Efficacy and Safety of Antidepressants in Patients With Comorbid Depression and Medical Diseases: An Umbrella Systematic Review and Meta-Analysis

Ole Köhler-Forsberg; Victoria Stiglbauer; Jelena Brasanac; Woo Ri Chae; Frederike Wagener; Kim Zimbalski; Oskar H Jefsen; Shuyan Liu; Malik R Seals; Stefanie Gamradt; Christoph U Correll; Stefan M Gold; Christian Otte

doi:10.1001/jamapsychiatry.2023.2983

. 2023 Sep 6;80(12):1196–1207. doi: 10.1001/jamapsychiatry.2023.2983

Efficacy and Safety of Antidepressants in Patients With Comorbid Depression and Medical Diseases

An Umbrella Systematic Review and Meta-Analysis

Ole Köhler-Forsberg ^1,^2,^✉, Victoria Stiglbauer ³, Jelena Brasanac ³, Woo Ri Chae ^3,^4,⁵, Frederike Wagener ³, Kim Zimbalski ³, Oskar H Jefsen ^1,², Shuyan Liu ^4,⁶, Malik R Seals ³, Stefanie Gamradt ³, Christoph U Correll ^4,^7,^8,^9,¹⁰, Stefan M Gold ^3,^4,^11,¹², Christian Otte ^3,⁴

¹Psychosis Research Unit, Aarhus University Hospital–Psychiatry, Aarhus, Denmark

²Department of Clinical Medicine, Aarhus University, Aarhus, Denmark

³Department of Psychiatry and Neuroscience, Campus Benjamin Franklin, Charité–Universitätsmedizin Berlin, Berlin, Germany

⁴DZPG (German Center for Mental Health), partner site Berlin, Berlin, Germany

⁵BIH Charité Clinician Scientist Program, BIH Biomedical Innovation Academy, Berlin Institute of Health at Charité–Universitätsmedizin Berlin, Berlin, Germany

⁶Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité–Universitätsmedizin Berlin, Berlin, Germany

⁷Department of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York

⁸Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York

⁹Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany

¹⁰Department of Psychiatry, Zucker Hillside Hospital, Northwell Health, Glen Oaks, New York

¹¹Department of Psychosomatic Medicine, Charité–Universitätsmedizin Berlin, Berlin, Germany

¹²Institute of Neuroimmunology and Multiple Sclerosis, Universitätsklinikum Hamburg–Eppendorf, Hamburg, Germany

Accepted for Publication: June 21, 2023.

Published Online: September 6, 2023. doi:10.1001/jamapsychiatry.2023.2983

^✉

Corresponding Author: Ole Köhler-Forsberg, MD, PhD, DMSc, Psychosis Research Unit, Aarhus University Hospital–Psychiatry, Palle Juul-Jensens Blvd 175, DK-8200 Aarhus N, Denmark (karkoe@rm.dk).

Author Contributions: Dr Köhler-Forsberg and Ms Stiglbauer had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Dr Köhler-Forsberg and Ms Stiglbauer contributed equally as co–first authors. Prof Gold and Prof Otte contributed equally as co–last authors.

Acquisition, analysis, or interpretation of data: Köhler-Forsberg, Stiglbauer, Brasanac, Chae, Wagener, Zimbalski, Jefsen, Liu, Seals, Gamradt, Gold, Otte.

Drafting of the manuscript: Köhler-Forsberg, Stiglbauer, Seals, Gold, Otte.

Critical review of the manuscript for important intellectual content: Stiglbauer, Brasanac, Chae, Wagener, Zimbalski, Jefsen, Liu, Gamradt, Correll, Gold, Otte.

Statistical analysis: Köhler-Forsberg, Brasanac, Otte.

Administrative, technical, or material support: Stiglbauer, Chae, Wagener, Liu, Gold, Otte.

Supervision: Köhler-Forsberg, Correll, Gold, Otte.

