the liver,
followed by ﬁbrosis, leading to end-stage liver disease
(cirrhosis), which can be fatal either due to complications
related to portal hypertension (decompensation)
or to hepatocellular carcinoma (HCC).
Coffee is ubiquitous in most societies. Coffee comprises
over a thousand compounds, many of which are
biologically active and may affect human health. These
include caffeine, chlorogenic acid, melanoids and the
pentacyclic diterpenes, kahweol and cafestol.4
The biological
effects of coffee include stimulation of the central
nervous system, primarily by caffeine, the
attenuation of oxidative stress and inﬂammation, and
anti-carcinogenesis.5
Due to its widespread consumption,
coffee and its effects on health have been studied
extensively. In the context of liver disease, coffee
appears to confer a number of protective effects. Animal
studies and human observational studies suggest
that coffee consumption reduces the frequency of
abnormal liver function tests, ﬁbrosis, cirrhosis and
HCC.6–10
In addition, a randomised-controlled trial
(RCT) showed that patients with hepatitis C who
drank more coffee had lower serum levels of liver
enzymes.11
The aim of this meta-analysis was to summarise
the evidence from studies on the effect of coffee
on cirrhosis.
METHODS
We followed the Prisma guidelines; a protocol is shown
in Table S1.
Study searches and selection
We searched for titles of articles in PubMed, Embase
(using Ovid) and Web of Science using the term: (coffee
OR caffeine) AND (*liver* OR *hepat* OR *cirrh* OR
*ﬁbro*). We performed the search in July 2015 and did
not restrict publication date. We also performed manual
searches of reference lists of relevant studies returned by
the initial search.
We included studies in this meta-analysis if they: (i)
involved a case–control study, cohort study or RCT; and
(ii) provided relative risks (RRs), odds ratios (ORs) or
hazard ratios (HRs), including 95% conﬁdence intervals
(95% CIs), for cirrhosis stratiﬁed by coffee consumption
in adults aged 18 or older. We excluded studies if they
did not provide a summary dose–effect size or allow one
to be calculated, which required individual effect sizes
for three or more consumption categories. We also
excluded studies if they were not in English. We
assumed a diagnosis of cirrhosis where studies reported
hospitalisation for chronic liver disease (CLD) or death
from CLD but without a diagnosis of HCC. If two or
more studies reported the same data, we used the most
recent study. OJK screened titles and abstracts to remove
duplicates. OJK and RB independently reviewed the
remaining studies.
Data extraction and quality assessment
The data extraction was performed by OJK and checked
by RB. The following data were extracted from each
study in a standardised manner: (i) the publication date,
the ﬁrst author’s surname and the country of origin; (ii)
the study characteristics, including the design, the inclusion
and exclusion criteria, the sample size, the measurement
of coffee consumption, the outcome measures, and
the adjustments for confounding variables and (iii) the
number of events (or cases) and non-events (or controls)
and the corresponding effect size and 95% CIs for different
categories of coffee consumption. For cohorts, we
also extracted information concerning whether CLD was
excluded at baseline, the follow-up time and the loss to
follow-up. Where studies provided multiple effect sizes
for a single category of coffee consumption, we extracted
the effect size most comprehensively adjusted for confounders.
Where studies reported effect sizes for caffeinated
and decaffeinated coffee consumption separately,
Aliment Pharmacol Ther 2016; 43: 562–574 563
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Systematic review with meta-analysis: coffee and risk of cirrhosis
but not total coffee consumption, we extracted the effect
sizes for caffeinated coffee. The case–control studies
reported ORs, while the cohort studies reported either
RRs 9, 12, 13
or HRs.8, 14
As the incidence rate of cirrhosis
was low, we assumed the ORs, RRs, HRs were equivalent,
and from herein we refer to all three as RR for
simplicity. We worked form published data only and
without contacting study authors.
We assessed the risk of bias in individual studies using
the Cochrane Risk Of Bias Assessment Tool: for NonRandomized
Studies of Interventions (ACROBAT-
NRSI),15
as has been used previously.16
We included the
following domains of bias: confounding, selection, measurement
of exposure at baseline, changing exposure
during follow-up, missing data (including loss to followup),
outcome measurement and selective reporting. In
accordance with the Cochrane tool, we judged each
domain of bias as ‘low’, ‘high’ or ‘unknown’ risk. We
made a single judgement for the risk of bias from ‘measurement
of exposure’, which combined the domains
‘measurement of exposure at baseline’ and ‘changing
exposure during follow-up’. We made an overall judgement
of the risk of bias for each study. We judged there
to be a ‘high’ overall risk of bias where there was plausibility
that individual domain bias would lead to bias in
the reported effect estimates. We determined the overall
quality of evidence supporting the effect of coffee on cirrhosis
using the Grading of Recommendations Assessment,
Development and Evaluation (GRADE).17
OJK
and PJR performed the risk of bias analysis and overall
quality of evidence assessment separately and then discussed
the results for consensus.
Statistical analysis
Eight studies reported RRs and 95% CIs for cirrhosis.
