Evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis: a simulation study
Abstract 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 censor...
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| Format: | Article |
| Language: | English |
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BMC
2019-05-01
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| Series: | BMC Medical Research Methodology |
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| Online Access: | http://link.springer.com/article/10.1186/s12874-019-0748-2 |
| _version_ | 1818322919829274624 |
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| author | Prabin Dahal Philippe J. Guerin Ric N. Price Julie A. Simpson Kasia Stepniewska |
| author_facet | Prabin Dahal Philippe J. Guerin Ric N. Price Julie A. Simpson Kasia Stepniewska |
| author_sort | Prabin Dahal |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-13T11:04:27Z |
| format | Article |
| id | doaj.art-cf2e1acd9c1a4c2386940409e2363c4d |
| institution | Directory Open Access Journal |
| issn | 1471-2288 |
| language | English |
| last_indexed | 2024-12-13T11:04:27Z |
| publishDate | 2019-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Research Methodology |
| spelling | doaj.art-cf2e1acd9c1a4c2386940409e2363c4d2022-12-21T23:49:07ZengBMCBMC Medical Research Methodology1471-22882019-05-0119111410.1186/s12874-019-0748-2Evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis: a simulation studyPrabin Dahal0Philippe J. Guerin1Ric N. Price2Julie A. Simpson3Kasia Stepniewska4WorldWide Antimalarial Resistance Network (WWARN)WorldWide Antimalarial Resistance Network (WWARN)WorldWide Antimalarial Resistance Network (WWARN)Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of MelbourneWorldWide Antimalarial Resistance Network (WWARN)Abstract 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.http://link.springer.com/article/10.1186/s12874-019-0748-2MalariaPlasmodium falciparumEfficacyCompeting risk eventsCumulative incidence function |
| spellingShingle | Prabin Dahal Philippe J. Guerin Ric N. Price Julie A. Simpson Kasia Stepniewska Evaluating antimalarial efficacy in single-armed and comparative drug trials using competing risk survival analysis: a simulation study BMC Medical Research Methodology Malaria Plasmodium falciparum Efficacy Competing risk events Cumulative incidence function |
| 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 | Malaria Plasmodium falciparum Efficacy Competing risk events Cumulative incidence function |
| url | http://link.springer.com/article/10.1186/s12874-019-0748-2 |
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