Conflict of Interest Disclosures: Dr Köhler-Forsberg reported personal fees from WCG Clinical and Lundbeck Pharma A/S outside the submitted work. Dr Gamradt reported personal fees from Abcam for giving a webinar presentation outside the submitted work. Dr Chae reported receiving research funding from the Deutsche Forschungsgemeinschaft outside the submitted work. Prof Correll reported receiving personal fees from AbbVie Inc outside the submitted work and consulting, advising, or receiving honoraria from Acadia Pharmaceuticals, Alkermes PLC, Allergan PLC, Angelini Pharma, Aristo Pharma GmbH, Biogen Inc, Boehringer Ingelheim, Cardio Diagnostics, Cerevel Therapeutics, LLC, CNX Therapeutics Ltd, COMPASS Pathways PLC, Darnitsa, Denovo, Gedeon Richter PLC, Hikma Pharmaceuticals PLC, Holmusk, Intra-Cellular Therapies, Janssen/Johnson & Johnson, Karuna Therapeutics, LB Pharmaceuticals, Lundbeck, MedAvante-ProPhase Inc, Medincell, Merck & Co, MindPax, Mitsubishi Tanabe Pharma Corporation, Mylan NV, Neurocrine Biosciences, Inc, Neurelis Inc, Newron Pharmaceuticals SpA, Noven, Novo Nordisk A/S, Otsuka Pharmaceutical Co, Ltd, Pharmabrain GmbH, PPD Biotech, Recordati, Relmada Therapeutics, Inc, Reviva Labs, Laboratorios Farmaceuticos ROVI, Seqirus Limited, SK Life Science Inc, Sunovion Pharmaceutical Inc, Sun Pharmaceutical Industries Ltd, Supernus Pharmaceuticals, Takeda Pharmaceuticals International, Teva Pharmaceutical Industries Ltd, and Viatris Inc; providing expert testimony for Janssen Pharmaceuticals and Otsuka Pharmaceutical Co, Ltd; serving on a data safety monitoring board for COMPASS Pathways PCL, Denovo, Lundbeck, Relmada Therapeutics, Inc, Reviva Labs, Laboratorios Farmaceuticos ROVI, Sage Therapeutics, Supernus Pharmaceuticals, and Teva Pharmaceutical Industries Ltd; receiving grant support from Janssen Pharmaceuticals and Takeda Pharmaceuticals International; receiving royalties from UpToDate; and holding a stock option in Cardio Diagnostics, MindPax, LB Pharmaceuticals, and The Quantic Group. Prof Gold reported receiving personal fees from Hexal AG and Streamed Up and grants from the National Multiple Sclerosis Society, Deutsche Forschungsgemeinschaft DFG, Bundesministerium für Gesundheit, Bundesministerium für Bildung und Forschung, and the European Commission outside the submitted work. Dr Otte reported receiving personal fees from Fortbildungskolleg, Janssen Pharmaceuticals, Lundbeck, Neuraxpharm, PeakProfiling GmbH, and LIMES Klinikgruppe and grants from the German Research Foundation, German Federal Ministry of Education and Research, European Union, and Berlin Institute of Health outside the submitted work. No other disclosures were reported.

Funding/Support: This research was supported in part by Mentor-Based Postdoctoral Fellowship Program in Rehabilitation Research MB-1707-28359 from the National Multiple Sclerosis Society (Prof Gold) and the BIH Charité Clinician Scientist Program funded by the Charité–Universitätsmedizin Berlin and the Berlin Institute of Health at Charité (Dr Chae).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 3.

Additional Contributions: Information specialist Helene Sognstrup, MSc (Aarhus University), helped with defining and conducting the literature search, for which she was not compensated.

^✉

Corresponding author.

PMCID: PMC10483387 PMID: 37672261

Key Points

Question

What is the evidence for use of antidepressants to treat or prevent comorbid depression in patients with medical diseases?

Findings

This umbrella systematic review identified 176 individual systematic reviews of randomized clinical trials in 43 medical diseases and quantitatively summarized and meta-analyzed the results of 52 meta-analyses of antidepressant effects in 27 medical diseases; results indicated sufficient quality of the individual meta-analyses but rather low quality of the meta-analyzed clinical trials. Compared with placebo, antidepressants showed better efficacy and worse tolerability and acceptability and were more likely to prevent depression.

Meaning

Antidepressants are effective and safe for the treatment and prevention of depression in patients with medical diseases, but too few large, high-quality trials exist.

This systematic review and meta-analysis assesses all available evidence for use of antidepressants in depression comorbid with medical diseases.

Abstract

Importance

Every third to sixth patient with medical diseases receives antidepressants, but regulatory trials typically exclude comorbid medical diseases. Meta-analyses of antidepressants have shown small to medium effect sizes, but generalizability to clinical settings is unclear, where medical comorbidity is highly prevalent.

Objective

To perform an umbrella systematic review of the meta-analytic evidence and meta-analysis of the efficacy and safety of antidepressant use in populations with medical diseases and comorbid depression.

Data Sources

PubMed and EMBASE were searched from inception until March 31, 2023, for systematic reviews with or without meta-analyses of randomized clinical trials (RCTs) examining the efficacy and safety of antidepressants for treatment or prevention of comorbid depression in any medical disease.

Study Selection

Meta-analyses of placebo- or active-controlled RCTs studying antidepressants for depression in individuals with medical diseases.

Data Extraction and Synthesis

Data extraction and quality assessment using A Measurement Tool for the Assessment of Multiple Systematic Reviews (AMSTAR-2 and AMSTAR-Content) were performed by pairs of independent reviewers following PRISMA guidelines. When several meta-analyses studied the same medical disease, the largest meta-analysis was included. Random-effects meta-analyses pooled data on the primary outcome (efficacy), key secondary outcomes (acceptability and tolerability), and additional secondary outcomes (response and remission).

Main Outcomes and Measures

Antidepressant efficacy presented as standardized mean differences (SMDs) and tolerability (discontinuation for adverse effects) and acceptability (all-cause discontinuation) presented as risk ratios (RRs).

