title: Cumulative subgroup analysis to reduce waste in clinical research for individualised medicine.
abstract: BACKGROUND
  Although subgroup analyses in clinical trials may provide evidence for individualised medicine, their conduct and interpretation remain controversial.
  
  
  METHODS
  Subgroup 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.
  
  
  RESULTS
  In 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.
  
  
  CONCLUSIONS
  To 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.
authors.affiliation: Norwich Medical School, Faculty of Medicine and Health Science, University of East Anglia, Research Park, Norwich, Norfolk, NR4 7TJ, UK. fujian.song@uea.ac.uk.
authors.forename: Fujian
authors.initials: F
authors.lastname: Song
authors.affiliation: Norwich Medical School, Faculty of Medicine and Health Science, University of East Anglia, Research Park, Norwich, Norfolk, NR4 7TJ, UK.
authors.forename: Max O
authors.initials: MO
authors.lastname: Bachmann
mesh_terms: D035843:Biomedical Research / Q000379:methods* / Q000592:standards*; D003627:Data Interpretation, Statistical; D006801:Humans; D015201:Meta-Analysis as Topic; D057285:Precision Medicine; D016032:Randomized Controlled Trials as Topic
keywords: Cumulative meta-analysis; Individual patient data; Individualised medicine; Randomised controlled trials; Subgroup analysis