The other, Klatsky et al., reported RRs and 95% CIs for
alcoholic and non-alcoholic cirrhosis separately, but not
total cirrhosis. For this study, we calculated a RR and
95% CI for total cirrhosis using the method described by
Hamling et al.18
We consider the RRs as reported in the different studies
below. However, because the reported categories of
coffee consumption varied between the studies, a direct
comparison was not initially possible. Thus, we calculated
for each study a summary RR and 95% CI for an
increase in coffee consumption of two cups per day. For
each study, this involved estimating the median coffee
consumption in each of the reported categories. Where
the consumption category was an integer (e.g. one cup
per day), we used the integer as the median. Where the
category was a closed range, (e.g. one to three cups per
day), we used the mid-point as the median. For the
highest ranges, which were open-ended (e.g. >two cups
per day), we used the lower end of the range plus the
width of the preceding closed range for the median. If
there was no preceding closed range, we used the lower
end of the open-ended range plus the difference between
the two preceding integers. This method was similar to
those used for estimating median exposure in ranges in
other meta-analyses.19, 20
After calculating median consumptions,
we performed a summary dose–response
analysis following the method of Greenland and Long-
necker.21
We tested for nonlinearity of the dose–response
across the range of consumption reported in the studies
(from 0 to four and above cups per day) using a
restricted cubic spline model.22
This used data from
eight studies that provided RRs for different categories of
coffee consumption (Tverdal and Skurtveit did not
report category-speciﬁc RRs). The P-value for nonlinearity
was 0.34. We also used the cubic spline model to calculate
RRs of cirrhosis for one to four cups per day
compared to none.
Using the RRs and 95% CIs for an increase of two
cups of coffee per day, we calculated a pooled RR and
95% CI of cirrhosis. We used a random effects model to
incorporate between study heterogeneity, assuming the
biological effects of coffee in different populations would
vary randomly, at least by type, processing and measurement
of coffee.23
We examined statistical heterogeneity
by performing Cochran’s Q and I2
tests. In accordance
with the Cochrane Handbook,24
Chapter 9.5.2, we used a
P-value of <0.1 to signify statistically signiﬁcant heterogeneity
and we interpreted the I2
values as follows: ‘0–
40% heterogeneity might not be important; 30–60% may
represent moderate heterogeneity; 50–90% may represent
substantial heterogeneity; 75–100%: considerable heterogeneity’.
We also examined heterogeneity by performing
a sensitivity analysis, in which we calculated pooled RRs
and 95% CIs while excluding studies one at a time from
the analysis.25
To examine potential publication bias, we
used Egger’s regression test. We did not test funnel plot
symmetry to assess for publication bias due to the low
power of that test when less than ten studies are avail-
able.26
We performed sub-analyses to calculate the
pooled RRs for cohort studies and case–control studies
separately, the RR of alcoholic cirrhosis and the RR of
death (i.e. with a diagnosis of cirrhosis or CLD). In order
to assess confounding and the direction and magnitude
of overall adjustment, we meta-analysed the crude effect
sizes and compared them with the adjusted values.
564 Aliment Pharmacol Ther 2016; 43: 562–574
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O. J. Kennedy et al.
For this purpose, we used the reported crude effect sizes
or, where not reported, we calculated crude effect sizes
from the published data. We used STATA (Release 13, StataCorp
LP, College Station, TX) and Mathematica (Version
10, Wolfram Research, Inc., Champaign, IL) to
perform the analyses, and we used a two-sided P > 0.05
for statistical signiﬁcance.
RESULTS
Details of the study selection process and the
included studies
Figure 1 illustrates the process for selecting the studies
for inclusion in this meta-analysis. The searches returned
2023 studies. After OJK ﬁrst excluded 1290 duplicates,
OJK and RB separately reviewed titles and abstracts and
excluded 646 irrelevant studies. OJK and RB then examined
the full text of the remaining studies and excluded
a further 78 studies for not meeting the eligibility criteria
described above. Nine studies remained and we included
all in this meta-analysis.7–9, 12–14, 27–29
Table 1 summarises the characteristics of the nine
included studies, which included eight journal articles and
one conference abstract.27
The studies were published
between 1994 and 2015 and involved 1990 cases and
432 133 participants. Five were cohort studies, involving
1364 cases and 429 202 participants, and four were case–
control studies, involving 626 cases and 2305 controls
(2931 participants in total). Two of the studies were in the
USA, six in Europe and one in Singapore. Seven studies
included men and women. One case–control study
included males only.27
One cohort study included only
male smokers without a history of malignancy, alcoholism
or major health problems.13
The other cohort studies all
involved men and women recruited as summarised in
Table 1. The cohort studies measured outcomes using
death and/or hospitalisation records and, thus, lost few
participants to follow-up. Participants in the case–control
studies were recruited from hospital records (i.e. both
cases and controls). The studies adjusted for a variable
mix of relevant confounders, but all adjusted for alcohol
(the exact adjustments used in the conference abstract
were unclear27
). All the studies measured coffee consumption
by means of a self-completion questionnaire or interview,
in which participants selected a pre-deﬁned category
of consumption. All measurements were in cups. One
study asked about the type of coffee preparation (e.g.
boiled, ﬁltered, etc.) and cup size.13
Another study asked
whether the coffee was caffeinated or decaffeinated.8
For
that study, we used the RRs for caffeinated coffee consumption
in our analysis, whereas for the other studies we
used the RRs for total coffee consumption.
