Literature DB >> 27313266

Declining Efficacy of Artemisinin Combination Therapy Against P. Falciparum Malaria on the Thai-Myanmar Border (2003-2013): The Role of Parasite Genetic Factors.

Aung Pyae Phyo1,2, Elizabeth A Ashley1,2,3, Tim J C Anderson4, Zbynek Bozdech5, Verena I Carrara1,3, Kanlaya Sriprawat1, Shalini Nair4, Marina McDew White4, Jerzy Dziekan5, Clare Ling1,2,3, Stephane Proux1, Kamonchanok Konghahong1, Atthanee Jeeyapant3, Charles J Woodrow2,3, Mallika Imwong3, Rose McGready1,2, Khin Maung Lwin1,3, Nicholas P J Day2,3, Nicholas J White2,3, Francois Nosten1,2.   

Abstract

BACKGROUND: Deployment of mefloquine-artesunate (MAS3) on the Thailand-Myanmar border has led to a sustained reduction in falciparum malaria, although antimalarial efficacy has declined substantially in recent years. The role of Plasmodium falciparum K13 mutations (a marker of artemisinin resistance) in reducing treatment efficacy remains controversial.
METHODS: Between 2003 and 2013, we studied the efficacy of MAS3 in 1005 patients with uncomplicated P. falciparum malaria in relation to molecular markers of resistance.
RESULTS: Polymerase chain reaction (PCR)-adjusted cure rates declined from 100% in 2003 to 81.1% in 2013 as the proportions of isolates with multiple Pfmdr1 copies doubled from 32.4% to 64.7% and those with K13 mutations increased from 6.7% to 83.4%. K13 mutations conferring moderate artemisinin resistance (notably E252Q) predominated initially but were later overtaken by propeller mutations associated with slower parasite clearance (notably C580Y). Those infected with both multiple Pfmdr1 copy number and a K13 propeller mutation were 14 times more likely to fail treatment. The PCR-adjusted cure rate was 57.8% (95% confidence interval [CI], 45.4, 68.3) compared with 97.8% (95% CI, 93.3, 99.3) in patients with K13 wild type and Pfmdr1 single copy. K13 propeller mutation alone was a strong risk factor for recrudescence (P = .009). The combined population attributable fraction of recrudescence associated with K13 mutation and Pfmdr1 amplification was 82%.
CONCLUSIONS: The increasing prevalence of K13 mutations was the decisive factor for the recent and rapid decline in efficacy of artemisinin-based combination (MAS3) on the Thailand-Myanmar border.
© The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America.

Entities:  

Keywords:  K13 mutation; Pfmdr1; Plasmodium falciparum malaria; artemisinin resistance; mefloquine–artesunate

Mesh:

Substances:

Year:  2016        PMID: 27313266      PMCID: PMC4996140          DOI: 10.1093/cid/ciw388

Source DB:  PubMed          Journal:  Clin Infect Dis        ISSN: 1058-4838            Impact factor:   9.079


The Thailand–Myanmar border is endemic for malaria with high-grade antimalarial drug resistance [1, 2]. After the failures of chloroquine and sulfadoxine-pyrimethamine, mefloquine was introduced as the treatment of uncomplicated Plasmodium falciparum malaria in 1985. However, resistance developed rapidly [2, 3], mediated by amplification of the multidrug-resistance gene 1 (Pfmdr1) [4]. In 1992 the cure rate of high-dose mefloquine monotherapy had fallen to 50% [5]. The first artemisinin-based combination treatment (ACT), mefloquine plus artesunate (MAS3), was deployed in 1994 in camps for displaced people [2]. The new treatment was highly efficacious and accompanied by a large and sustained reduction in P. falciparum incidence [6, 7] despite continued presence of effective malaria vectors. A similar impact was documented in the population of migrant workers living along the border [8]. The diminishing proportion of infections carrying multiple parasite clones also suggested reduced transmission [9]. Resistance to artemisinin derivatives, characterized by delayed parasite clearance in artesunate-treated patients, was first recognized in western Cambodia in 2007 [10, 11] and later on the Thailand–Myanmar border where it was found to be heritable [12] and associated with a selective sweep on chromosome 13 of the P. falciparum genome [13] due to mutations in the propeller region of the Kelch gene (K13) [14, 15]. However, the link between K13 polymorphism and treatment failure was not clearly established, and some authors have contested whether use of the term “artemisinin resistance” is justified [16-18]. This uncertainty may have contributed to the failure to contain artemisinin resistance in the greater Mekong area. Two recent studies have provided some evidence that K13 mutations are involved in combination with other mutations in the declining efficacy of 3-day dihydroartemisinin (DHA)–piperaquine in Cambodia [19]. An observational cohort study reported that treatment failure rates were higher in patients infected with parasites carrying the K13 C580Y mutation compared with the R539T mutation, but there were only 4 wild-type infections in that study. Two additional mutations (MAL13:1718319 and MAL10:688956), associated with parasite clearance rate in a genome wide association (GWAS) study [20], were in strong linkage disequilibrium with C580Y. The authors concluded that this triple mutant genotype might have contributed to the failures observed. A second study of 241 patients showed falciparum malaria recrudescence was associated with increased piperaquine in vitro 50% inhibitory concentrations and the presence of K13 mutations at 3 Cambodian sites [21] where isolates with multiple copies of Pfmdr1 are rare [21]. In contrast to Cambodia, P. falciparum malaria parasites along the Thailand–Myanmar border frequently have multiple copies of Pfmdr1 [4, 22]. The MAS3 combination has been deployed successfully as a first-line regimen for more than 15 years, but failure rates in recent years have risen. To determine the factors contributing to declining ACT efficacy, we studied 1005 falciparum malaria patients treated with MAS3 between 2003 and 2013.

