Abstract
After the completion of a clinical study for the drug efficacy and safety, subgroup analyses are typically conducted. The analyses may yield supportive information for the main finding based on the overall population, or generate new hypotheses on the drug effect for further investigation. Although there are valid reasons to perform subgroup analyses, the warning has been given to caution the interpretation of subgroup results. There is a general doubt on the believability of subgroup analysis because of the potential confounding and uncertainty related to subgroup findings which could be anti-intuitive, inconsistent, unexpected, or unexplainable. The present work is to discuss potential sources of confounding in subgroup analyses which may bias interpretations and lead to erroneous claims. Solutions to the problem are discussed. A special attention is paid to the use of the intensive randomization stratification to improve the quality and believability of subgroup analyses.
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References
Antman EM et al (2006) Enoxaparin versus unfractionated heparin with fibrinolysis for st-elevation myocardial infarction. NEJM 354:1477–1488
Ashley EA (2015) The precision medicine initiative - a new national effort. JAMA 313:2119–2101
Cui L, Hung HMJ, Wang SJ (1999) Modification of sample size in group sequential clinical trials. Biometrics 55(3):853–857
Cui L, Hung HMJ, Wang SJ, Tsong Y (2002) Issues related to subgroup analysis in clinical trials. J Biopharm Stat 12:347–358
Cui L, Zhang L, Yang B (2017) Optimal adaptive group sequential trial design with flexible timing of sample size determination. Contemp Clin Trials 63:8–12
Dmitrienko A, Tamhane AC, Bretz F (2009) Multiple testing problems in pharmaceutical statistics, 1st edn. Chapman and Hall/CRC
European Carotid Surgery Trialists’ Collaborative Group (1998) Randomised trial of endarterectomy for recently symptomatic carotid stenosis: final results of the MRC European Carotid Surgery Trial (ECST). Lancet 351:1379–1387
Hallstrom A, Davis K (1988) Imbalance in treatment assignments in stratified blocked randomization. Control Clin Trials 9:375–382
ISIS-2 Collaborative Group (1988) Randomized trial of intravenous streptokinase, oral aspirin, both or neither among 17817 cases of suspected acute myocardial infarction: ISIS-2. Lancet 332:349–360
Kernan W, Viscoli C, Makuch R, Brass L, Horwitz R (1999) Stratified randomization for clinical trials. J Clin Epidemiol 52:19–26
Lehmacher W, Wassmer G (1999) Adaptive sample size calculations in group sequential trials. Biometrics 55(4):1286–1290
Peto R (2011) Current misconception 3: that subgroup-specific trial mortality results often provide a good basis for individualising patient care. Br J Cancer 104:1057–1058
Pocock S, Simon R (1975) Sequential treatment assignment with balancing for prognostic factors in the controlled clinical trial. Biometrics 31:103–115
Rothwell PM (2005) Treating individuals 2. Subgroup analysis in randomised controlled trials: importance, indications, and interpretation. Lancet 365:176–186
Sleight P (2000) Subgroup analysis in clinical trial: fun to look at – but don’t believe them! Curr Control Trials Cardiovasc Med 1:25–27
Sun X, Briel M, Walter SD, Guyatt GH (2010) Is a subgroup effect believable? Updating criteria to evaluate the credibility of subgroup analyses. BMJ 340:c117
Sun X et al (2012) Credibility of claims of subgroup effects in randomised controlled trials: systematic review. BMJ 344:e1553
Therneau TM (1993) How many stratification factors are “too many” to use in a randomization plan? Control Clin Trials 14:98–108
Umbricht D et al (2014) Effect of bitopertin, a glycine reuptake inhibitor, on negative symptoms of schizophrenia a randomized, double-blind, proof-of-concept study. JAMA Psychiatry 71:637–646
Wang R, Lagakos S, Ware J, Hunter D, Drazen J (2007a) Statistics in medicine — reporting of subgroup analyses in clinical trials. N Engl J Med 357:2189–2194
Wang SJ, O’Neill R, Hung HMJ (2007b) Approaches to evaluation of treatment effect in randomized clinical trials with genomic subset. Pharm Stat 6:227–244
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Cui, L., Xu, T., Zhang, L. (2020). Issues Related to Subgroup Analyses and Use of Intensive Stratification. In: Ting, N., Cappelleri, J., Ho, S., Chen, (G. (eds) Design and Analysis of Subgroups with Biopharmaceutical Applications. Emerging Topics in Statistics and Biostatistics . Springer, Cham. https://doi.org/10.1007/978-3-030-40105-4_1
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DOI: https://doi.org/10.1007/978-3-030-40105-4_1
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