Figure S1 illustrates the results of the risk of bias
assessment for the individual studies. In summary, we
found a high risk of bias for the following domains: confounding,
selection and outcome measurement. We performed
an assessment of the overall quality of evidence
for the effect of coffee on cirrhosis using the GRADE
system. We rated the quality of evidence based on risk
of bias, inconsistency, indirectness, imprecision, publica-
2023 documents returned
in literature search
1290 duplicates removed
646 irrelevant documents
excluded after reading titles
and abstracts
87 documents selected
for full text review
5 cohort studies and
4 case control
studies
78 studies excluded because:
•
•
No OR, RR or HR for cirrhosis or no
RCT, CC, or cohort study (n = 49)
Commentary/review (n = 22)
•
•
<3 exposures categories (n = 4)
Later study of same cohort (n = 2)
• Tea and coffee together (n = 1)
Figure 1 | A schematic
showing the selection of
relevant studies for inclusion
in the meta-analysis.
Aliment Pharmacol Ther 2016; 43: 562–574 565
ª 2016 John Wiley & Sons Ltd
Systematic review with meta-analysis: coffee and risk of cirrhosis
tion bias and factors that increase the quality of evidence.
We rated the quality of evidence as low, as indicated
in the Table S2.
To understand better the magnitude and direction of
overall confounding across all studies, we compared the
pooled adjusted and unadjusted RRs of cirrhosis for an
increase in coffee consumption of two cups per day.
After adjustment, the pooled RR decreased from 0.66
(95% CI 0.47–0.85) to 0.56 (95% CI 0.44–0.68), indicating
the overall effect of adjusting for confounding
increase the effect size away from null.
In determining the overall risk of bias in the individual
studies, we found a high risk in all the case–control
studies because of the potential for selection bias in
Table 1 | Summary of the characteristics of the (a) cohort and (b) case–control studies included in this meta-analysis
Cohort study Country
Follow-up
years
Cohort
(% men)
Cases
(cumulative
rate/1000)
Population
characteristics
(age)
Measurement
of coffee
consumption
Outcome
ascertainment
(a)
Tverdal and
Skurtveit12
Norway 16.9 (mean) 51 306 (50) 53 (1.0) Gen pop (20–55)* FFQ Death records
(ICD codes)
Klatsky et al.9
United States 14.1 (mean) 125 580 (44) 330 (2.6) Gen pop (n/a)† FFQ Death/hospital
records
(ICD codes)‡
Lai et al.13
Finland 18.2 (median) 27 037 (100) 213 (7.9) Smokers (50–69)§ FFQ Death records
(ICD codes)
Goh et al.14
Singapore 14.7 (mean) 63 257 (44) 114 (1.8) Gen pop (45–74)¶ FFQ Death records
(ICD codes)
Setiawan et al.8
United States 18 (median) 162 022 (47) 654 (4.0) Gen pop (45–75)** FFQ Death records
(ICD codes)
Case–control
study Country
N (% men) and
age of cases
N (%men) and
age of controls
Case
selection
Control
selection
Measurement of
coffee
consumption
(b)
Corrao et al.28
Italy 115 (68) mean age 58 167 (60) mean
age 60
Hospital†† Same hospital‡‡ Interview
Corrao et al.7
Italy 274 (60) mean age 56 458 (60) mean
age 55
Hospital§§ Same hospital‡‡ Interview
Gallus et al.29
Italy 101 (82) median aged 62 1538 (74) median
age 56
Hospital¶¶ Same hospital‡‡ FFQ
Stucker et al.27
France 136 (100) aged <75 142 (100)
aged <75
Hospital Hospital‡‡,
*** FFQ
FFQ, Food frequency questionnaire; ICD, International Classiﬁcation of Diseases; gen pop; general population.
* Recruited from a cardiovascular screening programme.
† Members of a health care programme (CLD excluded at baseline by ICD codes).
‡ Cases identiﬁed by ICD codes but conﬁrmed only if (i) histological evidence, (ii) two hospital admissions 12 months apart or 1
admission plus a death certiﬁcate diagnosis, (iii) diagnosis by a gastroenterologist or (iv) a compelling clinical picture.
§ Recruited from an earlier trial into the effect of vitamin E supplementation on lung cancer incidence (those who reported cirrhosis
excluded at baseline).
¶ Residents in government housing estates.
** Recruited from a driving license database, voter registration lists and health care ﬁnancing administration data.
†† After exclusion of hepatic encephalopathy, hepatocellular carcinoma and primary biliary cirrhosis.
‡‡ Liver disease excluded.
§§ After exclusion of hepatic encephalopathy, hepatocellular carcinoma, primary biliary cirrhosis and other rare forms of cirrhosis,
such as Wilson’s disease and hemochromatosis.
¶¶ Derived from another case–control study into cancer.
*** Matched for age and birth country.
566 Aliment Pharmacol Ther 2016; 43: 562–574
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O. J. Kennedy et al.
choosing cases and controls and for recall bias in determining
exposure to confounders. We found an unclear
overall risk of bias in the cohort studies. We did not
assign a ‘low’ risk of overall bias to any study even if
there was no obvious source of bias that would have
affected the results. This was in accordance with the
ACROBAT-NRSI, which indicates that only randomised
trials should be considered ‘low’ overall risk of bias.
Coffee consumption and cirrhosis
Table 2 summarises the results as reported by the studies.
