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Background The introduction of new therapy modalities has significantly improved the outcome of aplastic anemia (AA) and paroxysmal nocturnal hemoglobinuria (PNH) patients. However, relatively little is known about the exact disease burden of AA/PNH since standardized assessments of symptoms including health-related quality of life (HRQoL) are frequently missing or inadequately designed for this rare patient group. We aimed to develop AA/PNH-specific questionnaires for self-reporting of symptoms, which could be included in electronic platforms for data collection and patient care. Methods By scoping review, we extracted any reported symptoms in AA/PNH and their prevalence from the literature (Phase I). Consensus rounds with patients and medical experts were conducted to identify core symptoms reported in the literature and to add missing items (Phase II). Ultimately, AA/PNH-specific patient-reported outcome (PRO) questionnaires including the selected measures were designed (Phase III). Results AA symptoms from 62 and PNH symptoms from 45 observational studies were extracted from the literature. Twenty-four patients and seven medical experts identified 11 core symptoms including HRQoL issues after three consensus rounds. Significant differences in the symptom ranking of patients versus medical experts could be observed. Therefore, patient- as well as expert-centered PRO questionnaires in AA and PNH were created following the concepts of validated instruments. Conclusion The development of symptom self-reporting questionnaires for AA and PNH was feasible and the disease-specific PRO questionnaires can now be validated within a web-based workflow in a subsequent feasibility study.

Objectives: We aimed to provide a systematic overview of freely available tools which may help plan or monitor costs for randomized clinical trials (RCTs). Study Design and Setting: We systematically searched MEDLINE, EMBASE, and EconLit and conducted internet searches via Google (last search, October 2018). We included all freely available tools and determined their specific purpose, which parts of clinical trial projects and which types of costs they covered, and if they were user-tested or validated in any form. Results: We identified 25 available tools. Most tools were downloadable on websites from institutions related to clinical research. Seven tools were developed to plan the budget for an entire RCT, 17 tools for calculating budgets of an individual trial center, and one tool for monitoring costs of ongoing RCTs. Eighteen tools considered fixed, variable, and indirect costs. Only two tools were clearly user-tested or validated. Conclusion: Several freely available tools aim to support investigators in planning costs of an entire trial or in planning the budget for a clinical trial site. How valid and useful they are remains to be shown for most of them. Future tools should be openly shared, user-tested, and validated.

Background The necessity of antibiotic prophylaxis for postoperative urinary tract infections (UTIs) after transurethral resection of bladder tumours is controversial. This potentially leads to the overuse of antibiotic prophylaxis and rising antimicrobial resistance rates. The objective of this systematic review and meta-analysis is to compare the impact of different antimicrobial prophylaxis schemes versus placebo on the prevention of postoperative UTI and asymptomatic bacteriuria. Methods We designed and registered a study protocol for a systematic review and meta-analysis of randomized controlled trials and non-randomized (e.g. cohort, case-control) studies examining any form of antibiotic prophylaxis in patients with transurethral resection of bladder tumours. Literature searches will be conducted in several electronic databases (from inception onwards), including MEDLINE (Ovid), EMBASE (Ovid), and the Cochrane Central Register of Controlled Trials (CENTRAL). Grey literature will be identified through searching conference abstracts. The primary outcome will be postoperative urinary tract infections. The secondary outcome will be asymptomatic bacteriuria. Two reviewers will independently screen all citations, full-text articles, and abstract data. Potential conflicts will be resolved through discussion. The study methodological quality (or bias) will be appraised using appropriate tools (e.g. Risk of Bias 2.0 tool and Newcastle-Ottawa Scale). If feasible, we will conduct random-effects meta-analysis of outcome data. Additional analyses will be conducted to explore the potential sources of heterogeneity (e.g. study design, publication year, the setting of the study, and antibiotics regimen). We will also search, identify, and discuss potential risk factors for urinary tract infections following transurethral resection of bladder tumours. This may serve as basis for a scoping review. Discussion In times of rising antimicrobial resistance rates, sound evidence on the necessity of antibiotic prophylaxis is essential for implementation into guideline recommendations and for decision-making in clinical practice. Systematic review registration PROSPERO, CRD42019131733