Results

Of 6587 references, 176 systematic reviews were identified in 43 medical diseases. Altogether, 52 meta-analyses in 27 medical diseases were included in the evidence synthesis (mean [SD] AMSTAR-2 quality score, 9.3 [3.1], with a maximum possible of 16; mean [SD] AMSTAR-Content score, 2.4 [1.9], with a maximum possible of 9). Across medical diseases (23 meta-analyses), antidepressants improved depression vs placebo (SMD, 0.42 [95% CI, 0.30-0.54]; I² = 76.5%), with the largest SMDs for myocardial infarction (SMD, 1.38 [95% CI, 0.82-1.93]), functional chest pain (SMD, 0.87 [95% CI, 0.08-1.67]), and coronary artery disease (SMD, 0.83 [95% CI, 0.32-1.33]) and the smallest for low back pain (SMD, 0.06 [95% CI, 0.17-0.39]) and traumatic brain injury (SMD, 0.08 [95% CI, −0.28 to 0.45]). Antidepressants showed worse acceptability (24 meta-analyses; RR, 1.17 [95% CI, 1.02-1.32]) and tolerability (18 meta-analyses; RR, 1.39 [95% CI, 1.13-1.64]) compared with placebo. Antidepressants led to higher rates of response (8 meta-analyses; RR, 1.54 [95% CI, 1.14-1.94]) and remission (6 meta-analyses; RR, 1.43 [95% CI, 1.25-1.61]) than placebo. Antidepressants more likely prevented depression than placebo (7 meta-analyses; RR, 0.43 [95% CI, 0.33-0.53]).

Conclusions and Relevance

The results of this umbrella systematic review of meta-analyses found that antidepressants are effective and safe in treating and preventing depression in patients with comorbid medical disease. However, few large, high-quality RCTs exist in most medical diseases.

Introduction

Major depressive disorder (MDD) has a point prevalence of approximately 5% in the general population.^1,2 Among individuals with medical diseases, MDD represents one of the most common comorbidities, with point prevalence often exceeding 10% or even 20%.^3,4 Furthermore, many more patients exhibit subclinical depressive symptoms.³

Treatment of depression comorbid with medical diseases is important because depression in these populations is associated with decreased quality of life and poorer prognosis.³ Antidepressants represent a first-line treatment, with the most recent meta-analysis of randomized clinical trials (RCTs)⁵ showing small to medium effect sizes for specific antidepressants compared with placebo for MDD in general. However, meta-analyses of antidepressant efficacy⁵ are primarily based on RCTs that excluded individuals with medical diseases, potentially limiting the generalizability. Given that every third to sixth patient with a medical disease is treated with antidepressants,^6,7,8 it is important to establish the efficacy and safety in these patient populations.

The trials that have examined antidepressant treatment for depression comorbid with medical disease tend to be more heterogeneous than pivotal trials for regulatory purposes, ranging from small academic trials to larger consortia in a wide range of different medical diseases in different clinical or geographical settings. This situation results in a complex evidence landscape for the treatment of comorbid depression that requires careful examination.

Currently, to our knowledge, there is no direct quantitative comparison of the evidence across all individual pharmacological strategies in comorbid depression. Moreover, the quality of the meta-analyses and the included RCTs has not been evaluated, which is an indispensable step before treatment recommendations can confidently be made.

To address this gap, we conducted an umbrella systematic review of all available evidence for use of antidepressants in depression comorbid with medical diseases. We hypothesized that antidepressants would be significantly superior to placebo in treating patients with depression and medical diseases and reasonably acceptable, with potential differences across distinct medical diseases.

Methods

Design

We performed an umbrella review covering systematic reviews with or without meta-analyses of RCTs for treatment of comorbid depression in medical diseases that reported the efficacy and tolerability of antidepressants compared with placebo or each other. The protocol was prospectively registered with PROSPERO (CRD42022297478) on December 10, 2021. The protocol defined a priori the review questions, search strategy, inclusion and exclusion criteria, risk of bias assessment, and data synthesis plan in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol statement (eTable 1 in Supplement 1). The present results are reported in accordance with PRISMA checklists (eTables 2 and 3 in Supplement 1).

Participants/Population

We included all systematic reviews on human participants, irrespective of age, sex, and setting (inpatient, outpatient, or community setting), participating in placebo- or active-controlled RCTs studying antidepressants for depression in medical diseases. Hence, the participants had to have been diagnosed with a medical disease and randomized to receive antidepressants for comorbid depression. Systematic reviews of patients with comorbid depressive symptoms (ie, but not diagnosed MDD) were also included.

Types of Included Studies

We applied the following predefined inclusion criteria: studies defined as a systematic review of placebo-controlled or active-controlled RCTs of antidepressants in humans with a medical disease (defined as all conditions except mental disorders, ie, International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10] codes within the F chapter) and comorbid depression that examined the antidepressant efficacy and tolerability of antidepressants (defined as all drugs listed under the World Health Organization Anatomical Therapeutic Chemical codes N06A⁹) vs placebo or each other. Exclusion criteria consisted of the following: observational studies and case reports; studies in which a medical disease and comorbid depression were not the exposure of interest and in which efficacy and tolerability of antidepressants were not the outcome of interest; studies or study arms in which the active drug was compared with any control other than placebo (eg, psychotherapy); depression comorbid with a mental disorder (ie, diagnosed within the ICD-10 F chapter, which includes dementia); and animal, in vivo, and in vitro experiments.

Search Methods

We conducted the literature search from database inception until March 31, 2023, in PubMed and EMBASE (for search terms used, see the eMethods in Supplement 1). We applied no restrictions regarding year or language.