Figure 2 is a forest plot of the calculated RRs of cirTable
2 | Summary of the results of the studies included in this meta-analysis
Study
Coffee (cups
per day) Participants
Cases
(cumulative
rate/1000)
Adjusted
RR (95% CI) Adjustments
Cohort studies country
Tverdal and Skurtveit12
(any cirrhosis)
2 51 306 53 (1.0) 0.6 (0.5–0.8) Gender, age, alcohol, smoking, BMI,
cholesterol, systolic blood pressure,
triglycerides
Tverdal and Skurtveit12
(alcoholic cirrhosis)
2 51 306 36 (0.7) 0.6 (0.5–0.8) Gender, age, alcohol, smoking, BMI,
cholesterol, systolic blood pressure,
triglycerides
Klatsky et al.9
(alcoholic cirrhosis)
0* 33 634 54 (1.6) 1 (ref.) Gender, alcohol, smoking, BMI,
race, education<1 17 576 24 (1.4) 0.7 (0.4–1.1)
1–3 52 351 96 (1.8) 0.6 (0.4–0.8)
4+ 20 504 22 (1.1) 0.2 (0.1–0.4)
Per extra cup 0.8 (0.7–0.9)
Klatsky et al.9
(non-alcoholic
cirrhosis)
0* 33 634 24 (0.7) 1 (ref.) Gender, alcohol, smoking, BMI,
race, education<1 17 576 17 (1.0) 1.2 (0.6–2.2)
1–3 52 351 68 (1.3) 1.3 (0.8–2.1)
4+ 20 504 18 (0.9) 0.7 (0.4–1.3)
Per extra cup 0.9 (0.8–1.0)
Lai et al.13
0 667 10 (15.0) 0.73 (0.38–1.42) Age, alcohol, smoking, BMI, cholesterol,
education, diabetes, tea, marital status,
ATBC intervention arm†
>0 to <1 3094 75 (24.2) 1 (ref.)
1 to <2 7204 68 (9.4) 0.44 (0.31–0.62)
2 to <3 8086 39 (4.8) 0.23 (0.15–0.35)
3 to <4 4515 15 (3.3) 0.15 (0.08–0.26)
4+ 3471 6 (1.7) 0.08 (0.03–0.18)
Per extra cup 0.55 (0.48–0.63)
Goh et al.14
0 ‡ 18 816 45 (2.4) 1 (ref.)§ Gender, age, alcohol, smoking, BMI,
education, diabetes, physical activity,
dialect group, year of recruitment
1 22 803 34 (1.5) 0.62 (0.40–0.97)§
2+ 21 638 35 (1.6) 0.63 (0.40–1.00)§
Setiawan et al.8
0 44 438 184 (4.1) 1 (ref.)§ Gender, age, alcohol, smoking, BMI, race,
education, diabetes<1 31 056 163 (5.2) 1.14 (0.92–1.41)§
1 45 717 202 (4.4) 0.85 (0.69–1.04)§
2–3 32 593 91 (2.8) 0.54 (0.42–0.69)§
4+ 8218 14 (1.7) 0.29 (0.17–0.50)§
Case–control studies
Corrao et al.28
0 60 28 1 (ref.)¶ Gender, age, alcohol, smoking, HBsAg and
anti-HCV status1 124 49 0.6 (0.2–1.1)¶
2+ 98 38 0.5 (0.3–1.0)¶
Corrao et al.7
0 112 57 1 (ref.)¶ Alcohol, smoking, education, HBsAg and
anti-HCV status, energy intake,
carbohydrates, lipids and proteins
>0 to 1** 173 71 0.47 (0.20–1.10)¶
>1 to 2** 258 84 0.23 (0.10–0.53)¶
>2 to 3** 87 25 0.21 (0.06–0.74)¶
3+** 57 20 0.16 (0.05–0.50)¶
Gallus et al.29
0 247 28 1 (ref.)¶ Gender, age, alcohol, smoking, BMI,
education, diabetes, area of residence,
year of interview, history of hepatitis
1 367 31 0.8 (0.4–1.6)¶
2 463 29 0.6 (0.3–1.2)¶
3+ 562 13 0.3 (0.1–0.7)¶
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Systematic review with meta-analysis: coffee and risk of cirrhosis
rhosis for an increase in coffee consumption of two cups
per day for each study and overall. In eight studies,
increasing coffee consumption by two cups per day was
associated with a statistically signiﬁcant reduction in the
risk of cirrhosis. In the other study, Goh et al., the corresponding
RR was 0.75 (95% CI 0.55–1.02). The pooled
RR across all studies was 0.56 (95% CI 0.44–0.68). In all
but one study, Goh et al., there was evidence of a dosedependent
relationship, with generally lower RRs for
higher consumption categories. The data as reported by
the studies are illustrated as a semi-log plot in Figure 3.
We calculated that compared to no consumption the
pooled RRs of cirrhosis were 0.78 (95% CI 0.68–0.90),
0.57 (95% CI 0.50–0.65), 0.43 (95% CI 0.37–0.50) and
0.35 (95% CI 0.30–0.41) for one to four cups of coffee
per day respectively.
