No improvement in the reporting of clinical trial subgroup effects in high-impact general medical journals

Gabler, Nicole B.; Duan, Naihua; Raneses, Eli; Suttner, Leah; Ciarametaro, Michael; Cooney, Elizabeth; Dubois, Robert W.; Halpern, Scott D.; Kravitz, Richard L.

doi:10.1186/s13063-016-1447-5

Cited by 37 publications

(36 citation statements)

References 30 publications

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“…A proposal by Kent and colleagues offers a framework for assessing and reporting multivariate risk‐based heterogeneity in treatment effects that can be applied to a wide variety of conditions . Although this framework has yet to be applied widely , there is increasing support for updating the conventional methods for evaluating treatment efficacy in order to appreciate the known heterogeneity in clinical trials . The manner in which data are presented and interpreted is vital to understanding variability in response and may help differentiate statistically significant findings from clinically meaningful outcomes.…”

Section: Discussionmentioning

confidence: 99%

Heterogeneity in Response to Treatment of Adolescents with Severe Obesity: The Need for Precision Obesity Medicine

Ryder

Kaizer

Jenkins

et al. 2019

Obesity

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Objective: Treating pediatric severe obesity is challenging because of the complex biological, behavioral, and environmental factors that underpin the disease. The multifactorial etiology of obesity combined with the physiologic complexity of the energy regulatory system contributes to treatment variability. The goal of this secondary analysis of pooled data was to describe the degree of individual variation in response to various interventions among adolescents with severe obesity. Methods: Data from three centers across the United States conducting either lifestyle (n = 53), pharmacotherapy (n = 40), or metabolic and bariatric surgery (n = 78) interventions were pooled. Inclusion criteria were severe obesity at baseline and at least one follow-up visit > 30 days after treatment start. Results: Change in BMI following intervention ranged from −50.2% to +12.9%, with each intervention (lifestyle [range: −25.4% to 5.0%], pharmacotherapy [range: −10.8% to 12.9%], and metabolic and bariatric surgery [range: −50.2% to −13.3%]) exhibiting wide individual variation in response. Changes in cardiometabolic risk factors demonstrated similarly high variability.Conclusions: Adolescents with severe obesity demonstrated a high degree of heterogeneity in terms of BMI reduction and cardiometabolic risk factor response across treatment modalities. Reporting individual response data in trials and identifying factors driving variability in response will be vital for advancing precision medicine approaches to address obesity.

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Section: Discussionmentioning

confidence: 99%

Heterogeneity in Response to Treatment of Adolescents with Severe Obesity: The Need for Precision Obesity Medicine

Ryder

Kaizer

Jenkins

et al. 2019

Obesity

View full text Add to dashboard Cite

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“…The problem caused by the unbalanced groups can be minimized by using multivariate analyses that include the most relevant factors associated with the benefit. This would be the best method for performing subgroup analysis; unfortunately, it is little used, or studies that used it are not published …”

Section: What's Known and Objectivementioning

confidence: 99%

“…An increasing number of publications perform subgroup analyses without detailed evaluation . Our easy‐to‐use checklist allows assessment of reliability and applicability of subgroup analyses that my help in the comprehensive evaluation of drugs and health interventions.…”

Section: ‘What's New?’ and Conclusionmentioning

confidence: 99%

Checklist for clinical applicability of subgroup analysis

et al. 2019

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What is known and objective: Subgroup analysis plays an important role in clinical decision-making. Correct management of subgroup analysis is necessary to optimize effectiveness, safety and efficiency of treatments. No homogeneous criteria have been developed for interpretation of subgroup analysis. In this study, the researcher develops a checklist to evaluate the reliability and applicability of the results of subset analyses. Methods: With a review of previous literature, three main criteria were included in the checklist: statistical association, biological plausibility and consistency among studies. Statistical association considered interaction probability, prespecification of analysis, number of subgroups analysed, sample size and positive/negative result in global analysis. Each item was given an indicative score. Total score was related to a level of applicability for the results in clinical practice. Checklist validation included interinvestigator concordance and assessment about utility. Three drug examples were used to validate the tool.Results and discussion: Twenty-six evaluators showed adequate interinvestigator concordance (kappa 0.79, 1 and 0.83 for each drug example regarding applicability). Kappa values increased to 0.94, 1 and 1 after group discussion. Checklist utility score was greater than 4.7/5 in three drug examples. In pre-analysis, inter-researcher agreement on global applicability recommendation of subgroup results to practice was 92.3% (ramucirumab), 96% (nivolumab) and 100% (mepolizumab). In post-analysis, inter-researcher agreement on applicability recommendation of subgroup results was 100%, 94.45% and 100%, respectively. The checklist validation shows a high interindividual agreement of the results, both with respect to the evaluation of the applicability of subgroup analysis and concerning clinical decision-making. What is new and conclusion:We have developed the first validated tool for interpretation of subgroup analyses. The checklist contributes to the adoption of homogeneous criteria for subgroup analyses, thereby allowing discussion and evaluation of the effects of a health intervention. K E Y W O R D S checklist, clinical decision-making, data interpretation, drug evaluation, statistical, subgroup analysis, validation studies | 531 GIL-SIERRA Et AL. How to cite this article: Gil-Sierra MD, Fénix-Caballero S, Abdel kader-Martin L, et al. Checklist for clinical applicability of subgroup analysis. J Clin Pharm Ther. 2020;45:530-538.

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“…regarding the conduct, reporting, and interpretation of subgroup analyses in clinical trials [9e12]. Recent studies found that there has been no improvement in the reporting of subgroup analyses [13,14], and that there were discrepancies between subgroup analyses planned in protocols and journal publications of clinical trials [15]. Many journals have been accepting and publishing clinical trial protocols so as to promote public access to them [16,17].…”

Section: What Is the Implication And What Should Change Now?mentioning

confidence: 99%

Justification and reporting of subgroup analyses were lacking or inadequate in randomized controlled trials

Fan

Bachmann

2019

Journal of Clinical Epidemiology

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Objectives: The aim of the article was to assess the appropriateness and rationales of subgroup analyses planned in protocols of randomized controlled trials and reported in subsequent corresponding trial publications. Study Design and Setting: We searched PubMed to identify trial protocols published in journals during 2006e2017. From a total of 3,774 initially identified records, we included a random sample of 479 protocols and identified 280 trial publications corresponding to the included protocols. Results: Subgroup analyses were specified in 19% of the protocols and reported in 21% of the trial publications. Of the 94 protocols with planned subgroup analyses, 32% mentioned testing for interaction, and only three considered statistical power. Subgroup analyses were not prespecified in 56% of the 59 trial publications with subgroup analyses. Subgroup analyses were stated as prespecified in nine trial publications, without support evidence from the corresponding protocols. Subgroup analyses were often reported insufficiently for assessing the consistency of subgroup effects across studies. Justifications for subgroup analyses were provided in only four trial protocols and seven trial publications. Conclusion: Inappropriate specification and reporting of subgroup analyses remain problematic in protocols and reports of randomized controlled trials. Justifications or rationales for subgroup analyses were only rarely provided in trial protocols and reports.

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No improvement in the reporting of clinical trial subgroup effects in high-impact general medical journals

Cited by 37 publications

References 30 publications

Heterogeneity in Response to Treatment of Adolescents with Severe Obesity: The Need for Precision Obesity Medicine

Heterogeneity in Response to Treatment of Adolescents with Severe Obesity: The Need for Precision Obesity Medicine

Checklist for clinical applicability of subgroup analysis

Justification and reporting of subgroup analyses were lacking or inadequate in randomized controlled trials

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