Background: Never before have clinical trials drawn as much public attention as those testing interventions for COVID-19. We aimed to describe the worldwide COVID-19 clinical research response and its evolution over the first 100 days of the pandemic. Methods: Descriptive analysis of planned, ongoing or completed trials by April 9, 2020 testing any intervention to treat or prevent COVID-19, systematically identified in trial registries, preprint servers, and literature databases. A survey was conducted of all trials to assess their recruitment status up to July 6, 2020. Results: Most of the 689 trials (overall target sample size 396,366) were small (median sample size 120; interquartile range [IQR] 60-300) but randomized (75.8%; n=522) and were often conducted in China (51.1%; n=352) or the USA (11%; n=76). 525 trials (76.2%) planned to include 155,571 hospitalized patients, and 25 (3.6%) planned to include 96,821 health-care workers. Treatments were evaluated in 607 trials (88.1%), frequently antivirals (n=144) or antimalarials (n=112); 78 trials (11.3%) focused on prevention, including 14 vaccine trials. No trial investigated social distancing. Interventions tested in 11 trials with >5,000 participants were also tested in 169 smaller trials (median sample size 273; IQR 90-700). Hydroxychloroquine alone was investigated in 110 trials. While 414 trials (60.0%) expected completion in 2020, only 35 trials (4.1%; 3,071 participants) were completed by July 6. Of 112 trials with detailed recruitment information, 55 had recruited Conclusions: The size and speed of the COVID-19 clinical trials agenda is unprecedented. However, most trials were small investigating a small fraction of treatment options. The feasibility of this research agenda is questionable, and many trials may end in futility, wasting research resources. Much better coordination is needed to respond to global health threats.

Objectives The objective of this study was to assess the agreement of treatment effect estimates from meta-analyses based on abbreviated or comprehensive literature searches. Study Design and Setting This was a meta-epidemiological study. We abbreviated 47 comprehensive Cochrane review searches and searched MEDLINE/Embase/CENTRAL alone, in combination, with/without checking references (658 new searches). We compared one meta-analysis from each review with recalculated ones based on abbreviated searches. Results The 47 original meta-analyses included 444 trials (median 6 per review [interquartile range (IQR) 3–11]) with 360045 participants (median 1,371 per review [IQR 685–8,041]). Depending on the search approach, abbreviated searches led to identical effect estimates in 34–79% of meta-analyses, to different effect estimates with the same direction and level of statistical significance in 15–51%, and to opposite effects (or effects could not be estimated anymore) in 6–13%. The deviation of effect sizes was zero in 50% of the meta-analyses and in 75% not larger than 1.07-fold. Effect estimates of abbreviated searches were not consistently smaller or larger (median ratio of odds ratio 1 [IQR 1–1.01]) but more imprecise (1.02–1.06-fold larger standard errors). Conclusion Abbreviated literature searches often led to identical or very similar effect estimates as comprehensive searches with slightly increased confidence intervals. Relevant deviations may occur.

Objectives Off-label drug use is highly prevalent but controversial and often discouraged assuming generally inferior medical effects associated with off-label use. Study Design and Setting We searched PubMed, MEDLINE, PubMed Health, and the Cochrane Library up to May 2015 for systematic reviews including meta-analyses of randomized clinical trials (RCTs) comparing off-label and approved drugs head-to-head in any population and on any medical outcome. We combined the comparative effects in meta-analyses providing summary odds ratios (sOR) for each treatment comparison and outcome, and then calculated an overall summary of the sOR across all comparisons (ssOR). Results We included 25 treatment comparisons with 153 RCTs and 24,592 patients. In six of 25 comparisons (24%), off-label drugs were significantly superior (five of 25) or inferior (one of 25) to approved treatments. There was substantial statistical heterogeneity across comparisons (I2 = 43%). Overall, off-label drugs were more favorable than approved treatments (ssOR 0.72; 95% CI = 0.54–0.95). Analyses of patient-relevant outcomes were similar (statistical significant differences in 24% (six of 25); ssOR 0.74; 95% CI = 0.56–0.98; I2 = 60%). Analyses of primary outcomes of the systematic reviews (n = 22 comparisons) indicated less heterogeneity and no statistically significant difference overall (ssOR 0.85; 95% CI = 0.67–1.06; I2 = 0%). Conclusion Approval status does not reliably indicate which drugs are more favorable in situations with clinical trial evidence comparing off-label with approved use. Drug effectiveness assessments without considering off-label use may provide incomplete information. To ensure that patients receive the best available care, funding, policy, reimbursement, and treatment decisions should be evidence based considering the entire spectrum of available therapeutic choices.

