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Use of recursive partitioning analysis in clinical trials and meta-analysis of randomized clinical trials, 1990-2016

Abstract:

Background: Recursive Partitioning Analysis (RPA) is a very flexible non parametric algorithm that allows classification of individuals according to certain criteria, particularly in clinical trials, the method is used to pbkp_redict response to treatment or classify individuals according to prognostic factors. Objectives: In this paper we examine how often RPA is used in clinical trials and in meta-analysis. Methods: We reviewed abstracts published between 1990 and 2016, and extracted data regarding clinical trial phase, year of publication, type of treatment, medical indication and main evaluated endpoints. Results: One hundred and eighty three studies were identified; of these 43 were meta-analyses and 23 were clinical trials. Most of the studies were published between 2011 and 2016, for both clinical trials and meta-analyses of randomized clinical trials. The pbkp_rediction of overall survival and progression free survival were the outcomes most evaluated, at 43.5% and 51.2% respectively. Regarding the use of RPA in clinical trials, the brain was the most common site studied, while for meta-analytic studies, other cancer sites were also studied. The combination of chemotherapy and radiation was seen frequently in clinical trials. Conclusion: Recursive partitioning analysis is a very easy technique to use, and it could be a very powerful tool to pbkp_redict response in different subgroups of patients, although it is not widely used in clinical trials.