Egger’s regression test gave no indication of statistically
signiﬁcant publication bias (P > 0.05). Cochran’s Q
and I2
were 48 (P = 0.0) and 83.3%, respectively, and
showed statistically signiﬁcant heterogeneity between the
Table 2 | (Continued)
Study
Coffee (cups
per day) Participants
Cases
(cumulative
rate/1000)
Adjusted
RR (95% CI) Adjustments
Stucker et al.27
0–1 133†† 76†† 1 (ref.)¶ n/a
2 70†† 33†† 0.65 (0.3–1.4)¶
2+ 75†† 27†† 0.33 (0.2–0.7)¶
BMI, body mass index; ATBC, alpha-tocopherol, beta-caroten; HBsAg, hepatitis B virus surface antigen; HCV, hepatitis C virus.
* Never or seldom.
† Participants were taken from another trial investigating vitamin E supplementation in the form of alpha-tocopherol or beta-caro-
ten.
‡ None/less than daily.
§ Hazard ratio.
¶ Odds ratio.
** Reported as caffeine from coffee, with 100 mg being equal to one cup.
†† Calculated from the total number of cases and controls and the percentage of the totals in each consumption category.
Name
Cohort studies
Tverdal and Skurtveit (12) 53
Lai et al. (13) 213
Goh et al. (14) 114
Setiawan et al. (8)
Subtotal (I-squared = 91.1%, p = 0.000)
Subtotal (I-squared = 0.0%, p = 0.403)
Overall (I-squared = 83.3%, p = 0.000)
Note: Weights are from random effects
analysis
.25 .5 .75 1
Case control studies
Klatsky et al. (9) 330
0.60 (0.50, 0.80) 11.97
0.73 (0.62, 0.86) 12.74
0.30 (0.23, 0.40) 13.64
0.75 (0.55, 1.02) 9.60
0.59 (0.51, 0.69)
0.59 (0.41, 0.76)
13.51
61.47
0.67 (0.47, 0.96) 9.20
0.40 (0.24, 0.66) 10.20
0.55 (0.35, 0.87) 8.84
0.50 (0.33, 0.74) 10.29
0.52 (0.40, 0.63)
0.56 (0.44, 0.68)
38.53
100.00
Cases RR (95% Cl)
%
Weight
Corrao et al. 1994 (28)
Corrao et al. 2001 (7)
Gallus et al. (29)
Stucker et al. (27)
654
274
101
115
136
Figure 2 | Forest plot showing
the associations of cirrhosis
with drinking an additional
two cups of coffee per day as
reported by the included
studies individually and pooled
overall. The pooled RRs were
calculated by random effects
meta-analyses. The sizes of
the squares represent the
weighting of each study in the
calculation and the pooled
RRs are represented by
diamonds.
568 Aliment Pharmacol Ther 2016; 43: 562–574
ª 2016 John Wiley & Sons Ltd
O. J. Kennedy et al.
studies. We further investigated this heterogeneity by
means of a sensitivity analysis, in which we calculated
pooled RRs while excluding the studies one at a time.
The pooled RRs in the sensitivity analysis and the Q and
I2
varied most substantially when Lai et al. was excluded.
Without Lai et al., the pooled RR for an increase in coffee
consumption of two cups per day was 0.61 (95% CI
0.53–0.68). The corresponding Q and I2
values were 11
(P = 0.14) and 36.1%, showing markedly reduced heterogeneity
compared to when Lai et al. was included. The
pooled RR of cirrhosis for an increase of two cups per
day in cohort studies was 0.58 (95% CI 0.41–0.76; I2
91.1%) and in case–control studies it was 0.52 (95% CI
0.40–0.63; I2
0.0%). The RRs of alcoholic cirrhosis, calculated
from two studies,9, 12
and death from liver disease,
calculated from four studies,8, 12–14
for an increase in
coffee consumption of two cups per day were 0.62 (95%
CI 0.51–0.73; I2
0.0%) and 0.55 (95% CI 0.35–0.74; I2
90.3%) respectively.
DISCUSSION
Earlier meta-analyses have reported an inverse association
between coffee consumption and liver cancer.10, 30, 31
Studies have also reported protective effects of coffee in animals
with liver disease and in humans where the outcomes
were less severe CLD including abnormal LFTs.9, 32, 33
However, this is the ﬁrst meta-analysis to show a protective
effect of coffee against cirrhosis. The analysis of ﬁve cohort
and four case–control studies has shown that increasing
daily coffee consumption by two cups is associated with a
near halving of the risk of cirrhosis. While statistically signiﬁcant
heterogeneity existed across the studies, this was
explained by the effect of one study, and the association was
consistent through the sensitivity analysis. Sensitivity analyses
showed that increasing daily coffee consumption by
two cups is also associated with reduced RRs of alcoholic
cirrhosis and death from cirrhosis.
One of the strengths of this meta-analysis was the
inclusion of studies that reported a summary dose RR or
RRs for three or more categories of coffee consumption
only. This allowed the estimation of a clinically relevant
dose–response between coffee and cirrhosis. We excluded
four studies, including one conference abstract, which
reported RRs for less than three categories of coffee con-
sumption.34–37
Those studies reported inverse associations
between coffee and cirrhosis, which were
statistically signiﬁcant in three studies, and thus support
the ﬁndings of this meta-analysis. There are also limitations.
First, the studies included were observational
which, by design, do not infer causation and are generally
more susceptible to bias and confounding than randomised
studies. In the risk of bias assessment, the case–
control studies were at high risk of selection bias in
choosing cases and controls and to recall bias in the estimation
of coffee and alcohol consumption years previously.