Background & aims Wilson disease (WD) is a rare disorder of copper metabolism. The objective of this systematic review was to determine the comparative effectiveness and safety of common treatments of WD. Methods We included WD patients of any age or stage and the study drugs D-penicillamine, zinc salts, trientine and tetrathiomolybdate. The control could be placebo, no treatment or any other treatment. We included prospective, retrospective, randomized and non-randomized studies. We searched Medline and Embase via Ovid, the Cochrane Central Register of Controlled Trials, and screened reference lists of included articles. Where possible, we applied random-effects meta-analyses. Results The 23 included studies reported on 2055 patients and mostly compared D-penicillamine to no treatment, zinc, trientine or succimer. One study compared tetrathiomolybdate and trientine. Post-decoppering maintenance therapy was addressed in one study only. Eleven of 23 studies were of low quality. When compared to no treatment, D-penicillamine was associated with a lower mortality (odds ratio 0.013; 95% CI 0.0010 to 0.17). When compared to zinc, there was no association with mortality (odds ratio 0.73; 95% CI 0.16 to 3.40) and prevention or amelioration of clinical symptoms (odds ratio 0.84; 95% CI 0.48 to 1.48). Conversely, D-penicillamine may have a greater impact on side effects and treatment discontinuations than zinc. Conclusions There are some indications that zinc is safer than D-penicillamine therapy while being similarly effective in preventing or reducing hepatic or neurological WD symptoms. Study quality was low warranting cautious interpretation of our findings.

Objectives To evaluate how estimated treatment effects agree between nonrandomized studies using causal modeling with marginal structural models (MSM-studies) and randomized trials (RCTs). Study Design Meta-epidemiological study. Setting MSM-studies providing effect estimates on any healthcare outcome of any treatment were eligible. We systematically sought RCTs on the same clinical question and compared the direction of treatment effects, effect sizes, and confidence intervals. Results The main analysis included 19 MSM-studies (1,039,570 patients) and 141 RCTs (120,669 patients). MSM-studies indicated effect estimates in the opposite direction from RCTs for eight clinical questions (42%), and their 95% CI (confidence interval) did not include the RCT estimate in nine clinical questions (47%). The effect estimates deviated 1.58-fold between the study designs (median absolute deviation OR [odds ratio] 1.58; IQR [interquartile range] 1.37 to 2.16). Overall, we found no systematic disagreement regarding benefit or harm but confidence intervals were wide (summary ratio of odds ratios [sROR] 1.04; 95% CI 0.88 to 1.23). The subset of MSM-studies focusing on healthcare decision-making tended to overestimate experimental treatment benefits (sROR 1.44; 95% CI 0.99 to 2.09). Conclusion Nonrandomized studies using causal modeling with MSM may give different answers than RCTs. Caution is still required when nonrandomized “real world” evidence is used for healthcare decisions.

Objective The objective of the study was to systematically survey the methodological literature and collect suggested criteria for assessing the credibility of effect modification and associated rationales. Study Design and Setting We searched MEDLINE, Embase, and WorldCat up to March 2018 for publications providing guidance for assessing the credibility of effect modification identified in randomized trials or meta-analyses. Teams of two investigators independently identified eligible publications and extracted credibility criteria and authors’ rationale, reaching consensus through discussion. We created a taxonomy of criteria that we iteratively refined during data abstraction. Results We identified 150 eligible publications that provided 36 criteria and associated rationales. Frequent criteria included significant test for interaction (n = 54), a priori hypothesis (n = 49), providing a causal explanation (n = 47), accounting for multiplicity (n = 45), testing a small number of effect modifiers (n = 38), and prespecification of analytic details (n = 39). For some criteria, we found more than one rationale; some criteria were connected through a common rationale. For some criteria, experts disagreed regarding their suitability (e.g., added value of stratified randomization; trustworthiness of biologic rationales). Conclusion Methodologists have expended substantial intellectual energy providing criteria for critical appraisal of apparent effect modification. Our survey highlights popular criteria, expert agreement and disagreement, and where more work is needed, including testing criteria in practice.

