Link to Pubmed [PMID] – 31307982
Antimicrob. Agents Chemother. 2019 Jul;
BACKGROUND: Drug efficacy trials monitor the continued efficacy of front-line drugs against falciparum malaria. Over-estimates of efficacy result in a country retaining a failing drug as first-line treatment with associated increases in morbidity and mortality, while under-estimating drug effectiveness leads to removal of an effective treatment with substantial practical and economic implications. Trials are challenging: they require long durations of follow-up to detect drug failures, and patients are frequently re-infected during that period. Molecular correction based on parasite genotypes distinguishes reinfections from drug failures to ensure the accuracy of failure rate estimates. Several molecular correction “algorithms” are proposed, but which is most accurate and/or robust remains unknown.
METHODS: We used pharmacological modelling to simulate parasite dynamics and genetic signals that occur in patients enrolled in malaria drug clinical trials. We compared estimates of treatment failure obtained from a selection of proposed molecular correction algorithms against the known “true” failure rate in the model.
FINDINGS: (i) Molecular correction is essential to avoid substantial over-estimates of drug failure rates. (ii) The current WHO-recommended algorithm consistently under-estimates the true failure rate. (iii) Newly-proposed algorithms produce more accurate failure rate estimates; the most accurate algorithm depends on the choice of drug, trial follow-up length, and transmission intensity. (iv) Long durations of patient follow-up may be counterproductive; large numbers of new infections accumulate and may be misclassified, over-estimating drug failure rate. (v) Our model was highly consistent with existing data.
INTERPRETATION: The current WHO-recommended method for molecular correction and analysis of clinical trials should be re-evaluated and updated.