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Evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis: a simulation study

BACKGROUND: Antimalarial efficacy studies in patients with uncomplicated Plasmodium falciparum are confounded by a new infection (a competing risk event) since this event can potentially preclude a recrudescent event (primary endpoint of interest). The current WHO guidelines recommend censoring comp...

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Autores principales: Dahal, Prabin, Guerin, Philippe J., Price, Ric N., Simpson, Julie A., Stepniewska, Kasia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525412/
https://www.ncbi.nlm.nih.gov/pubmed/31101088
http://dx.doi.org/10.1186/s12874-019-0748-2
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author Dahal, Prabin
Guerin, Philippe J.
Price, Ric N.
Simpson, Julie A.
Stepniewska, Kasia
author_facet Dahal, Prabin
Guerin, Philippe J.
Price, Ric N.
Simpson, Julie A.
Stepniewska, Kasia
author_sort Dahal, Prabin
collection PubMed
description BACKGROUND: Antimalarial efficacy studies in patients with uncomplicated Plasmodium falciparum are confounded by a new infection (a competing risk event) since this event can potentially preclude a recrudescent event (primary endpoint of interest). The current WHO guidelines recommend censoring competing risk events when deriving antimalarial efficacy. We investigated the impact of considering a new infection as a competing risk event on the estimation of antimalarial efficacy in single-armed and comparative drug trials using two simulation studies. METHODS: The first simulation study explored differences in the estimates of treatment failure for areas of varying transmission intensities using the complement of the Kaplan-Meier (K-M) estimate and the Cumulative Incidence Function (CIF). The second simulation study extended this to a comparative drug efficacy trial for comparing the K-M curves using the log-rank test, and Gray’s k-sample test for comparing the equality of CIFs. RESULTS: The complement of the K-M approach produced larger estimates of cumulative treatment failure compared to the CIF method; the magnitude of which was correlated with the observed proportion of new infection and recrudescence. When the drug efficacy was 90%, the absolute overestimation in failure was 0.3% in areas of low transmission rising to 3.1% in the high transmission settings. In a scenario which is most likely to be observed in a comparative trial of antimalarials, where a new drug regimen is associated with an increased (or decreased) rate of recrudescences and new infections compared to an existing drug, the log-rank test was found to be more powerful to detect treatment differences compared to the Gray’s k-sample test. CONCLUSIONS: The CIF approach should be considered for deriving estimates of antimalarial efficacy, in high transmission areas or for failing drugs. For comparative studies of antimalarial treatments, researchers need to select the statistical test that is best suited to whether the rate or cumulative risk of recrudescence is the outcome of interest, and consider the potential differing prophylactic periods of the antimalarials being compared. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12874-019-0748-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-65254122019-05-24 Evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis: a simulation study Dahal, Prabin Guerin, Philippe J. Price, Ric N. Simpson, Julie A. Stepniewska, Kasia BMC Med Res Methodol Research Article BACKGROUND: Antimalarial efficacy studies in patients with uncomplicated Plasmodium falciparum are confounded by a new infection (a competing risk event) since this event can potentially preclude a recrudescent event (primary endpoint of interest). The current WHO guidelines recommend censoring competing risk events when deriving antimalarial efficacy. We investigated the impact of considering a new infection as a competing risk event on the estimation of antimalarial efficacy in single-armed and comparative drug trials using two simulation studies. METHODS: The first simulation study explored differences in the estimates of treatment failure for areas of varying transmission intensities using the complement of the Kaplan-Meier (K-M) estimate and the Cumulative Incidence Function (CIF). The second simulation study extended this to a comparative drug efficacy trial for comparing the K-M curves using the log-rank test, and Gray’s k-sample test for comparing the equality of CIFs. RESULTS: The complement of the K-M approach produced larger estimates of cumulative treatment failure compared to the CIF method; the magnitude of which was correlated with the observed proportion of new infection and recrudescence. When the drug efficacy was 90%, the absolute overestimation in failure was 0.3% in areas of low transmission rising to 3.1% in the high transmission settings. In a scenario which is most likely to be observed in a comparative trial of antimalarials, where a new drug regimen is associated with an increased (or decreased) rate of recrudescences and new infections compared to an existing drug, the log-rank test was found to be more powerful to detect treatment differences compared to the Gray’s k-sample test. CONCLUSIONS: The CIF approach should be considered for deriving estimates of antimalarial efficacy, in high transmission areas or for failing drugs. For comparative studies of antimalarial treatments, researchers need to select the statistical test that is best suited to whether the rate or cumulative risk of recrudescence is the outcome of interest, and consider the potential differing prophylactic periods of the antimalarials being compared. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12874-019-0748-2) contains supplementary material, which is available to authorized users. BioMed Central 2019-05-17 /pmc/articles/PMC6525412/ /pubmed/31101088 http://dx.doi.org/10.1186/s12874-019-0748-2 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Dahal, Prabin
Guerin, Philippe J.
Price, Ric N.
Simpson, Julie A.
Stepniewska, Kasia
Evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis: a simulation study
title Evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis: a simulation study
title_full Evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis: a simulation study
title_fullStr Evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis: a simulation study
title_full_unstemmed Evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis: a simulation study
title_short Evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis: a simulation study
title_sort evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis: a simulation study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525412/
https://www.ncbi.nlm.nih.gov/pubmed/31101088
http://dx.doi.org/10.1186/s12874-019-0748-2
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