Screening Procedure

Pairs of independent reviewers (V.S. and J.B., V.S. and K.Z., W.R.C. and O.H.J., K.Z. and S.G., F.W. and M.R.S., V.S. and F.W., and V.S. and S.L.), blinded to each other’s results, screened all identified articles during each step of the screening procedure. First, titles and abstracts were screened based on the eligibility criteria outlined above. Second, full texts were examined and screened for applicability based on the above-mentioned inclusion and exclusion criteria. There was agreement between reviewers in 88.6% of studies and disagreement in 11.4%, so a senior author (O.K.-F., S.M.G., or C.O.) not involved in the initial assessment made the final decision. The Cohen κ, a measure of interrater agreement, resulted in κ = 0.74 (which is considered substantial agreement).

Selection of Systematic Reviews

In case several systematic reviews of the same medical disease were identified, we chose the review that conducted the (network) meta-analysis with the largest number of RCTs. If 2 (network) meta-analyses on the same medical disease included the same number of RCTs, we chose the one with the largest number of participants. (Network) meta-analyses meeting the inclusion criteria were removed if there was another (network) meta-analysis with more RCTs for that same medical disease and antidepressant treatment as long as more than 50% of the meta-analyzed trials overlapped and the pooled sample was larger, as done previously.¹⁰ To show representative findings, we included only systematic reviews with broad and generalizable inclusion criteria, meaning that we did not consider systematic reviews that were restricted only to specific subpopulations (eg, defined based on a specific geographical area or age group).

Data Extraction Process

For the initial data extraction performed on all systematic reviews that passed full-text screening, pairs of reviewers (V.S. and J.B., V.S. and K.Z., W.R.C. and O.H.J., K.Z. and S.G., F.W. and M.R.S., V.S. and F.W., and V.S. and S.L.) independently extracted descriptive data (listed in the eMethods in Supplement 1), representing the basis for choosing those systematic reviews to be included for detailed data extraction (as described in the Selection of Systematic Reviews subsection). Furthermore, for the largest systematic reviews (as defined in the Selection of Systematic Reviews subsection), paired independent reviewers (V.S. and J.B., V.S. and K.Z., W.R.C. and O.H.J., K.Z. and S.G., F.W. and M.R.S., V.S. and F.W., and V.S. and S.L.) performed a detailed data extraction (listed in the eMethods in Supplement 1). Any inconsistencies in the data extraction were resolved by a third author (O.K.-F., S.M.G., or C.O.). We used predesigned forms that were piloted initially on a small number of included studies. We contacted authors for missing outcome data or in case of unclear information.

Study Outcomes

Our primary aim was to examine the efficacy and safety of antidepressants in the treatment of comorbid depression. The primary outcome was antidepressant efficacy, defined as improvement on a depression rating scale during the trial (eg, the Hamilton Depression Rating Scale [HDRS]). Key secondary outcomes were (1) antidepressant acceptability, defined as all-cause discontinuation, and (2) antidepressant tolerability, defined as discontinuation for adverse effects. Additional secondary outcomes included (1) study-defined antidepressant response (eg, as ≥50% improvement on the HDRS); (2) study-defined depression remission (eg, ≤7 points on the 17-item HDRS); (3) study discontinuation for intolerability, inefficacy, and nonadherence; and (4) at least 1 adverse event as well as specific adverse events, including suicidal behavior, suicide, and death. Our secondary aim was to examine the efficacy of antidepressants in preventing comorbid depression. The primary outcome was the occurrence of comorbid depression as defined in the specific (network) meta-analyses.

Critical Appraisal of Methodological Quality

For systematic reviews included in the detailed data extraction, we applied A Measurement Tool for the Assessment of Multiple Systematic Reviews (AMSTAR)–2 (scores range from 0-16, with higher scores indicating better quality of systematic reviews), which allows measurement of the quality of the methodology of systematic reviews,¹¹ and AMSTAR-Content (scores range from 0-9, with higher scores indicating the quality of RCTs in meta-analyses), which allows measurement of the quality of the included RCTs in systematic reviews.¹⁰ We present both AMSTAR-2 quality and AMSTAR-Content ratings of each included systematic review. The rating was performed independently by pairs of reviewers (V.S. and J.B., V.S. and K.Z., W.R.C. and O.H.J., K.Z. and S.G., F.W. and M.R.S., V.S. and F.W., and V.S. and S.L.), and discrepant scores were resolved by a third reviewer (O.K.-F., S.M.G., or C.O.). We calculated the mean scores across the included systematic review for the AMSTAR-2 quality and AMSTAR-Content to investigate whether there were limitations in the quality of the conducted systematic reviews and/or the included RCTs as done previously.¹⁰

Methods for Evidence Synthesis

We summarized the evidence from several (network) meta-analyses in different medical diseases using random-effects meta-analyses to present the standardized mean difference (SMD) for continuous measures (ie, efficacy) and risk ratios (RRs) for binary measures (eg, response or remission) from the newest or largest (network) meta-analysis within each medical disease. We converted all odds ratios (ORs) to RRs using a standard formula.¹² To pool the meta-analysis estimates from (network) meta-analyses (eg, the overall SMD from all [network] meta-analyses or an SMD for specific disease groups, such as cardiology or pain), we used the DerSimonian-Laird estimator. From (network) meta-analyses, we extracted effect sizes from each specific comparison of an antidepressant vs placebo. We used the I² test to quantify the degree of heterogeneity. Stata, version 14.0 (StataCorp LLC) was used for all analyses. Additional analyses and deviations from the protocol are described in the eMethods in Supplement 1. Two-sided P < .05 indicated statistical significance.

