Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria: pitfalls and challenges
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, failur...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2017-10-01
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| Series: | Malaria Journal |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12936-017-2074-7 |
| _version_ | 1818266108872884224 |
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| author | Prabin Dahal Julie A. Simpson Grant Dorsey Philippe J. Guérin Ric N. Price Kasia Stepniewska |
| author_facet | Prabin Dahal Julie A. Simpson Grant Dorsey Philippe J. Guérin Ric N. Price Kasia Stepniewska |
| author_sort | Prabin Dahal |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-12T20:01:28Z |
| format | Article |
| id | doaj.art-75d01eb8fffc44fcb62aa96e33dfca98 |
| institution | Directory Open Access Journal |
| issn | 1475-2875 |
| language | English |
| last_indexed | 2024-12-12T20:01:28Z |
| publishDate | 2017-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Malaria Journal |
| spelling | doaj.art-75d01eb8fffc44fcb62aa96e33dfca982022-12-22T00:13:44ZengBMCMalaria Journal1475-28752017-10-0116111410.1186/s12936-017-2074-7Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria: pitfalls and challengesPrabin Dahal0Julie A. Simpson1Grant Dorsey2Philippe J. Guérin3Ric N. Price4Kasia Stepniewska5WorldWide Antimalarial Resistance Network (WWARN)Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of MelbourneDepartment of Medicine, University of CaliforniaWorldWide Antimalarial Resistance Network (WWARN)WorldWide Antimalarial Resistance Network (WWARN)WorldWide Antimalarial Resistance Network (WWARN)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.http://link.springer.com/article/10.1186/s12936-017-2074-7Plasmodium falciparumKaplan–MeierCumulative incidence functionCompeting risksComparative studies |
| spellingShingle | Prabin Dahal Julie A. Simpson Grant Dorsey Philippe J. Guérin Ric N. Price Kasia Stepniewska Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria: pitfalls and challenges Malaria Journal Plasmodium falciparum Kaplan–Meier Cumulative incidence function Competing risks Comparative studies |
| title | Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria: pitfalls and challenges |
| title_full | Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria: pitfalls and challenges |
| title_fullStr | Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria: pitfalls and challenges |
| title_full_unstemmed | Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria: pitfalls and challenges |
| title_short | Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria: pitfalls and challenges |
| title_sort | statistical methods to derive efficacy estimates of anti malarials for uncomplicated plasmodium falciparum malaria pitfalls and challenges |
| topic | Plasmodium falciparum Kaplan–Meier Cumulative incidence function Competing risks Comparative studies |
| url | http://link.springer.com/article/10.1186/s12936-017-2074-7 |
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