| Title |
Statistical methods to derive efficacy estimates of anti-malarials for uncomplicated Plasmodium falciparum malaria: pitfalls and challenges
|
|---|---|
| Published in |
Malaria Journal, October 2017
|
| DOI | 10.1186/s12936-017-2074-7 |
| Pubmed ID | |
| Authors |
Prabin Dahal, Julie A. Simpson, Grant Dorsey, Philippe J. Guérin, Ric N. Price, Kasia Stepniewska |
| 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. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 33% |
| Spain | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 2 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 33 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 33% |
| Student > Ph. D. Student | 5 | 15% |
| Student > Master | 3 | 9% |
| Professor | 3 | 9% |
| Student > Bachelor | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 7 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 30% |
| Biochemistry, Genetics and Molecular Biology | 3 | 9% |
| Nursing and Health Professions | 3 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 6% |
| Agricultural and Biological Sciences | 2 | 6% |
| Other | 5 | 15% |
| Unknown | 8 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 May 2018.
All research outputs
#8,203,620
of 24,580,204 outputs
Outputs from Malaria Journal
#2,503
of 5,786 outputs
Outputs of similar age
#127,120
of 332,796 outputs
Outputs of similar age from Malaria Journal
#65
of 126 outputs
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