Results

We identified 6587 references, of which 263 publications underwent full-text screening. Of those, 176 systematic reviews (including 45 Cochrane reviews) covering 43 medical diseases (Table) were eligible for initial data extraction (ie, a mean of 4.1 [range, 1-40] systematic reviews per medical disease). Figure 1 presents the study flowchart; eTable 4 in Supplement 2, the specific exclusion criteria for the 87 excluded studies; and eTable 5 in Supplement 2, the detailed bibliographic information for the included 176 systematic reviews. Most of the systematic reviews were performed in neurological (n = 79), cardiological (n = 18), and oncological (n = 20) diseases (Table). Descriptive information for all 176 systematic reviews is presented in eTable 6 in Supplement 2. Based on these descriptive data, we identified the largest systematic reviews within each medical disease. Data on primary and secondary outcome measures for these 73 systematic reviews^{13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83} are presented in eTable 7 in Supplement 2 for treatment of depression and in eTable 8 in Supplement 2 for prevention of depression.

Table. Number of Systematic Reviews on Antidepressant Treatment of Comorbid Depression in Medical Diseases.

Medical disease	No. of systematic reviews	No. of Cochrane reviews	Meta-analysis performed^a
All	176	45	NA
Neurology	79^b	14	Yes
ALS	1	0	No
Multiple sclerosis	2	1	Yes
Parkinson disease	15	1	Yes
Stroke	40	10	Yes
Traumatic brain injury	15	0	Yes
Epilepsy	3	2	No
Huntington disease	2	0	No
Cancer	20^b	4	Yes
Lung	1	0	No
Breast	2	0	Yes
Brain	3	2	No
Cardiology	18	2
Acute coronary syndrome	4	0	No
Coronary artery disease	5	2	Yes
Coronary heart disease	2	0	Yes
Heart failure	4	0	Yes
Ischemic heart disease	1	0	Yes
Myocardial infarction	1	0	Yes
Cardiac rehabilitation	1	0	Yes
Fibromyalgia	8	2	Yes
Rheumatoid arthritis	2	1	Yes
Pain	7	2
Phantom limb pain	1	1	No
Noncardiac chest pain	1	0	Yes
Neuropathic pain	1	0	Yes
Low back pain, chronic	1	0	Yes
Low back pain, nonspecific	2	1	Yes
Functional chest pain	1	0	Yes
Diabetes	7	1	Yes
Hepatitis C virus and interferon alfa	7	0	No
HIV	4	1	Yes
Tinnitus	4	3	No
Palliative	2	0	No
Chronic physical illness	4	2	Yes
Axis III disorder	1	0	Yes
Pulmonary diseases	3	1
Asthma	1	0	Yes
COPD	1	1	Yes
Tuberculosis	1	0	No
IBD	3	1	Yes
PCOS	1	1	No
PMS	1	0	No
Overweight	2	1	No
Dialysis	1	1	No
Kidney disease	2	1	No

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Abbreviations: ALS, amyotrophic lateral sclerosis; COPD, chronic obstructive pulmonary disease; IBD, inflammatory bowel disease; NA, not applicable; PCOS, polycystic ovary syndrome; PMS, premenstrual syndrome.

^{^a}

Whether the newest or largest systematic review identified a sufficient number of randomized controlled trials (RCTs) to perform meta-analyses. The number of RCTs and patients represent those RCTs that studied the effect of antidepressant drugs in medical diseases. All meta-analyses within the specific medical diseases were based on fewer RCTs and patients, as many RCTs did not report necessary data.

^{^b}

Most systematic reviews on cancer included all patients with cancer (ie, independent of the cancer site), while 6 systematic reviews investigated specific cancer types (ie, breast, brain, and lung). In neurology, 1 systematic review included all neurological diseases, which is why the number of the systematic reviews in the specific neurological diseases adds up to 78 and not 79.

Figure 1. — *ICD-10* indicates *International Statistical Classification of Diseases and Related Health Problems, Tenth Revision*; WHO ATC, World Health Organization Anatomical Therapeutic Chemical Code.

^aeTable 4 in Supplement 2 presents the specific exclusion criteria for each of the 87 systematic reviews that were excluded during full-text screening.

^bOf the 165 systematic reviews, several were on the same medical disease. Therefore, we included only the largest systematic review for quantitative synthesis.

AMSTAR-2 quality and AMSTAR-Content ratings were conducted for those 73 systematic reviews included in the detailed data extraction (the specific item scores and total scores are presented in eTable 9 in Supplement 2), of which 52 performed meta-analyses. The mean (SD) AMSTAR-2 quality rating score across these 52 meta-analyses was 9.3 (3.1 [range, 1.5-15.0]) of a maximum of 16, indicating that the meta-analyses were of moderate to good quality. In contrast, the mean (SD) AMSTAR-Content score was 2.4 (1.9 [range, 0-8.0]) of a maximum of 9, indicating that the included original RCTs were of low quality.

