Nonlinear mixed-effects modelling of in vitro drug susceptibility and molecular correlates of multidrug resistant Plasmodium falciparum

The analysis of in vitro anti-malarial drug susceptibility testing is vulnerable to the effects of different statistical approaches and selection biases. These confounding factors were assessed with respect to pfmdr1 gene mutation and amplification in 490 clinical isolates. Two statistical approaches for estimating the drug concentration associated with 50 effect (EC50) were compared: the commonly used standard two-stage (STS) method, and nonlinear mixed-effects modelling. The in vitro concentration-effect relationships for, chloroquine, mefloquine, lumefantrine and artesunate, were derived from clinical isolates obtained from patients on the western border of Thailand. All isolates were genotyped for polymorphisms in the pfmdr1 gene. The EC50 estimates were similar for the two statistical approaches but 15-28 of isolates in the STS method had a high coefficient of variation (>15 ) for individual estimates of EC50 and these isolates had EC50 values that were 32 to 66 higher than isolates derived with more precision. In total 41 (202/490) of isolates had amplification of pfmdr1 and single nucleotide polymorphisms were found in 50 (10 ). Pfmdr1 amplification was associated with an increase in EC50 for mefloquine (139 relative increase in EC50 for 2 copies, 188 for 3+ copies), lumefantrine (82 and 75 for 2 and 3+ copies respectively) and artesunate (63 and 127 for 2 and 3+ copies respectively). In contrast pfmdr1 mutation at codons 86 or 1042 were associated with an increase in chloroquine EC50 (44-48 ). Sample size calculations showed that to demonstrate an EC50 shift of 50 or more with 80 power if the prevalence was 10 would require 430 isolates and 245 isolates if the prevalence was 20 . In conclusion, although nonlinear mixed-effects modelling did not demonstrate any major advantage for determining estimates of anti-malarial drug susceptibility, the method includes all isolates, thereby, potentially improving confirmation of candidate molecular markers of anti-malarial drug susceptibility.