METHODS

Patient Recruitment

The study was designed for the longitudinal monitoring of MAS3 efficacy in prospectively enrolled patients presenting to the clinics of the Shoklo Malaria Research Unit [23] with uncomplicated P. falciparum malaria, excluding pregnant women, patients with severe malaria [24] or >4% infected red blood cells, and those who had been treated with mefloquine in the previous 60 days. All patient treatments were supervised. Oral artesunate (Guilin Pharmaceutical Co., People's Republic of China), was given at a dose of 4 mg/kg/day for 3 days. Mefloquine (Roche, Switzerland, or CIPLA, India) was given either as split doses of 15 mg/kg and 10 mg/kg or 8 mg/kg once a day for 3 days [25]. On the first treatment day (day 0) a full clinical examination was performed; parasitemia and hematocrit were measured from capillary blood. Blood smears were microscopically examined daily until negative. Patients were seen weekly for 6 weeks. At each visit symptoms were recorded and a capillary blood sample was obtained for malaria smear and hematocrit. Dried blood spots for parasite genotyping were collected on grade 3 MM Whatman paper (Whatman, United Kingdom) at the first visit and in case of recurrence. Recurrence was defined by the occurrence of parasitemia during follow-up due either to a recrudescence or a reinfection. In 2013 single-dose primaquine as a gametocytocide (0.25 mg/kg) was added routinely on the first day of treatment.

Parasite Genotyping

Parasite DNA was extracted and genotyped at 3 polymorphic loci (MSP1, MSP2, and GLURP) to distinguish recrudescence from reinfection [26]. We determined Pfmdr1 copy number using quantitative polymerase chain reaction (PCR) and K13 polymorphisms by direct sequencing of PCR products (see Supplementary Methods). Pfmdr1 and K13 sequencing were done retrospectively after patient recruitment was completed.

Statistical Analyses

Data were analyzed using Stata 14 (StataCorp, College Station, Texas). Normally distributed data were compared using Student t test and nonnormally distributed data were compared using the Mann–Whitney rank sum test. Categorical variables were assessed using χ2 tests. Analysis of variance was used to compare 3 or more groups. We used logistic regression to examine the association between each potential risk factor and used outcome and multiple logistic regression to analyze resulting risk factors. Survival time data were assessed using Cox regression. The population attributable fraction (PAF) for falciparum malaria recrudescence was calculated for K13 mutations and Pfmdr1 amplification individually and then for the marker combination using the formula 1–(1–PAF) × (1–PAF). We censored patients with indeterminate genotypes, new infections with P. falciparum, or those lost to follow-up.

Ethical Approval

The Oxford Tropical Research Ethics Committee (OXTREC 562-15) and the faculty of Tropical Medicine, Mahidol University (MUTM 2015-019-01) gave ethical approval for the study.

RESULTS

Patients

Between January 2003 and December 2013, 1022 patients were recruited, and 1005 remained in the study (Figure 1). Overall, 290 (28.8%) patients did not complete the full 42 days but were included in survival analyses. There were significant changes in gender ratio, age, duration of symptoms, and admission temperatures over the recruitment period, with an increasing proportion of older febrile male patients over time (Supplementary Table 1). The proportion of patients with fever at admission (tympanic temperature ≥37.5°C) rose significantly from 26.2% in 2003 to 65.4% in 2013 (P = .005). There was also an increase in the median duration of symptoms before presentation from 2 days in 2003 to 3 days in 2013 (P = .04).
Figure 1.

Patient flow diagram after 3-day treatment with mefloquine plus artesunate.

Patient flow diagram after 3-day treatment with mefloquine plus artesunate.