Systematic reviews in 16 of the 43 medical diseases contained insufficient RCTs to perform (network) meta-analyses (Table). Of the 27 medical diseases in which quantitative measures were presented, 23 meta-analyses presented SMDs on the antidepressant effect vs placebo (ie, our primary outcome measure). Those 23 (network) meta-analyses were published between 2008 and 2022 and included 1 to 26 RCTs and 30 to 1986 patients. The overall SMD from these 23 meta-analyses was 0.42 (95% CI, 0.30-0.54; I² = 76.5%), favoring antidepressants over placebo in reducing depressive symptoms but with large heterogeneity between the disease groups (Figure 2A) (SMD range, 0.11 [95% CI, −0.02 to 0.25] to 0.79 [95% CI, 0.57-1.01]) and within specific medical diseases (Figure 2B) (SMDs, 0.06 [95% CI, 0.17-0.39] for lower back pain; 0.08 [95% CI, −0.28 to 0.45] for traumatic brain injury; 0.83 [95% CI, 0.32-1.33] for coronary artery disease; 0.87 [95% CI, 0.08-1.67] for functional chest pain; and 1.38 [95% CI, 0.82-1.93] for myocardial infarction). Compared with placebo, antidepressants were associated with better rates of response (8 meta-analyses; overall RR, 1.54 [95% CI, 1.14-1.94]; I² = 69.3%) (eFigure 1 in Supplement 1) and remission (6 meta-analyses; RR, 1.43 [95% CI, 1.25-1.61]; I² = 0%) (eFigure 2 in Supplement 1).

Figure 2. — Weights (size of diamond markers) are determined by random-effects analyses. AMSTAR indicates A Measurement Tool for the Assessment of Multiple Systematic Reviews; CAD, coronary artery disease; CHD, coronary heart disease; COPD, chronic obstructive pulmonary disease; HF, heart failure; IBD, inflammatory bowel disease; IHD, ischemic heart disease; MI, myocardial infarction; MS, multiple sclerosis; NR, not reported; RCTs (as defined in Figure 3), randomized controlled trials; and TBI, traumatic brain injury. The overall SMD of 0.42 in part A is based on all specific meta-analyses presented in part B, with part A furthermore presenting the pooled SMDs within each disease category (eg, the pooled SMD for pain in part B is based on the 4 meta-analyses with pain as the disease group from part B).

Regarding key secondary outcomes, acceptability-related (24 meta-analyses; RR, 1.17 [95% CI, 1.02-1.32]; I² = 59.2%) and tolerability-related (18 meta-analyses; RR, 1.39 [95% CI, 1.13-1.64]; I² = 49.8%) discontinuation risks were higher with antidepressants compared with placebo (Figure 3). Occurrence of any adverse effect was also significantly more likely with antidepressants (10 meta-analyses; RR, 1.22 [95% CI, 1.06-1.38]; I² = 29.7%) (eFigure 3 in Supplement 1). Regarding specific adverse events, antidepressants had increased risks for sexual dysfunction (RR, 2.33 [95% CI, 1.04-3.62]; I² = 0%), dry mouth (RR, 2.12 [95% CI, 1.41-2.83]; I² = 0%), and nausea (RR, 1.70 [95% CI, 1.07-2.33]; I² = 0%) compared with placebo (eFigure 4 in Supplement 1).

Figure 3. — Acceptability is measured by all-cause discontinuation of study medication; tolerability is measured by discontinuation of study medication due to adverse effects. Weights (size of markers) are determined by random-effects analyses. AMSTAR indicates A Measurement Tool for the Assessment of Multiple Systematic Reviews; IBD, inflammatory bowel disease; IHD, ischemic heart disease; NR, not reported; RCTs, randomized controlled trials; SSRI, selective serotonin reuptake inhibitor; and TCA, tricyclic antidepressant. If no specific antidepressant drug is mentioned (eg, SSRI), then the analyses were not restricted to specific antidepressants but could cover all antidepressants.

In additional analyses, the primary efficacy estimates were not significantly associated with the Cochrane vs non-Cochrane systematic reviews (eFigure 5 in Supplement 1) nor with the number of RCTs, publication year, or AMSTAR-Quality scores (eFigure 6 in Supplement 1). However, there were statistically significant associations between a larger sample size and higher AMSTAR Content scores with lower SMDs (eFigure 6 in Supplement 1). Few (network) meta-analyses identified data for direct comparisons between antidepressant groups and specific antidepressants, with all analyses indicating no differences between antidepressants except for paroxetine outperforming fluoxetine in patients with coronary artery disease and amitriptyline outperforming duloxetin in fibromyalgia (eFigure 7 in Supplement 1). Estimates of the specific antidepressants and antidepressant groups are presented in eFigure 8 in Supplement 1.

Of 10 systematic reviews studying antidepressants in the prevention of depression (eTable 8 in Supplement 2), 7 meta-analyses assessed antidepressant efficacy compared with placebo (Figure 4). These reviews were published between 2014 and 2021 and ranged from 2 to 13 RCTs and 147 to 1352 patients. Across medical diseases, antidepressant treatment was associated with an overall 57% reduced risk of developing depression (RR, 0.43 [95% CI, 0.33-0.53]; I² = 20.9%) compared with placebo.

