Matching-adjusted indirect comparison for survival data analysis:implementation in R language
With the increase in the number of single-arm clinical trials and lack of head-to-head clinical studies,the application of unadjusted indirect comparisons and network meta-analysis methods has been limited.Matching-adjusted indirect comparison(MAIC)is an alternative method to fully utilize individual patient data from one study and balance potential bias caused by baseline characteristics differences in different trials through propensity score matching with aggregated data reported in other studies,and complete the comparison of the efficacy between target interventions.This study introduced the concept and principles of MAIC.In addition,we demonstrated how to use the anchored MAIC method based on R language for survival data,which has been widely used in anti-cancer drug evaluation.This study aimed to provide an alternative method to inform evidence-based decisions.
R languageMatching-adjusted indirect comparisonsSurvival data
万方数据
维普