Objective To compare effect estimates of randomised clinical trials that use routinely collected data (RCD-RCT) for outcome ascertainment with traditional trials not using routinely collected data. Design Meta-research study. Data source Studies included in the same meta-analysis in a Cochrane review. Eligibility criteria for study selection Randomised clinical trials using any type of routinely collected data for outcome ascertainment, including from registries, electronic health records, and administrative databases, that were included in a meta-analysis of a Cochrane review on any clinical question and any health outcome together with traditional trials not using routinely collected data for outcome measurement. Review methods Effect estimates from trials using or not using routinely collected data were summarised in random effects meta-analyses. Agreement of (summary) treatment effect estimates from trials using routinely collected data and those not using such data was expressed as the ratio of odds ratios. Subgroup analyses explored effects in trials based on different types of routinely collected data. Two investigators independently assessed the quality of each data source. Results 84 RCD-RCTs and 463 traditional trials on 22 clinical questions were included. Trials using routinely collected data for outcome ascertainment showed 20% less favourable treatment effect estimates than traditional trials (ratio of odds ratios 0.80, 95% confidence interval 0.70 to 0.91, I 2 =14%). Results were similar across various types of outcomes (mortality outcomes: 0.92, 0.74 to 1.15, I 2 =12%; non-mortality outcomes: 0.71, 0.60 to 0.84, I 2 =8%), data sources (electronic health records: 0.81, 0.59 to 1.11, I 2 =28%; registries: 0.86, 0.75 to 0.99, I 2 =20%; administrative data: 0.84, 0.72 to 0.99, I 2 =0%), and data quality (high data quality: 0.82, 0.72 to 0.93, I 2 =0%). Conclusions Randomised clinical trials using routinely collected data for outcome ascertainment show smaller treatment benefits than traditional trials not using routinely collected data. These differences could have implications for healthcare decision making and the application of real world evidence.

Key Points Question What are the available data on cancer treatment outcomes for new cancer therapies approved by the US Food and Drug Administration? Findings In this comparative effectiveness study of 92 novel cancer therapies approved for 100 indications over 17 years, 44% of drug approvals were based on data from nonrandomized clinical trials. Randomized clinical trials typically reported that these drugs were associated with substantial tumor responses and delays in the time to progression or death, but the median absolute increase in overall survival was only 2 months. Meaning This study’s findings indicate that, at the time of drug approval, limited supporting data are available to decision-makers, and the increase in overall survival associated with new cancer drugs is typically small., Importance Clinical trial evidence used to support drug approval is typically the only information on benefits and harms that patients and clinicians can use for decision-making when novel cancer therapies become available. Various evaluations have raised concern about the uncertainty surrounding these data, and a systematic investigation of the available information on treatment outcomes for cancer drugs approved by the US Food and Drug Administration (FDA) is warranted. Objective To describe the clinical trial data available on treatment outcomes at the time of FDA approval of all novel cancer drugs approved for the first time between 2000 and 2016. Design, Setting, and Participants This comparative effectiveness study analyzed randomized clinical trials and single-arm clinical trials of novel drugs approved for the first time to treat any type of cancer. Approval packages were obtained from drugs@FDA, a publicly available database containing information on drug and biologic products approved for human use in the US. Data from January 2000 to December 2016 were included in this study. Main Outcomes and Measures Regulatory and clinical trial characteristics were described. For randomized clinical trials, summary treatment outcomes for overall survival, progression-free survival, and tumor response across all therapies were calculated, and median absolute survival increases were estimated. Tumor types and regulatory characteristics were assessed separately. Results Between 2000 and 2016, 92 novel cancer drugs were approved by the FDA for 100 indications based on data from 127 clinical trials. The 127 clinical trials included a median of 191 participants (interquartile range [IQR], 106-448 participants). Overall, 65 clinical trials (51.2%) were randomized, and 95 clinical trials (74.8%) were open label. Of 100 indications, 44 indications underwent accelerated approval, 42 indications were for hematological cancers, and 58 indications were for solid tumors. Novel drugs had mean hazard ratios of 0.77 (95% CI, 0.73-0.81; I2 = 46%) for overall survival and 0.52 (95% CI, 0.47-0.57; I2 = 88%) for progression-free survival. The median tumor response, expressed as relative risk, was 2.37 (95% CI, 2.00-2.80; I2 = 91%). The median absolute survival benefit was 2.40 months (IQR, 1.25-3.89 months). Conclusions and Relevance In this study, data available at the time of FDA drug approval indicated that novel cancer therapies were associated with substantial tumor responses but with prolonging median overall survival by only 2.40 months. Approval data from 17 years of clinical trials suggested that patients and clinicians typically had limited information available regarding the benefits of novel cancer treatments at market entry., This comparative effectiveness research examines clinical trial data on treatment outcomes used to support US Food and Drug Administration approval of novel cancer therapies that were approved for the first time between 2000 and 2016.