Figure 4. — Weights (size of markers) are determined by random-effects analyses. AD indicates antidepressant; HCV, hepatitis C virus; IFN-α, Interferon alfa; RCTs, randomized controlled trials; SSRIs, selective serotonin reuptake inhibitors; and TBI, traumatic brain injury.

Discussion

This umbrella systematic review and meta-analysis provides 5 main findings. First, antidepressants were more efficacious compared with placebo (with a small to medium effect size) and led to higher response and remission rates. Second, antidepressants were associated with higher acceptability-related and tolerability-related discontinuation rates and a higher risk for any adverse event. Third, effect sizes for antidepressant efficacy varied considerably across specific comorbid medical diseases. Fourth, in patients with medical diseases, antidepressants prevented depression with an overall risk reduction of 57%. Finally, our quality appraisal indicated that the systematic reviews were of moderate quality, but the included RCTs often were of low quality.

The effect sizes observed were in a range similar to those reported by an earlier meta-analyses for antidepressants in patients with MDD but without medical comorbidity.⁵ However, the evidence base for comorbid depression generally rests on smaller and more heterogeneous trials. In MDD without medical comorbidity, more and larger RCTs have been performed (the efficacy SMDs for the specific antidepressants ranged from 0.17 to 0.48 in the most recent meta-analysis⁵). Accordingly, our overall SMD of 0.42 (range, 0.11-0.66) indicates comparable efficacy of antidepressants vs placebo in patients with medical diseases and comorbid depression.

Additionally, Cipriani et al⁵ reported ORs for acceptability ranging from 0.84 to 1.30 for specific antidepressants. This fits well with the RR of 1.17 (95% CI, 1.02-1.32) for acceptability of antidepressants vs placebo in our current analysis. Also, antidepressants were less tolerable than placebo in the meta-analysis,⁵ with ORs ranging from 1.21 to 4.44 for specific antidepressants. Again, this is compatible with our findings of worse tolerability of antidepressants compared to placebo with an RR of 1.39 (95% CI, 1.13-1.64). The adverse effects that occurred more often with antidepressants compared with placebo in patients with depression and medical diseases encompassed dry mouth, nausea, and sexual dysfunction, all of which are well-known adverse effects of antidepressants.⁸⁴ Therefore, as a broad conclusion, clinicians can expect that antidepressants are about equally efficacious and safe in patients with depression with and without medical diseases.

Importantly, effect sizes for antidepressant efficacy varied considerably across specific comorbid medical diseases, with SMDs ranging from 0.06 in chronic low back pain⁷⁰ to 1.38 after myocardial infarction⁷² (Figure 2B). We did not find any association between the effect size and the number of RCTs, publication year, or AMSTAR-2 quality score of the included meta-analyses (eFigure 6 in Supplement 1). This would argue for disease-specific rather than methodological reasons for differences in the effect sizes of antidepressants. For example, it is possible that the effects of antidepressants are smaller in more chronic conditions (such as chronic low back pain) compared with diseases with an acute onset (such as myocardial infarction). However, the quality of the RCTs that informed the meta-analyses was mostly low, as indicated by a mean AMSTAR-Content score of 2.4 on a scale ranging from 0 to 9. Furthermore, some meta-analyses were based on very limited RCTs with few participants. For example, the meta-analysis in chronic low back pain with the smallest effect size is based on 2 RCTs and 132 patients, whereas the meta-analysis in myocardial infarction with the largest effect size consists of 10 RCTs with 280 participants. Therefore, we would caution not to overinterpret differences across medical diseases at this stage of the data. As is so often the case, large confirmatory controlled trials in different medical diseases are needed to answer the question whether antidepressants systematically differ in their efficacy and safety across medical diseases.

In several medical diseases, we identified many systematic reviews. For example, we identified 79 systematic reviews in neurology covering a maximum of 25 RCTs, and 40 systematic reviews were published specifically in stroke covering a maximum of 10 RCTs. Hence, more systematic reviews than RCTs have been published in some medical diseases. This result emphasizes the need for large, well-conducted RCTs studying antidepressants for comorbid depression in medical diseases. Importantly, the prescription rate of antidepressants ranges from about 15% in patients with acute coronary syndrome⁶ or cancer⁷ to 35% in patients with stroke⁸ and 42% in patients with colon cancer.⁸⁵ In other words, millions of people with a medical disease are being treated with antidepressants worldwide. Clearly, these treatment approaches need to be informed by larger and better trials.

There was an overall 57% reduced risk of developing depression in patients with a medical disease when they were treated preventively with antidepressants. However, preventive effects of antidepressants were tested in only a few medical diseases. Thus, more research is needed for such preventive approaches in individual patients with a high risk of developing a depressive episode (eg, those with a history of depressive episodes).⁸⁶ However, the potential preventive efficacy should be weighed against potential adverse effects associated with antidepressants. For example, a Cochrane review found that selective serotonin reuptake inhibitors prevented depression within 12 months after stroke but were associated with an increased risk of bone fractures and seizures.⁴²