Despite the risk of bias, the case–control studies
agreed broadly with the cohort studies. We found that
overall adjustment (including for body mass index, diabetes,
alcohol and viral hepatitis) increased the effect size
away from null, which suggests that coffee drinkers had
greater overall exposure to the known risk factors of cirrhosis
compared to noncoffee drinkers. However, resid-
1
0.5Relativerisk
0.2
0.1
0 1 2 3
Cups of coffee per day
Corrao et al. 1994 (28)
Corrao et al. 2001 (7)
Gallus et al. (29)
Goh et al. (14)
Klatsky et al (9)
Lai et al. (13)
Setiawan et al. (8)
Stucker et al. (27)
Tverdal and Skurtveit (12)
4 5 6
Figure 3 | A semi-log plot of the adjusted study-speciﬁc and overall RRs of cirrhosis vs. cups of coffee per day. The
study-speciﬁc RRs are plotted against the estimated median coffee consumption in each reported category.
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Systematic review with meta-analysis: coffee and risk of cirrhosis
ual confounding may have existed in all studies due to
confounding variables that were not measured accurately
or not adjusted for. While all the studies adjusted for
alcohol consumption (we were unclear as to what adjustments
were made in the conference abstract27
), which is
the most critical confounder, only six studies adjusted
for age, six for body mass index and gender, and four
for diabetes. The cohort studies did not adjust for viral
hepatitis status but prevalence was likely to be low in the
populations studied. One particular concern is the potential
for confounding from hidden nutritional and lifestyle
factors not measured and adjusted for in the studies. If
such factors were associated with coffee consumption
and inﬂuenced the risk of cirrhosis, this would introduce
bias into our ﬁndings. Another potential confounder is
that people with pre-existing liver disease metabolise caffeine
more slowly38, 39
and, as a result, may drink less
coffee. This may have been important in the case–control
studies, in which participants estimated previous coffee
consumption over a time when they probably already
had reduced liver function. The corresponding effect
would be diluted in the cohort studies due to the long
follow-up (all were longer than 14 years) and the exclusion
of pre-existing liver disease at baseline in two of the
studies.9, 13
Some of the cohort studies investigated confounding
by pre-existing liver disease in sensitivity analyses.
In one such analysis, Setiawan et al. found that the
RR of CLD death for ≥ two cups of coffee daily compared
to none remained comparable in magnitude and
statistically signiﬁcant (RR 0.54; 95% CI 0.42–0.69) when
deaths in the ﬁrst 2 years were excluded. Lai et al. found
that the RR of CLD death for an extra cup of coffee
per day was 0.53 (95% CI 0.44–0.64) in the ﬁrst 10 years
of the trial and 0.57 (95% CI 0.48–0.69) in the last
10 years. As such, drinking coffee appeared to protect
against cirrhosis in participants who would have had
varying levels of undiagnosed liver disease at baseline.
We investigated the overall effect of confounding by
comparing the adjusted and unadjusted RRs across all trials.
We found that adjustment for confounding increased
the pooled RR away from null. In accordance with the
GRADE system, this added to the overall quality of evidence
for the protective effect of coffee against cirrhosis.
We found statistically signiﬁcant heterogeneity
between the studies, which may indicate important differences
in the populations studied and in the study
methods. The ages, countries and regions of origin, and
proportions of men and women varied. In addition, and
as noted above, participants with evidence of CLD at
baseline were excluded from two cohort studies, while in
the other cohort studies CLD was not looked for systematically
at baseline and, thus, was not excluded. Between
the cohort studies, the most signiﬁcant difference in the
populations was that in Lai et al. the participants were
all Finnish male smokers recruited from an earlier study
into lung cancer, while in the others participants were
men and women recruited from databases more representative
of the general population (see Table 1). When
the study of Lai et al. was excluded during the sensitivity
analysis, heterogeneity became statistically insigniﬁcant,
whereas the pooled RR varied by 5% only.
Heterogeneity may also exist in the measurement of
coffee consumption. In all studies, participants estimated
the usual daily intake of coffee or the daily average over
a speciﬁed preceding period (e.g. 1 year). Participants’
responses may have been inﬂuenced if they knew they
were in a study investigating nutrition, leading to overestimation
or underestimation of consumption. This may
be more signiﬁcant for the case–control studies because
participants recalled coffee consumption over longer
periods and because cases may recall their diet differently
to controls leading to differential misclassiﬁcation
of exposure. CLD in cases may have reduced consumption
and hence overestimated the apparent protective
effect. Differences in cup sizes, the methods of preparation
(e.g. ﬁltered vs. boiled) and the types of coffee (e.g.
decaffeinated vs. caffeinated) might also be important.
For example, one study13
found that the RR of cirrhosis
for an additional cup per day was 0.50 (95% CI 0.40–
0.63) for ﬁltered coffee and 0.62 (95% 0.43–0.88) for
boiled coffee. Another study8
found that the RR of CLD
death for ≥ two daily cups of decaffeinated coffee was
0.54 (95% CI 0.35–0.85), although this was broadly similar
to that for caffeinated coffee.