Background The available evidence on the benefits and harms of novel drugs and therapeutic biologics at the time of approval is reported in publicly available documents provided by the US Food and Drug Administration (FDA). We aimed to create a comprehensive database providing the relevant information required to systematically analyze and assess this early evidence in meta-epidemiological research. Methods We designed a modular and flexible database of systematically collected data. We identified all novel cancer drugs and therapeutic biologics approved by the FDA between 2000 and 2016, recorded regulatory characteristics, acquired the corresponding FDA approval documents, identified all clinical trials reported therein, and extracted trial design characteristics and treatment effects. Herein, we describe the rationale and design of the data collection process, particularly the organization of the data capture, the identification and eligibility assessment of clinical trials, and the data extraction activities. Discussion We established a comprehensive database on the comparative effects of drugs and therapeutic biologics approved by the FDA over a time period of 17 years for the treatment of cancer (solid tumors and hematological malignancies). The database provides information on the clinical trial evidence available at the time of approval of novel cancer treatments. The modular nature and structure of the database and the data collection processes allow updates, expansions, and adaption for a continuous meta-epidemiological analysis of novel drugs. The database allows us to systematically evaluate benefits and harms of novel drugs and therapeutic biologics. It provides a useful basis for meta-epidemiological research on the comparative effects of innovative cancer treatments and continuous evaluations of regulatory developments.

BackgroundSubacute cough following a non-specific viral infection lasting 3–8 weeks is common. However, despite many treatment options there are no systematic reviews evaluating these.AimTo provide a systematic overview of treatment options and outcomes evaluated in randomised clinical trials (RCTs).Design and settingSystematic review and meta-analyses assessing the overall effects of any treatment for subacute cough.MethodThe authors systematically searched PubMed/MEDLINE and the Cochrane Central Register of Controlled Trials (last search March 2017) for RCTs in adult patients with subacute cough. The authors considered trials evaluating any outcome of any drug or non-drug treatments, apart from traditional Chinese and Asian medicines. They combined treatment effects on cough-related outcomes in random effects meta-analyses.ResultsSix eligible RCTs including 724 patients were identified. These assessed montelukast, salbutamol plus ipratropium bromide, gelatine, fluticasone propionate, budesonide, and nociception opioid 1 receptor agonist and codeine. Five studies reported effects on various cough severity scores at various timepoints. No treatment option was associated with a clear benefit on cough recovery or other patient-relevant outcomes in any of the studies or in meta-analyses for cough outcomes at 14 days and 28 days. Reported adverse events were rather mild and reported for 14% of patients across all treatments.ConclusionEvidence on treatment options for subacute cough is weak. There is no treatment showing clear patient-relevant benefits in clinical trials.

Objectives To determine how marginal structural models (MSMs), which are increasingly used to estimate causal effects, are used in randomized clinical trials (RCTs) and compare their results with those from intention-to-treat (ITT) or other analyses. Study Design and Setting We searched PubMed, Scopus, citations of key references, and Clinicaltrials.gov. Eligible RCTs reported clinical effects based on MSMs and at least one other analysis. Results We included 12 RCTs reporting 138 analyses for 24 clinical questions. In 19/24 (79%), MSM-based and other effect estimates were all in the same direction, 22/22 had overlapping 95% confidence intervals (CIs), and in 19/22 (86%), the MSM effect estimate lay within all 95% CIs of all other effects (in two cases no CIs were reported). For the same clinical question, the largest effect estimate from any analysis was 1.19-fold (median; interquartile range 1.13-1.34) larger than the smallest. All MSM and ITT effect estimates were in the same direction and had overlapping 95% CIs. In 71% (12/17), they also agreed on the presence of statistical significance. MSM-based effect estimates deviated more from the null than those based on ITT (P = 0.18). The effect estimates of both approaches differed 1.12-fold (median; interquartile range 1.02-1.22). Conclusions MSMs provided largely similar effect estimates as other available analyses. Nevertheless, some of the differences in effect estimates or statistical significance may become important in clinical decision-making, and the multiple estimates require utmost attention of possible selective reporting bias.