Strengths and Limitations

Strengths of our analysis include the comprehensive and in-depth approach and formally assessing the quality of the systematic reviews and of the included RCTs. Limitations include those of the included systematic reviews and RCTs, that is, primarily the small number of RCTs and the absence of large RCTs to yield robust efficacy estimates. Second, most of the meta-analyses pooled all antidepressants with only a few analyses of specific antidepressants or antidepressant groups. Hence, it is currently not possible to make recommendations for specific antidepressants, pointing to the need for future RCTs comparing specific antidepressants head-to-head. Additionally, many systematic reviews did not report several important aspects (eg, sex, age, antidepressant dose or duration, depression scores, absolute numbers, and risk reduction rates). Accordingly, we were unable to study potential moderators of efficacy, to examine whether the absolute decrease in depression scores differed between comorbid depression and MDD without medical comorbidity,⁵ or to calculate the number needed to treat or number needed to harm. Third, several systematic reviews did not report tolerability, acceptability, and adverse effects, limiting detailed analyses on these important aspects. Fourth, we only considered evidence from (network) meta-analyses, meaning that we did not include evidence from RCTs that have not yet been meta-analyzed. Fifth, 2 network meta-analyses included 3-armed RCTs, meaning that the placebo was not independent because the placebo group was used repeatedly.

Conclusions

Despite the paucity of large and well-conducted RCTs studying antidepressants for comorbid depression in medical diseases, this umbrella systematic review and meta-analysis demonstrates that antidepressants are efficacious and safe for comorbid depression in medical diseases, with effect sizes that are similar to those reported for antidepressants in MDD without medical comorbidity. Furthermore, antidepressants can prevent the development of depression in some medical diseases, but this finding should be weighed against potential adverse effects. It is important to screen for and manage comorbid depression in patients with medical diseases, and clinicians should choose treatments based on patient preferences and the antidepressant’s risk-benefit ratio. Future large, high-quality RCTs should include head-to-head comparisons between antidepressants to expand the knowledge on potential differences in efficacy and safety between antidepressants for depression comorbid with medical diseases and to allow more specific treatment recommendations for distinct medical diseases.

Supplement 1.

eMethods. Search Strategy, Data Extraction, Additional Analyses, and Protocol Deviations

eTable 1. PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) 2015 Checklist: Recommended Items to Address in a Systematic Review Protocol

eTable 2. PRISMA 2020 (Preferred Reporting Items for Systematic Review and Meta-Analysis) Checklist

eTable 3. PRISMA 2020 (Preferred Reporting Items for Systematic Review and Meta-Analysis) for Abstract Checklist

eFigure 1. Risk Ratios for Antidepressant Response, Compared With Placebo, for Comorbid Depression in Medical Diseases

eFigure 2. Risk Ratios for Antidepressant Remission, Compared With Placebo, for Comorbid Depression in Medical Diseases

eFigure 3. Risk Ratios for at Least 1 Adverse Event During Antidepressant Treatment, Compared With Placebo, for Comorbid Depression in Medical Diseases

eFigure 4. Risk Ratios for Specific Adverse Events During Antidepressant Treatment, Compared With Placebo, for Comorbid Depression in Medical Diseases

eFigure 5. Standardized Mean Differences (SMDs) of Antidepressant Efficacy for Comorbid Depression in Patients With Medical Diseases, Divided Into Whether the SRs Were Cochrane or Non-Cochrane Systematic Reviews (SRs)

eFigure 6. Standardized Mean Differences (SMDs) of Antidepressant Efficacy for Comorbid Depression in Patients With Medical Diseases, Sorted by (1) No. of RCTs, (2) No. of Patients, (3) Publication Year, (4) AMSTAR-2 Quality Score, and (5) AMSTAR-Content Score

eFigure 7. Standardized Mean Differences (SMDs) and Risk Ratios (RRs) of Direct Comparisons Between Antidepressant Drugs in Comorbid Depression in Patients With Medical Diseases

eFigure 8. Standardized Mean Differences (SMDs) for Specific Antidepressant Drugs and Antidepressant Groups in Comorbid Depression in Patients With Medical Diseases

Click here for additional data file.^{(1MB, pdf)}

Supplement 2.

eTable 4. Reasons for Exclusion for All the 87 Systematic Reviews That Were Excluded During the Full-Text Screening Phase

eTable 5. Bibliographic Data for All 176 Identified Systematic Reviews That Were Identified During the Full-Text Screening Phase

eTable 6. Descriptive Information From All 176 Identified Systematic Reviews That Were Identified During the Full-Text Screening Phase

eTable 7. Detailed Information on Primary and Secondary Outcome Measures From the 73 Systematic Reviews Representing the Newest or Largest Cochrane and Non-Cochrane Systematic Reviews on the Treatment of Depression in Each Medical Disease

eTable 8. Detailed Information on Primary and Secondary Outcome Measures From the 73 Systematic Reviews Representing the Newest or Largest Cochrane and Non-Cochrane Systematic Reviews on the Prevention of Depression in Each Medical Disease

eTable 9. Detailed Information on AMSTAR-2 Quality and AMSTAR-Content Ratings From the 73 Systematic Reviews Representing the Newest or Largest Cochrane and Non-Cochrane Systematic Reviews on the Treatment or Prevention in Each Medical Disease

Click here for additional data file.^{(256.9KB, xlsx)}

Supplement 3.

Data Sharing Statement

Click here for additional data file.^{(16.1KB, pdf)}

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