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Open AccessJournal ArticleDOI

Association of Pharmacological Treatments for Obesity With Weight Loss and Adverse Events: A Systematic Review and Meta-analysis

TLDR
All active agents were associated with significant excess weight loss compared with placebo at 1 year and phentermine-topiramate, naltrexone-bupropion, and liraglutide, each associated with 5% weight loss at 52 weeks, were linked with the highest odds of adverse event-related treatment discontinuation.
Abstract
Importance Five medications have been approved for the management of obesity, but data on comparative effectiveness are limited. Objective To compare weight loss and adverse events among drug treatments for obesity using a systematic review and network meta-analysis. Data Sources MEDLINE, EMBASE, Web of Science, Scopus, and Cochrane Central from inception to March 23, 2016; clinical trial registries. Study Selection Randomized clinical trials conducted among overweight and obese adults treated with US Food and Drug Administration–approved long-term weight loss agents (orlistat, lorcaserin, naltrexone-bupropion, phentermine-topiramate, or liraglutide) for at least 1 year compared with another active agent or placebo. Data Extraction and Synthesis Two investigators identified studies and independently abstracted data using a predefined protocol. A Bayesian network meta-analysis was performed and relative ranking of agents was assessed using surface under the cumulative ranking (SUCRA) probabilities. Quality of evidence was assessed using GRADE criteria. Main Outcomes and Measures Proportions of patients with at least 5% weight loss and at least 10% weight loss, magnitude of decrease in weight, and discontinuation of therapy because of adverse events at 1 year. Results Twenty-eight randomized clinical trials with 29 018 patients (median age, 46 years; 74% women; median baseline body weight, 100.5 kg; median baseline body mass index, 36.1) were included. A median 23% of placebo participants had at least 5% weight loss vs 75% of participants taking phentermine-topiramate (odds ratio [OR], 9.22; 95% credible interval [CrI], 6.63-12.85; SUCRA, 0.95), 63% of participants taking liraglutide (OR, 5.54; 95% CrI, 4.16-7.78; SUCRA, 0.83), 55% taking naltrexone-bupropion (OR, 3.96; 95% CrI, 3.03-5.11; SUCRA, 0.60), 49% taking lorcaserin (OR, 3.10; 95% CrI, 2.38-4.05; SUCRA, 0.39), and 44% taking orlistat (OR, 2.70; 95% CrI, 2.34-3.09; SUCRA, 0.22). All active agents were associated with significant excess weight loss compared with placebo at 1 year—phentermine-topiramate, 8.8 kg (95% CrI, −10.20 to −7.42 kg); liraglutide, 5.3 kg (95% CrI, −6.06 to −4.52 kg); naltrexone-bupropion, 5.0 kg (95% CrI, −5.94 to −3.96 kg); lorcaserin, 3.2 kg (95% CrI, −3.97 to −2.46 kg); and orlistat, 2.6 kg (95% CrI, −3.04 to −2.16 kg). Compared with placebo, liraglutide (OR, 2.95; 95% CrI, 2.11-4.23) and naltrexone-bupropion (OR, 2.64; 95% CrI, 2.10-3.35) were associated with the highest odds of adverse event–related treatment discontinuation. High attrition rates (30%-45% in all trials) were associated with lower confidence in estimates. Conclusions and Relevance Among overweight or obese adults, orlistat, lorcaserin, naltrexone-bupropion, phentermine-topiramate, and liraglutide, compared with placebo, were each associated with achieving at least 5% weight loss at 52 weeks. Phentermine-topiramate and liraglutide were associated with the highest odds of achieving at least 5% weight loss.

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References
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Measuring inconsistency in meta-analyses

TL;DR: A new quantity is developed, I 2, which the authors believe gives a better measure of the consistency between trials in a meta-analysis, which is susceptible to the number of trials included in the meta- analysis.
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Bias in meta-analysis detected by a simple, graphical test

TL;DR: Funnel plots, plots of the trials' effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials.
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Meta-Analysis in Clinical Trials*

TL;DR: This paper examines eight published reviews each reporting results from several related trials in order to evaluate the efficacy of a certain treatment for a specified medical condition and suggests a simple noniterative procedure for characterizing the distribution of treatment effects in a series of studies.
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Inference from Iterative Simulation Using Multiple Sequences

TL;DR: The focus is on applied inference for Bayesian posterior distributions in real problems, which often tend toward normal- ity after transformations and marginalization, and the results are derived as normal-theory approximations to exact Bayesian inference, conditional on the observed simulations.
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