There is compelling evidence that published trial information is selectively reported and that results not showing favourable effects of the tested treatments often remain unpublished. Clinical trial information published by regulatory authorities such as the US Food and Drug Administration (FDA) may help to reduce such reporting biases. FDA approval documents are long and do not follow the typical structure of medical journal articles, which may discourage reviewers from using them for evidence syntheses. Our practical guidance on how to efficiently identify and use approval documents to find the relevant information may help promoting the use of this valuable data source for evidence syntheses.

Background Multiple surgical procedures in a single patient are relatively common and lead to dependent (clustered) data. This dependency needs to be accounted for in study design and data analysis. A systematic review was performed to assess how clustered data were handled in inguinal hernia trials. The impact of ignoring clustered data was estimated using simulations. Methods PubMed, Embase and the Cochrane Library were reviewed systematically for RCTs published between 2004 and 2013, including patients undergoing unilateral or bilateral inguinal hernia repair. Study characteristics determining the appropriateness of handling clustered data were extracted. Using simulations, various statistical methods accounting for clustered data were compared with an analysis ignoring clustering by assuming 100 hernias, with a varying percentage of patients having bilateral hernias. Results Of the 50 eligible trials including patients with bilateral hernias, 20 (40 per cent) did not provide information on how they dealt with clustered data and 18 (36 per cent) avoided clustering by assessing the outcome by patient and not by hernia. None of the remaining 12 trials (24 per cent) considered clustering in the design or analysis. In the simulations, ignoring clustering led to an increased type I error rate of up to 12 per cent and to a loss in power of up to 15 per cent, depending on whether the patient or the hernia was the randomization unit. Conclusion Clustering was rarely considered in inguinal hernia trials. The simulations underline the importance of considering clustering as part of the statistical analysis to avoid false-positive and false-negative results, and hence inappropriate study conclusions.

Background and Objective Confounding bias is a most pervasive threat to validity of observational epidemiologic research. We assessed whether authors of observational epidemiologic studies consider confounding bias when interpreting the findings. Study Design and Setting We randomly selected 120 cohort or case–control studies published in 2011 and 2012 by the general medical, epidemiologic, and specialty journals with the highest impact factors. We used Web of Science to assess citation metrics through January 2017. Results Sixty-eight studies (56.7%, 95% confidence interval: 47.8–65.5%) mentioned “confounding” in the Abstract or Discussion sections, another 20 (16.7%; 10.0–23.3%) alluded to it, and there was no mention or allusion at all in 32 studies (26.7%; 18.8–34.6%). Authors often acknowledged that for specific confounders, there was no adjustment (34 studies; 28.3%) or deem it possible or likely that confounding affected their main findings (29 studies; 24.2%). However, only two studies (1.7%; 0–4.0%) specifically used the words “caution” or “cautious” for the interpretation because of confounding-related reasons and eventually only four studies (3.3%; 0.1–6.5%) had limitations related to confounding or any other bias in their Conclusions. Studies mentioning that the findings were possibly or likely affected by confounding were more frequently cited than studies with a statement that findings were unlikely affected (median 6.3 vs. 4.0 citations per year, P = 0.04). Conclusions Many observational studies lack satisfactory discussion of confounding bias. Even when confounding bias is mentioned, authors are typically confident that it is rather irrelevant to their findings and they rarely call for cautious interpretation. More careful acknowledgment of possible impact of confounding is not associated with lower citation impact.

Background Streptococcus pneumoniae is responsible for approximately 1.6 million yearly deaths worldwide. An up-to-date evidence base on the effects of pneumococcal conjugate vaccines (PCVs) on infectious diseases and mortality in any population or setting regardless of age or health status is currently lacking.

