Abstract
BackgroundWhile placebo-controlled randomised controlled trials remain the standard way to evaluate drugs for efficacy, historical data are used extensively across the development cycle. This ranges from supplementing contemporary data to increase the power of trials to cross-trial comparisons in estimating comparative efficacy. In many cases, these approaches are performed without in-depth review of the context of data, which may lead to bias and incorrect conclusions.MethodsWe discuss the original ‘Pocock’ criteria for the use of historical data and how the use of historical data has evolved over time. Based on these factors and personal experience, we created a series of questions that may be asked of historical data, prior to their use. Based on the answers to these questions, various statistical approaches are recommended. The strategy is illustrated with a case study in colorectal cancer.ResultsA number of areas need to be considered with historical data, which we split into three categories: outcome measurement, study/patient characteristics (including setting and inclusion/exclusion criteria), and disease process/intervention effects. Each of these areas may introduce issues if not appropriately handled, while some may preclude the use of historical data entirely. We present a tool (in the form of a table) for highlighting any such issues. Application of the tool to a colorectal cancer data set demonstrates under what conditions historical data could be used and what the limitations of such an analysis would be.ConclusionHistorical data can be a powerful tool to augment or compare with contemporary trial data, though caution is required. We present some of the issues that may be considered when involving historical data and what (if any) statistical approaches may account for differences between studies. We recommend that, where historical data are to be used in analyses, potential differences between studies are addressed explicitly.
Highlights
While placebo-controlled randomised controlled trials remain the standard way to evaluate drugs for efficacy, historical data are used extensively across the development cycle
randomised controlled trials (RCTs) in which all patients are randomised to either the intervention or control treatment are the standard approach for comparing efficacy, there is interest in making use of historical data to reduce the need for contemporary controls
The focus lies on combining historical control patients with patients randomised to the control in the current study
Summary
While placebo-controlled randomised controlled trials remain the standard way to evaluate drugs for efficacy, historical data are used extensively across the development cycle This ranges from supplementing contemporary data to increase the power of trials to cross-trial comparisons in estimating comparative efficacy. Is necessary to obtain a sufficiently powered analysis, due to the limited number of patients available for randomisation In principle, both intervention and control patients of previous studies can be combined with data of the current study. The combination of historical and randomised controls to supplement the analysis of contemporary or future clinical trials was popularised by Pocock.[1] The main concern with the use of historical data is the possibility that the historical studies differ in characteristics with the current study, due to, for example, improvement in supportive care over time, differences in patient selection, and between-centre differences. Previous work has demonstrated substantial bias when comparing the outcomes of comparisons made using observational data to RCTs conducted in the same population.[2,3,4,5,6,7] This finding was quantified in a simulation study.[8]
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