A systematic review and meta-analysis of evidence for correlation between molecular markers of parasite resistance and treatment outcome in falciparum malaria

Abstract

Background: An assessment of the correlation between anti-malarial treatment outcome and molecular markers would improve the early detection and monitoring of drug resistance by Plasmodium falciparum. The purpose of this systematic review was to determine the risk of treatment failure associated with specific polymorphisms in the parasite genome or gene copy number.

Methods: Clinical studies of non-severe malaria reporting on target genetic markers (SNPs for pfmdr1, pfcrt, dhfr, dhps, gene copy number for pfmdr1) providing complete information on inclusion criteria, outcome, follow up and genotyping, were included. Three investigators independently extracted data from articles. Results were stratified by gene, codon, drug and duration of follow-up. For each study and aggregate data the random effect odds ratio (OR) with 95%CIs was estimated and presented as Forest plots. An OR with a lower 95th confidence interval > 1 was considered consistent with a failure being associated to a given gene mutation.

Results: 92 studies were eligible among the selection from computerized search, with information on pfcrt (25/159 studies), pfmdr1 (29/236 studies), dhfr (18/373 studies), dhps (20/195 studies). The risk of therapeutic failure after chloroquine was increased by the presence of pfcrt K76T (Day 28, OR = 7.2 [95%CI: 4.5-11.5]), pfmdr1 N86Y was associated with both chloroquine (Day 28, OR = 1.8 [95%CI: 1.3-2.4]) and amodiaquine failures (OR = 5.4 [95%CI: 2.6-11.3, p < 0.001]). For sulphadoxine-pyrimethamine the dhfr single (S108N) (Day 28, OR = 3.5 [95%CI: 1.9-6.3]) and triple mutants (S108N, N51I, C59R) (Day 28, OR = 3.1 [95%CI: 2.0-4.9]) and dhfr-dhps quintuple mutants (Day 28, OR = 5.2 [95%CI: 3.2-8.8]) also increased the risk of treatment failure. Increased pfmdr1 copy number was correlated with treatment failure following mefloquine (OR = 8.6 [95%CI: 3.3-22.9]).

Conclusion: When applying the selection procedure for comparative analysis, few studies fulfilled all inclusion criteria compared to the large number of papers identified, but heterogeneity was limited. Genetic molecular markers were related to an increased risk of therapeutic failure. Guidelines are discussed and a checklist for further studies is proposed.

Figure 1

Flow chart for the selection of studies published during the last ten years.

Figure 2

Pfmdr N86Y predictive value of therapeutic failure with chloroquine treatment. (A) Studies with 14 days follow-up (B) Studies with 28 days follow-up. Odds ratios (95% CI) are presented both numerically and graphically. The size of the forest plots is proportional to the relative weight of the study in the meta-analysis. The first row has the name of the first author and the year of publication of the study analysed. Target genes used for distinguishing reinfection to recrudescence are indicated when available. The red plot is the total OR for the listed studies.

Figure 3

Pfmdr N86Y predictive value of therapeutic failure with amodiaquine treatment. Studies with different follow-up were included. Odds ratios (95% CI), forest plots and studies description are similar to figure 1.

Figure 4

Pfcrt K76T predictive value of therapeutic failure with chloroquine. (A) Studies with 14 days follow-up (B) Studies with 28 days follow-up. Odds ratios (95% CI), forest plots and studies description are similar to previous figures. One study with day 35 end point was included in the day 28 list since the difference seems to be weak in terms of late failure rate.

Figure 5

Pfdhfr S108N predictive value of therapeutic failure with Sulfadoxine-pyrimethamine. Studies with different follow-up were included. S108N point mutation was considered irrespective of the presence of other mutations at different Pfdhfr codons. Studies were stratified according first to the duration of the follow-up, second to the use of genotyping for recrudescence, third to the date of publication.

Figure 6

Pfdhfr N51I+C59R+S108N predictive value of therapeutic failure with Sulfadoxine-pyrimethamine. Studies with different follow-up were included. The duration of the follow-up of the last study was supposed to be 28 days while not clearly indicated in the method by authors.

Figure 7

Pfdhps 437 – 540 predictive value of therapeutic failure with Sulfadoxine-pyrimethamine. Odds ratios (95% CI), forest plots and studies description are similar to previous figures. Studies were stratified according first to the duration of the follow-up, second to the use of genotyping for recrudescence, third to the date of publication.