WorldWide Antimalarial Resistance Network (WWARN), Oxford, UK.
Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7FZ, UK.
Malar J. 2017 Oct 26;16(1):430. doi: 10.1186/s12936-017-2074-7.
The Kaplan-Meier (K-M) method is currently the preferred approach to derive an efficacy estimate from anti-malarial trial data. In this approach event times are assumed to be continuous and estimates are generated on the assumption that there is only one cause of failure. In reality, failures are captured at pre-scheduled time points and patients can fail treatment due to a variety of causes other than the primary endpoint, commonly termed competing risk events. Ignoring these underlying assumptions can potentially distort the derived efficacy estimates and result in misleading conclusions. This review details the evolution of statistical methods used to derive anti-malarial efficacy for uncomplicated Plasmodium falciparum malaria and assesses the limitations of the current practices. Alternative approaches are explored and their implementation is discussed using example data from a large multi-site study.
Kaplan-Meier（K-M）法目前是从抗疟试验数据中得出疗效估计的首选方法。在这种方法中，假设事件时间是连续的，并且在只有一个失败原因的假设下生成估计值。实际上，失败是在预定的时间点捕获的，并且患者可能由于除主要终点以外的多种原因而无法完成治疗，通常称为竞争风险事件。忽略这些基本假设可能会扭曲得出的疗效估计值，并导致误导性结论。本综述详细介绍了用于推导无并发症恶性疟原虫疟疾抗疟疗效的统计方法的演变，并评估了当前实践的局限性。还探讨了替代方法，并使用来自大型多地点研究的示例数据讨论了它们的实施。
