Impact of trial attrition rates on treatment effect estimates in chronic inflammatory diseases: A meta-epidemiological study

IF 5 2区生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Research Synthesis Methods Pub Date : 2024-02-13 DOI:10.1002/jrsm.1708

Silja H. Overgaard, Caroline M. Moos, John P. A. Ioannidis, George Luta, Johannes I. Berg, Sabrina M. Nielsen, Vibeke Andersen, Robin Christensen

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Abstract

The objective of this meta-epidemiological study was to explore the impact of attrition rates on treatment effect estimates in randomised trials of chronic inflammatory diseases (CID) treated with biological and targeted synthetic disease-modifying drugs. We sampled trials from Cochrane reviews. Attrition rates and primary endpoint results were retrieved from trial publications; Odds ratios (ORs) were calculated from the odds of withdrawing in the experimental intervention compared to the control comparison groups (i.e., differential attrition), as well as the odds of achieving a clinical response (i.e., the trial outcome). Trials were combined using random effects restricted maximum likelihood meta-regression models and associations between estimates of treatment effects and attrition rates were analysed. From 37 meta-analyses, 179 trials were included, and 163 were analysed (301 randomised comparisons; n = 62,220 patients). Overall, the odds of withdrawal were lower in the experimental compared to control groups (random effects summary OR = 0.45, 95% CI, 0.41–0.50). The corresponding overall treatment effects were large (random effects summary OR = 4.43, 95% CI 3.92–4.99) with considerable heterogeneity across interventions and clinical specialties (I² = 85.7%). The ORs estimating treatment effect showed larger treatment benefits when the differential attrition was more prominent with more attrition in the control group (OR = 0.73, 95% CI 0.55–0.96). Higher attrition rates from the control arm are associated with larger estimated benefits of treatments with biological or targeted synthetic disease-modifying drugs in CID trials; differential attrition may affect estimates of treatment benefit in randomised trials.

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试验减员率对慢性炎症性疾病治疗效果估计值的影响：一项荟萃流行病学研究。

本项荟萃流行病学研究的目的是探讨自然减员率对慢性炎症性疾病（CID）生物和靶向合成疾病调节药物随机试验治疗效果估计值的影响。我们从科克伦综述中抽取了试验样本。我们从试验出版物中检索了自然减员率和主要终点结果；根据试验干预组与对照对比组相比的退出几率（即不同自然减员率）以及获得临床反应的几率（即试验结果）计算出了比值比（OR）。使用随机效应限制最大似然元回归模型对试验进行合并，并分析治疗效果估计值与自然减员率之间的关联。37 项元分析共纳入 179 项试验，分析了 163 项试验（301 项随机比较；n = 62,220 名患者）。总体而言，与对照组相比，实验组的戒断几率较低（随机效应汇总 OR = 0.45，95% CI，0.41-0.50）。相应的总体治疗效果较大（随机效应总结 OR = 4.43，95% CI 3.92-4.99），不同干预措施和临床专科之间存在相当大的异质性（I2 = 85.7%）。治疗效果的 OR 估计值显示，当对照组自然减员较多、差异化较明显时，治疗效果较好（OR = 0.73，95% CI 0.55-0.96）。在CID试验中，对照组较高的自然减员率与生物或靶向合成改良疾病药物治疗的较大估计收益有关；不同的自然减员率可能会影响随机试验中治疗收益的估计值。

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来源期刊

Research Synthesis Methods MATHEMATICAL & COMPUTATIONAL BIOLOGYMULTID-MULTIDISCIPLINARY SCIENCES

CiteScore

16.90

自引率

3.10%

发文量

期刊介绍： Research Synthesis Methods is a reputable, peer-reviewed journal that focuses on the development and dissemination of methods for conducting systematic research synthesis. Our aim is to advance the knowledge and application of research synthesis methods across various disciplines. Our journal provides a platform for the exchange of ideas and knowledge related to designing, conducting, analyzing, interpreting, reporting, and applying research synthesis. While research synthesis is commonly practiced in the health and social sciences, our journal also welcomes contributions from other fields to enrich the methodologies employed in research synthesis across scientific disciplines. By bridging different disciplines, we aim to foster collaboration and cross-fertilization of ideas, ultimately enhancing the quality and effectiveness of research synthesis methods. Whether you are a researcher, practitioner, or stakeholder involved in research synthesis, our journal strives to offer valuable insights and practical guidance for your work.