Abstract
BackgroundAntimalarial clinical efficacy studies for uncomplicated Plasmodium falciparum malaria frequently encounter situations in which molecular genotyping is unable to discriminate between parasitic recurrence, either new infection or recrudescence. The current WHO guideline recommends excluding these individuals with indeterminate outcomes in a complete case (CC) analysis. Data from the four artemisinin-based combination (4ABC) trial was used to compare the performance of multiple imputation (MI) and inverse probability weighting (IPW) against the standard CC analysis for dealing with indeterminate recurrences.Methods3369 study participants from the multicentre study (4ABC trial) with molecularly defined parasitic recurrence treated with three artemisinin-based combination therapies were used to represent a complete dataset. A set proportion of recurrent infections (10, 30 and 45%) were reclassified as missing using two mechanisms: a completely random selection (mechanism 1); missingness weakly dependent (mechanism 2a) and strongly dependent (mechanism 2b) on treatment and transmission intensity. The performance of MI, IPW and CC approaches in estimating the Kaplan-Meier (K-M) probability of parasitic recrudescence at day 28 was then compared. In addition, the maximum likelihood estimate of the cured proportion was presented for further comparison (analytical solution). Performance measures (bias, relative bias, standard error and coverage) were reported as an average from 1000 simulation runs.ResultsThe CC analyses resulted in absolute underestimation of K-M probability of day 28 recrudescence by up to 1.7% and were associated with reduced precision and poor coverage across all the scenarios studied. Both MI and IPW method performed better (greater consistency and greater efficiency) compared to CC analysis. In the absence of censoring, the analytical solution provided the most consistent and accurate estimate of cured proportion compared to the CC analyses.ConclusionsThe widely used CC approach underestimates antimalarial failure; IPW and MI procedures provided efficient and consistent estimates and should be considered when reporting the results of antimalarial clinical trials, especially in areas of high transmission, where the proportion of indeterminate outcomes could be large. The analytical solution estimating the cured proportion could provide an alternative approach, in scenarios with minimal censoring due to loss to follow-up or new infections.
Highlights
Antimalarial clinical efficacy studies for uncomplicated Plasmodium falciparum malaria frequently encounter situations in which molecular genotyping is unable to discriminate between parasitic recurrence, either new infection or recrudescence
The trial is one of the largest antimalarial studies ever conducted and well suited to study the utility of multiple imputation (MI) and inverse probability weighting (IPW) approaches for handling indeterminate recurrences
Similar findings were observed in Machekano et al (2008) who reported an absolute overestimation in efficacy of 3.2% by complete case (CC) approach compared to IPW and MI methods for the antimalarial regimen of chloroquine (CQ) + sulphadoxinepyrimethamine (SP) and by up to 1.7% for the regimen amodiaquine (AQ) + SP when the observed proportion of missing recurrences were 33% in the CQ + SP arm and 17% for AQ + SP arm [16]
Summary
Antimalarial clinical efficacy studies for uncomplicated Plasmodium falciparum malaria frequently encounter situations in which molecular genotyping is unable to discriminate between parasitic recurrence, either new infection or recrudescence. The current WHO guideline for dealing with indeterminate outcomes in antimalarial efficacy trials is to exclude them from the analysis, that is, to carry out a complete case (CC) analysis [2] This implicitly assumes that the indeterminate cases are a representative random sample of the study population, ignoring the fact that these indeterminate recurrences must be either a recrudescence or new infection, and may depend on other measured and unmeasured patient and parasite characteristics. As well as biased, such ad hoc single imputation approaches consider the imputed datum as the ‘known observed’ value and uncertainty regarding not knowing the reason for parasite recurrence isn’t fully accounted for This yields inferences that are over-precise, i.e. standard errors are too small rendering the associated hypothesis tests as invalid [3,4,5]
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