A protocol for a systematic review and individual patient data meta-analysis investigating the relationship between Pfkelch13 mutations and response to artemisinin-based treatment for uncomplicated falciparum malaria

Read the full article

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Introduction

Artemisinin-based combination therapies (ACTs) remain the WHO-recommended treatment for uncomplicated Plasmodium falciparum malaria. However, the emergence and spread of artemisinin resistance (ART-R) threatens ACT efficacy. ART-R is phenotypically expressed as delayed parasite clearance, which can facilitate ACT partner drug resistance. ART-R has been causally linked to specific mutations in the Pfkelch13 gene.

Methods and Analysis

The systematic review and associated meta-analysis aim to determine the correlation between Pfkelch13 genotypes and clinical and parasitological response to ACTs from a globally representative dataset pooling individual patient data (IPD) from eligible published and unpublished studies. The eligibility criteria include Pfkelch13 genotyping results at baseline complemented by individually linked parasitological and clinical assessments following artemisinin-based treatment. The data will be curated, standardised, and analysed using this proposed statistical analysis plan, adhering to PRISMA-IPD guidelines. Our statistical analysis plan (SAP) will apply hierarchical modelling to assess the effect of Pfkelch13 mutations on parasite clearance half-life and therapeutic efficacy across different regions. This will include study sites as random effects in the model and potential predictors such as age, sex, baseline parasite load and other potential effect modifiers as fixed effects. This analysis will enhance the understanding of the influence of Pfkelch13 mutations on malaria treatment outcomes.

Ethics and Dissemination

Data is obtained with informed consent and ethical approvals from the relevant countries and was pseudonymised before curation in the IDDO/WWARN repository. Data ownership remains with contributors. This IPD meta-analysis met the Oxford Tropical Research Ethics Committee criteria for waiving ethical review, as it is a secondary analysis of existing pseudonymised data. The resulting peer-reviewed publication will help strengthen and enhance the efficiency of ART-R surveillance and response and support policy decisions. The results will be submitted for publication in a peer-reviewed journal and shared at scientific conferences.

Registration details

PROSPERO-registered (CRD42019133366)

Article summary

Strengths and limitations of study

  • Inclusion of all available data based on a PROSPERO-registered systematic review of published and unpublished studies representing diverse patient and malaria parasite populations across varied global geographic regions, malaria transmission intensities and antimalarial drug pressures.

  • Individual patient data (IPD) meta-analysis is the only valid approach to determine the relationship between mutant alleles and parasite clearance, taking into account moderators of treatment response. This protocol outlines the combined efforts of stakeholders, national malaria programs, and researchers to investigate this relationship through data reuse.

  • This WWARN Data Management and Statistical Analysis Plan allows for standardised IPD to be included in the WWARN repository, which is then pooled into a single, quality-assured database using Clinical Data Interchange Standards Consortium (CDISC) standards.

  • IPD meta-analyses are limited by the data available, with inconsistencies in the type and completeness of covariates measured across the studies. For example, studies often only assess known mutations previously associated with ART-R, reducing the likelihood of detecting clinically relevant mutations not previously reported.

  • A key limitation is that current published studies may be insufficient to investigate the direct impact of Pfkelch13 mutant genotypes on the predictors/indicators of increased malaria transmission.

  • Article activity feed