Background Colchicine is an anti-inflammatory drug that is used for a wide range of inflammatory diseases. Cardiovascular disease also has an inflammatory component but the effects of colchicine on cardiovascular outcomes remain unclear. Previous safety analyses were restricted to specific patient populations. Objectives To evaluate potential cardiovascular benefits and harms of a continuous long-term treatment with colchicine in any population, and specifically in people with high cardiovascular risk. Search methods We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, ClinicalTrials.gov, WHO International Clinical Trials Registry, citations of key papers, and study references in January 2015. We also contacted investigators to gain unpublished data. Selection criteria Randomised controlled trials (parallel-group or cluster design or first phases of cross-over studies) comparing colchicine over at least six months versus any control in any adult population. Data collection and analysis Primary outcomes were all-cause mortality, myocardial infarction, and adverse events. Secondary outcomes were cardiovascular mortality, stroke, heart failure, non-scheduled hospitalisations, and non-scheduled cardiovascular interventions. We conducted predefined subgroup analyses, in particular for participants with high cardiovascular risk. . Main results We included 39 randomised parallel-group trials with 4992 participants. Colchicine had no effect on all-cause mortality (RR 0.94, 95% CI 0.82 to 1.09; participants = 4174; studies = 30; I² = 27%; moderate quality of evidence). There is uncertainty surrounding the effect of colchicine in reducing cardiovascular mortality (RR 0.34, 95% CI 0.09 to 1.21, I² = 9%; participants = 1132; studies = 7; moderate quality of evidence). Colchicine reduced the risk for total myocardial infarction (RR 0.20, 95% CI 0.07 to 0.57; participants = 652; studies = 2; moderate quality of evidence). There was no effect on total adverse events (RR 1.52, 95% CI 0.93 to 2.46; participants = 1313; studies = 11; I² = 45%; very low quality of evidence) but gastrointestinal intolerance was increased (RR 1.83, 95% CI 1.03 to 3.26; participants = 1258; studies = 11; I² = 74%; low quality of evidence). Colchicine showed no effect on heart failure (RR 0.62, 95% CI 0.10 to 3.88; participants = 462; studies = 3; I² = 45%; low quality of evidence) and no effect on stroke (RR 0.38, 95% CI 0.09 to 1.70; participants = 874; studies = 3; I² = 45%; low quality of evidence). Reporting of serious adverse events was inconsistent; no event occurred over 824 patient-years (4 trials). Effects on other outcomes were very uncertain. Summary effects of RCTs specifically focusing on participants with high cardiovascular risk were similar (4 trials; 1230 participants). Authors' conclusions There is much uncertainty surrounding the benefits and harms of colchicine treatment. Colchicine may have substantial benefits in reducing myocardial infarction in selected high-risk populations but uncertainty about the size of the effect on survival and other cardiovascular outcomes is high, especially in the general population from which most of the studies in our review were drawn. Colchicine is associated with gastrointestinal side effects based on low-quality evidence. More evidence from large-scale randomised trials is needed.

Colchicine is an old anti-inflammatory drug that has shown substantial cardiovascular benefits in recent trials. We systematically reviewed cardiovascular benefits and harms of colchicine in any population and specifically in patients with high cardiovascular risk. We evaluated randomised controlled trials comparing colchicine over at least 6 months versus any control in any adult population. Primary outcomes were all-cause mortality, myocardial infarction and adverse events. Cardiovascular mortality was a secondary outcome. We included 39 trials with 4992 patients. The quality of evidence for mortality outcomes and myocardial infarction was moderate but lower for adverse events. Colchicine had no effect on all-cause mortality (RR 0.94, 95% CI 0.82 to 1.09; I(2)=27%; 30 trials). Cardiovascular mortality was reduced in some but not all meta-analytical models (random-effects RR 0.34, 0.09 to 1.21, I(2)=9%; Peto's OR 0.24, 0.09 to 0.64, I(2)=15%; Mantel-Haenszel fixed-effect RR 0.20, 0.06 to 0.68, I(2)=0%; 7 trials). The risk for myocardial infarction was reduced (RR 0.20, 0.07 to 0.57; 2 trials). There was no effect on total adverse events (RR 1.52, 0.93 to 2.46, I(2)=45%; 11 trials) but gastrointestinal intolerance was increased (RR 1.83, 1.03 to 3.26, I(2)=74%; 11 trials). Reporting of serious adverse events was inconsistent; no event occurred over 824 patient-years (4 trials). Effects in high cardiovascular risk populations were similar (4 trials; 1230 patients). We found no evidence supporting colchicine doses above 1 mg/day. Colchicine may have substantial cardiovascular benefits; however, there is sufficient uncertainty about its benefit and harm to indicate the need for large-scale trials to further evaluate this inexpensive, promising treatment in cardiovascular disease.