Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria

Pitfalls and challenges

Prabin Dahal, Julie A. Simpson, Grant Dorsey, Philippe J. Guérin, Ric N. Price, Kasia Stepniewska

    Research output: Contribution to journalReview articleResearchpeer-review

    Abstract

    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.

    Original languageEnglish
    Article number430
    Pages (from-to)1-14
    Number of pages14
    JournalMalaria Journal
    Volume16
    DOIs
    Publication statusPublished - 26 Oct 2017

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    Falciparum Malaria
    Antimalarials
    Therapeutics

    Cite this

    Dahal, Prabin ; Simpson, Julie A. ; Dorsey, Grant ; Guérin, Philippe J. ; Price, Ric N. ; Stepniewska, Kasia. / Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria : Pitfalls and challenges. In: Malaria Journal. 2017 ; Vol. 16. pp. 1-14.
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    abstract = "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.",
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    Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria : Pitfalls and challenges. / Dahal, Prabin; Simpson, Julie A.; Dorsey, Grant; Guérin, Philippe J.; Price, Ric N.; Stepniewska, Kasia.

    In: Malaria Journal, Vol. 16, 430, 26.10.2017, p. 1-14.

    Research output: Contribution to journalReview articleResearchpeer-review

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    T2 - Pitfalls and challenges

    AU - Dahal, Prabin

    AU - Simpson, Julie A.

    AU - Dorsey, Grant

    AU - Guérin, Philippe J.

    AU - Price, Ric N.

    AU - Stepniewska, Kasia

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