Improving Methods for Analyzing Antimalarial Drug Efficacy Trials: Molecular Correction Based on Length-Polymorphic Markers msp-1, msp-2, and glurp

Antimicrob Agents Chemother. 2019 Aug 23;63(9):e00590-19. doi: 10.1128/AAC.00590-19. Print 2019 Sep.

Abstract

Drug efficacy trials monitor the continued efficacy of front-line drugs against falciparum malaria. Overestimating efficacy results in a country retaining a failing drug as first-line treatment with associated increases in morbidity and mortality, while underestimating 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 reinfected 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" have been proposed, but which is most accurate and/or robust remains unknown. We used pharmacological modeling 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. Our findings are as follows. (i) Molecular correction is essential to avoid substantial overestimates of drug failure rates. (ii) The current WHO-recommended algorithm consistently underestimates 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, overestimating drug failure rate. (v) Our model was highly consistent with existing in vivo data. The current WHO-recommended method for molecular correction and analysis of clinical trials should be reevaluated and updated.

Keywords: ACT; artemisinin; drug efficacy; drug failure; lumefantrine; malaria; mefloquine; modeling; molecular correction; piperaquine.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Antigens, Protozoan / genetics*
  • Antigens, Protozoan / metabolism
  • Antimalarials / pharmacokinetics
  • Antimalarials / pharmacology*
  • Artemisinins / pharmacokinetics
  • Artemisinins / pharmacology
  • Biomarkers / metabolism
  • Clinical Trials as Topic
  • Gene Expression
  • Humans
  • Lumefantrine / pharmacokinetics
  • Lumefantrine / pharmacology
  • Malaria, Falciparum / drug therapy
  • Malaria, Falciparum / parasitology
  • Mefloquine / pharmacokinetics
  • Mefloquine / pharmacology
  • Merozoite Surface Protein 1 / genetics*
  • Merozoite Surface Protein 1 / metabolism
  • Models, Statistical*
  • Parasitic Sensitivity Tests
  • Plasmodium falciparum / drug effects*
  • Plasmodium falciparum / genetics
  • Plasmodium falciparum / growth & development
  • Polymorphism, Restriction Fragment Length
  • Protozoan Proteins / genetics*
  • Protozoan Proteins / metabolism
  • Quinolines / pharmacokinetics
  • Quinolines / pharmacology
  • Time Factors
  • Treatment Outcome

Substances

  • Antigens, Protozoan
  • Antimalarials
  • Artemisinins
  • Biomarkers
  • Merozoite Surface Protein 1
  • Protozoan Proteins
  • Quinolines
  • merozoite surface protein 2, Plasmodium
  • glutamate-rich protein, Plasmodium
  • artemisinin
  • piperaquine
  • Lumefantrine
  • Mefloquine