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BMC Medicine

, 14:197

First Online: 15 December 2016Received: 19 September 2016Accepted: 09 November 2016DOI: 10.1186-s12916-016-0744-x

Cite this article as: Song, F. & Bachmann, M.O. BMC Med 2016 14: 197. doi:10.1186-s12916-016-0744-x

Abstract

BackgroundAlthough subgroup analyses in clinical trials may provide evidence for individualised medicine, their conduct and interpretation remain controversial.

MethodsSubgroup effect can be defined as the difference in treatment effect across patient subgroups. Cumulative subgroup analysis refers to a series of repeated pooling of subgroup effects after adding data from each of related trials chronologically, to investigate the accumulating evidence for subgroup effects. We illustrated the clinical relevance of cumulative subgroup analysis in two case studies using data from published individual patient data IPD meta-analyses. Computer simulations were also conducted to examine the statistical properties of cumulative subgroup analysis.

ResultsIn case study 1, an IPD meta-analysis of 10 randomised trials RCTs on beta blockers for heart failure reported significant interaction of treatment effects with baseline rhythm. Cumulative subgroup analysis could have detected the subgroup effect 15 years earlier, with five fewer trials and 71% less patients, than the IPD meta-analysis which first reported it. Case study 2 involved an IPD meta-analysis of 11 RCTs on treatments for pulmonary arterial hypertension that reported significant subgroup effect by aetiology. Cumulative subgroup analysis could have detected the subgroup effect 6 years earlier, with three fewer trials and 40% less patients than the IPD meta-analysis. Computer simulations have indicated that cumulative subgroup analysis increases the statistical power and is not associated with inflated false positives.

ConclusionsTo reduce waste of research data, subgroup analyses in clinical trials should be more widely conducted and adequately reported so that cumulative subgroup analyses could be timely performed to inform clinical practice and further research.

KeywordsSubgroup analysis Individual patient data Cumulative meta-analysis Randomised controlled trials Individualised medicine AbbreviationsIPDIndividual patient data

OROdds ratio

PAHPulmonary arterial hypertension

RCTRandomised controlled trial

RHRRatio of hazard ratios

RORRatio of odds ratios

Electronic supplementary materialThe online version of this article doi:10.1186-s12916-016-0744-x contains supplementary material, which is available to authorized users.

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Autor: Fujian Song - Max O. Bachmann

Fuente: https://link.springer.com/







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