Heterogeneity might have arisen due to the different
outcome measures. First, four studies identiﬁed outcomes
using death records only, four studies used hospital
records only, and one study used both. The importance of
these differences is unclear as the pooled RR of death, calculated
from studies using death records only, was similar
to the RR pooled from the case–control studies, which
used hospital records only. Secondly, studies identiﬁed
cases differently, for example, by histology, a compelling
clinical picture or by searching death and hospital records
for Classiﬁcation of Diseases (ICD) codes, for example,
9th edition code 571: ‘Chronic liver disease and cirrhosis’.
Histology is the reference standard, and ideally would have
been used to conﬁrm all cases, but the clinical picture of
cirrhosis is speciﬁc (e.g. oesophageal varices or spontaneous
bacterial peritonitis) and patients who die from
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O. J. Kennedy et al.
CLD (i.e. ICD 571) but do not have HCC are highly likely
to have cirrhosis. However, there was one study8
which
appeared to include ICD codes relating to acute liver disease
in the total count of CLD deaths. We were uncertain
how differences in outcome measurements affected our
pooled RR, which did not vary substantially during the
sensitivity analysis and remained statistically signiﬁcant.
The use of biopsy in some studies 9, 27, 29
may have
introduced ascertainment bias if there were differential
biopsy use according to baseline coffee consumption or
to other correlated risk factors. Bias may also have been
introduced if there were undetected cases of compensated
cirrhosis on account of the included studies using
hospital and/or death records only to identify cases.
Some compensated cases might have been detected if
biopsies were performed on asymptomatic participants
in hospital (e.g. for a reason other than cirrhosis), but
undiagnosed compensated cases in the community
would have been missed. The risk of bias from these
undetected cases is uncertain because the pathological
pro-ﬁbrotic mechanism which causes the initial establishment
of cirrhosis is the same irrespective of aetiology
or subsequent clinical sequelae (i.e. whether the
individual remains asymptomatic, is hospitalised or
dies). Thus, it is logical to expect that the alleged protective
effect of coffee, which likely begins long before
cirrhosis is established, would apply equally to cases
detected by the included studies and those that were
not. However, the uncertainty highlights the need for
randomised trials.
We could only partially examine the inﬂuence of aetiology
on the inverse association between coffee consumption
and cirrhosis. We found that the pooled RR
for alcoholic cirrhosis was similar to the overall estimate.
However, there was insufﬁcient data to calculate estimates
for other important aetiologies of cirrhosis, such
as viral hepatitis and NAFLD. While the potential inﬂuence
of aetiology is unclear since the underlying pathological
process leading to cirrhosis is the same, this issue
should be considered further in new studies.
There also exists the possibility of language bias since
we included English language studies only. However, most
studies are published in English, and studies investigating
the effect of language bias in meta-analyses generally
report limited evidence of an effect.40
There is also some
evidence that non-English language trials tend to be of
lower quality and report larger effect sizes,41
and so the
inclusion of English language studies only is unlikely to
lead to signiﬁcant bias in our ﬁndings. Finally, there also
exists the potential of publication bias. While Egger’s
regression test detected no statistically signiﬁcant publication
bias, we were unable to rule out publication bias
completely. First, the relatively small number of studies
provided limited statistical power and, secondly, studies
with statistically signiﬁcant results are more likely to be
published compared to those with null results.42
As such,
the pooled RR reported in this study may be exaggerated
compared to the true value.
It is biologically plausible that coffee protects the liver
against the inﬂammatory and ﬁbrotic process leading to
cirrhosis. Caffeine is thought to be important, and animal
studies show that caffeine not from coffee protects
against toxin-induced liver ﬁbrosis.33, 43
Caffeine’s protective
mechanism of action may be through antagonism
of the adenosine receptor A2aAR.44
Hepatic stellate cells
(HSCs) are the primary effector cells mediating ﬁbrogenesis
in the liver and express A2aAR. Activation of
A2aAR markedly up-regulates collagen synthesis in
HSCs,45, 46
whereas mice lacking expression of A2aAR
are protected from toxin-induced ﬁbrosis.47
Caffeine
might also attenuate ﬁbrosis by suppression of inﬂammation
and oxidative stress. Caffeine inhibits tumour necrosis
factor-a, a pro-inﬂammatory cytokine and reactive
oxygen species production by Kupffer cells.48
While caffeine
might be important, there is evidence that other
noncaffeine-mediated mechanisms also contribute to the
protective effect seen. First, adjusting for coffee consumption
pushes the association between caffeine and
cirrhosis towards null, and some studies report no association
between cirrhosis and noncoffee sources of caffeine.7,
8
Secondly, and as is mentioned above, there is
some epidemiological evidence that decaffeinated coffee
protects against cirrhosis and abnormal liver function
tests.8, 49
Decaffeinated coffee also protects against toxininduced
ﬁbrosis in animal studies.43
The evidence for
decaffeinated coffee protecting against cirrhosis is weaker
overall than for regular coffee, but there is still biological
plausibility. Coffee contains a range of biologically active
ingredients beyond caffeine, including anti-oxidative and
anti-inﬂammatory agents, such as chlorogenic acid, kahweol
and cafestol, and there is evidence that these may
confer protection against liver ﬁbrosis.43
The protective effect of coffee against cirrhosis may also
involve indirect mechanisms that modify risk factors. Laboratory
studies have shown that various constituents of
coffee inhibit the activities of hepatitis B and C viruses.50–
52
In addition, and of even greater signiﬁcance to public
health, is the inverse association between coffee (both caffeinated
and decaffeinated) and type 2 diabetes mellitus
(T2DM). A recent meta-analysis calculated that the RR of
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ª 2016 John Wiley & Sons Ltd
Systematic review with meta-analysis: coffee and risk of cirrhosis
T2DM for an increase in consumption of one cup per day
was 0.91 (95% CI 0.89–0.94) for regular coffee and 0.94
(95% CI 0.91–0.98) for decaffeinated coffee.53
The mechanism
of action of coffee on T2DM is unclear, but caffeine
is unlikely to be the sole mediator. Caffeine causes a shortterm
reduction in insulin sensitivity54
and generally studies
do not show a protective effect of caffeine against
T2DM after adjustment for coffee and tea intake.55, 56
Chlorogenic acid in coffee is likely important; it has been
shown to inhibit glucose absorption in the gut. It also inhibits
hydrolysis of glucose-6-phosphate, which is the ﬁnal
step of glucose production by gluconeogenesis and
glycogenolysis.57
Other constituents in coffee that may
improve glucose metabolism and partly explain the relationship
between coffee and T2DM include magnesium,
trigonelle, lignans and quindes.58–61
The favourable metabolic
effects of coffee would be expected to protect against
NAFLD and the related inﬂammation (NASH) which can
lead to ﬁbrosis and cirrhosis.
