Summarizing historical information on controls in clinical trials
- 6 January 2010
- journal article
- Published by SAGE Publications in Clinical Trials
- Vol. 7 (1), 5-18
- https://doi.org/10.1177/1740774509356002
Abstract
Background Historical information is always relevant when designing clinical trials, but it might also be incorporated in the analysis. It seems appropriate to exploit past information on comparable control groups. Purpose Phase IV and proof-of-concept trials are used to discuss aspects of summarizing historical control data as prior information in a new trial. The importance of a fair assessment of the similarity of control parameters is emphasized. Methods The methodology is meta-analytic-predictive. Heterogeneity of control parameters is expressed via the between-trial variation, which is the key parameter determining the prior effective sample size and its upper bound (prior maximum sample size). Results For a Phase IV trial (930 control patients in 11 historical trials) between-trial heterogeneity was fairly small, resulting in a prior effective sample size of approximately 90 patients. For a proof-of-concept trial (363 patients in four historical trials) heterogeneity was moderate to substantial, resulting in a prior effective sample size of approximately 20. For another proof-of-concept trial (14 patients in one historical trial), assuming substantial heterogeneity implied a prior effective sample size of 7. The prior effective sample size can only be large if the amount of historical data is large and between-trial heterogeneity is small. The prior effective sample size is bounded by the prior maximum sample size (ratio of within- to between-trial variance), irrespective of the amount of historical data. Limitations The meta-analytic-predictive approach assumes exchangeability of control parameters across trials. Due to the difficulty to quantify between-trial variability, sensitivity of conclusions regarding assumptions and type of inference should be assessed. Conclusions The use of historical control information is a valuable option and may lead to more efficient clinical trials. The proposed approach is attractive for nonconfirmatory trials, but under certain circumstances extensions to the confirmatory setting could be envisaged as well. Clinical Trials 2010; 7: 5—18. http://ctj.sagepub.comKeywords
This publication has 52 references indexed in Scilit:
- A Re-Evaluation of Random-Effects Meta-AnalysisJournal of the Royal Statistical Society Series A: Statistics in Society, 2008
- Bias Modelling in Evidence SynthesisJournal of the Royal Statistical Society Series A: Statistics in Society, 2008
- Determining the Effective Sample Size of a Parametric PriorBiometrics, 2008
- Daclizumab, a humanised monoclonal antibody to the interleukin 2 receptor (CD25), for the treatment of moderately to severely active ulcerative colitis: a randomised, double blind, placebo controlled, dose ranging trialGut, 2006
- Bayesian random effects meta‐analysis of trials with binary outcomes: methods for the absolute risk difference and relative risk scalesStatistics in Medicine, 2002
- Advanced methods in meta‐analysis: multivariate approach and meta‐regressionStatistics in Medicine, 2002
- Meta-Analysis of Migraine Headache Treatments: Combining Information from Heterogeneous DesignsJournal of the American Statistical Association, 1999
- Using Historical Controls to Adjust for Covariates in Trend Tests for Binary DataJournal of the American Statistical Association, 1998
- Meta-analysis in clinical trialsControlled Clinical Trials, 1986
- Combining Historical and Randomized Controls for Assessing Trends in ProportionsJournal of the American Statistical Association, 1983