Topic
Subgroup analysis
About: Subgroup analysis is a research topic. Over the lifetime, 2728 publications have been published within this topic receiving 61965 citations.
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TL;DR: Clinical trials need a predefined statistical analysis plan for uses of baseline data, especially covariate-adjusted analyses and subgroup analyses, and investigators and journals need to adopt improved standards of statistical reporting, and exercise caution when drawing conclusions from subgroup findings.
1,055 citations
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TL;DR: Fixed-dose combination decreases the risk of medication non-compliance and should be considered in patients with chronic conditions like hypertension for improving medication compliance which can translate into better clinical outcomes.
982 citations
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TL;DR: Key issues include: the overuse and overinterpretation of subgroup analyses; the underuse of appropriate statistical tests for interaction; inconsistencies in the use of covariate-adjustment; the lack of clear guidelines on covariate selection; the over use of baseline comparisons in some studies; the misuses of significance tests for baseline comparability, and the need for trials to have a predefined statistical analysis plan.
Abstract: Clinical trial investigators often record a great deal of baseline data on each patient at randomization When reporting the trial's findings such baseline data can be used for (i) subgroup analyses which explore whether there is evidence that the treatment difference depends on certain patient characteristics, (ii) covariate-adjusted analyses which aim to refine the analysis of the overall treatment difference by taking account of the fact that some baseline characteristics are related to outcome and may be unbalanced between treatment groups, and (iii) baseline comparisons which compare the baseline characteristics of patients in each treatment group for any possible (unlucky) differences This paper examines how these issues are currently tackled in the medical journals, based on a recent survey of 50 trial reports in four major journals The statistical ramifications are explored, major problems are highlighted and recommendations for future practice are proposed Key issues include: the overuse and overinterpretation of subgroup analyses; the underuse of appropriate statistical tests for interaction; inconsistencies in the use of covariate-adjustment; the lack of clear guidelines on covariate selection; the overuse of baseline comparisons in some studies; the misuses of significance tests for baseline comparability, and the need for trials to have a predefined statistical analysis plan for all these uses of baseline data
980 citations
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TL;DR: Subgroup analyses are important if there are potentially large differences between groups in the risk of a poor outcome with or without treatment, if there is potential heterogeneity of treatment effect in relation to pathophysiology, or ifthere are practical questions about when to treat.
850 citations
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TL;DR: Guidelines are provided in this paper that will assist clinicians in making decisions regarding whether to base a treatment decision on overall results or on the results of a subgroup analysis.
Abstract: The extent to which a clinician should believe and act on the results of subgroup analyses of data from randomized trials or meta-analyses is controversial. Guidelines are provided in this paper for making these decisions. The strength of inference regarding a proposed difference in treatment effect among subgroups is dependent on the magnitude of the difference, the statistical significance of the difference, whether the hypothesis preceded or followed the analysis, whether the subgroup analysis was one of a small number of hypotheses tested, whether the difference was suggested by comparisons within or between studies, the consistency of the difference, and the existence of indirect evidence that supports the difference. Application of these guidelines will assist clinicians in making decisions regarding whether to base a treatment decision on overall results or on the results of a subgroup analysis.
806 citations