Cirrhosis is by far the most important risk factor for
HCC. Accordingly, the ﬁndings of this meta-analysis
may in part explain observational studies showing an
inverse association between coffee and HCC. However,
while it is logical to suggest that preventing cirrhosis
would reduce HCC, other mechanisms involving a direct
anti-carcinogenic effect of coffee may exist. Caffeine is
thought to directly inhibit the proliferation of HCC
cells.62
In addition, cafestol and kahweol upregulate
phase II enzymes in the liver, which may increase clearance
of potentially carcinogenic toxic insults,63, 64
and
the anti-oxidative effects of coffee may reduce DNA
damage from reactive oxygen species. Observational
studies do not show a consistent association between
HCC and decaffeinated coffee,8, 65
which indicates that
caffeine may be the primary agent. This is supported by
a recent meta-analysis which showed an inverse association
between HCC and green tea, a noncoffee source of
caffeine.66
Before recommending an increase in coffee consumption
to those at risk of cirrhosis, consideration is
required of the wider effects of coffee. There is evidence
of an association of coffee with lung and bladder cancer
and with bone fractures.19, 67, 68
However, there are also
beneﬁts of coffee beyond those on the liver. Coffee has
been inversely associated with all-cause mortality,69
neurological
diseases 70
and a number of different cancers.71
Coffee may also protect against stroke,72
although there
is a need for further work to understand fully the effects
of coffee on the cardiovascular system. This is especially
important at higher levels of consumption, where there
is less evidence concerning the beneﬁcial effects of coffee
as well as the potential harms.
In conclusion, this meta-analysis shows that an
increase in daily coffee consumption of two cups is associated
with a near halving of the risk of cirrhosis. This is
a large effect compared to many medications used for
the prevention of disease. For example, statin therapy
reduces the risk of cardiovascular disease by 25%.73
Furthermore,
unlike many medications, coffee is generally
well tolerated and has an excellent safety proﬁle. The
ﬁndings of this meta-analysis are important given the
high incidence of severe liver disease, the positive interaction
between alcohol and obesity for liver disease risk
and the lack of speciﬁc treatments to prevent liver disease
due to these factors. The next steps should be to
develop interventions that support patients at risk of or
with mild–moderate CLD, to increase their coffee consumption,
even in existing coffee drinkers given the
dose–response relationship, and then to evaluate the
effect of increasing consumption on robust markers of
CLD in well-designed randomised studies. However,
such studies would be challenging (e.g. blinding would
not be possible) and would require careful consideration
of patient selection/stratiﬁcation, trial methodology and
the availability of suitable surrogate endpoints, given that
hard clinical endpoints would take years to occur.
SUPPORTING INFORMATION
Additional Supporting Information may be found in the
online version of this article:
Figure S1. Risk of bias graph and summary: review
authors’ judgements about each risk of bias item separately
and as percentages across all included studies.
*The assessment of the risk of bias from the measurement
of exposure included changes in exposure over
time. **The assessment of the risk of bias from missing
data included loss to follow-up for cohort studies.
Table S1. PRISMA-P protocol.
Table S2. Summary of Findings table according to the
GRADE assessment.
AUTHORSHIP
Guarantor of article: Julie Parkes.
Author contributions: JP, PJR and OJK conceived the study. OJK
performed the search. OJK and RB reviewed and selected the studies.
OJK and PJR did the risk of bias and overall quality of evidence
assessment. OJK extracted the data which were checked by RB. OJK
performed the statistical analysis. OJK drafted the manuscript. All
authors critically reviewed the manuscript and provided comments
or made amendments.
572 Aliment Pharmacol Ther 2016; 43: 562–574
ª 2016 John Wiley & Sons Ltd
O. J. Kennedy et al.
All authors approved the ﬁnal version of the article, including
the authorship list.
ACKNOWLEDGEMENT
Declaration of personal and funding interests: None.
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