Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria: pitfalls and challenges

Malaria Journal

Review

Julie A. Simpson¹  Grant Dorsey²  Prabin Dahal³  Philippe J. Guérin³  Kasia Stepniewska³  Ric N. Price⁴ 

[1] Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia;Department of Medicine, University of California, San Francisco, CA, USA;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, OX3 7FZ, Oxford, UK;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, OX3 7FZ, Oxford, UK;Global and Tropical Health Division, Menzies School of Health Research and Charles Darwin University, Darwin, Australia;

关键词: Plasmodium falciparum;    Kaplan–Meier;    Cumulative incidence function;    Competing risks;    Comparative studies;   

DOI  :  10.1186/s12936-017-2074-7

 received in 2017-03-17, accepted in 2017-10-19,  发布年份 2017

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY   
© The Author(s) 2017

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