Clinical Responses

MAS3 was well tolerated and cleared the clinical symptoms rapidly. By 24 hours 84.3% (95% confidence interval [CI], 81.6, 86.7) and by 72 hours 98.0% (95% CI, 95.2, 99.1) of patients were afebrile. There was no change in fever clearance times over the study period. The mean fractional reduction in hematocrit from baseline to day 7 did not differ significantly by year (test for trend P = .08). Risk factors associated with anemia (hematocrit <30%) on admission were pretreatment gametocytemia (adjusted odds ratio [aOR], 9.43; 95% CI, 5.45, 16.34; P < .0001), age <13 years (aOR 3.77; 95% CI, 2.17, 6.56; P < .0001), and female gender (aOR 2.18; 95% CI, 1.28, 3.72; P = .004). No patient in the cohort developed severe malaria, and there were no deaths.

K13 Sequencing

K13 sequences from 699 (68.5%) admission parasite isolates and 112 (59.9%) recurrent isolates were analyzed (Supplementary Table 2). In the admission infections, 24 different nonsynonymous polymorphisms were detected, including 20 in the propeller region (Figure 2 and Supplementary Table 3). No sample had more than 1 mutation. The most frequent mutations were C580Y (10.4%) and E252Q (8.3%). The proportion of infections caused by isolates with any K13 polymorphism increased from 6.7% (1/15; 95% CI, .2, 31.9) in 2003 to 83.9% (52/62; 95% CI, 72.3, 92.0) in 2013 (P < .001; Figure 3). During the period 2005–2009, the E252Q mutation was most common, but from 2010 the K13 propeller mutations (notably C580Y) predominated (Figure 2A and 2B). More recurrent isolates had K13 mutations (81/112 [72.3%]) compared with admission isolates (314/699 [44.9%]; P < .0001). In the recurrent isolates, more recrudescent isolates also had K13 mutant alleles compared with reinfections (65/76 [85.5%] vs 12/24 [50%]; P < .001).
Figure 2.

A, Primary amino acid positions and frequencies of K13 mutations. (B) Annual proportions of K13 propeller mutations (summed) and 4 individual genotypes (for which n > 25).

Figure 3.

Annual proportions of day 42 polymerase chain reaction (PCR)–adjusted cure rates, summed K13 mutations, and amplified Pfmdr1. Abbreviations: ACT, artemisinin-based combination treatment; SNP, single-nucleotide polymorphism; WHO, World Health Organization.

A, Primary amino acid positions and frequencies of K13 mutations. (B) Annual proportions of K13 propeller mutations (summed) and 4 individual genotypes (for which n > 25). Annual proportions of day 42 polymerase chain reaction (PCR)–adjusted cure rates, summed K13 mutations, and amplified Pfmdr1. Abbreviations: ACT, artemisinin-based combination treatment; SNP, single-nucleotide polymorphism; WHO, World Health Organization.

Pfmdr1 Copy Number

Pfmdr1 copy numbers were measured in 726 (71.4%) admission isolates and 65 (34.8%) recurrent isolates (Supplementary Table 2). The proportion of infections caused by parasites with multiple (>1) Pfmdr1 copies on admission doubled from 32.4% (95% CI, 17.4, 50.5) in 2003 to 64.7% (95% CI, 46.5, 80.3) in 2013 (P = .031; Figure 3). There was no significant difference in the distribution of Pfmdr1 copy number with gender or age. Significantly more recurrent isolates had multiple copies of Pfmdr1 53/65 (81.5%) compared with admission isolates 377/726 (51.9%; P < .001). Among these recurrent isolates, more recrudescent isolates also had multiple copies of Pfmdr1 compared with reinfections (38/42 [90.5%] vs 8/13 [61.5%]; P = .002). Our study did not characterize the single nucleotide polymorphisms of the Pfmdr1 gene because these relevant single-nucleotide polymorphisms (SNPs) are rare in Thailand [27] and mefloquine resistance is driven by copy number changes on a Pfmdr1 wild-type background [4, 28–30]. Isolates carrying wild-type K13 were associated with single-copy Pfmdr1, while K13 mutations were associated with amplified Pfmdr1 (Fisher exact test, P < .001) (Supplementary Figure 1). The success rate for genotyping of K13 and Pfmdr1 was lower in recurrent infections because of significantly lower parasitemia (P = .0004) and thus much lower parasite DNA concentrations.

Parasite Clearance

Clearance data were available for 957 patients (95.2%). There was a significant increase in the proportion of patients who were parasitemic at day 3 (P < .001, test for trend; Table 1). Multivariate analysis showed that mutation in the K13 gene was the strongest risk factor for day 3 positivity, with later year of treatment, higher parasitemia, higher hematocrit, and fever on admission (but not Pfmdr1 amplification) as independent risk factors (Table 2). K13 propeller mutations were stronger predictors of day 3 positivity, and the 3 most common propeller mutations (C580Y, N458Y, and R561H) were each significantly associated with day 3 positivity (Table 2).
Table 1.

Parasitological Responses to Mefloquine–Artesunate by Year

Years20032004200520062007200820092010201120122013
Completed treatment (n)42143694949164112845316476
Proportion of day 3 blood slide positive (%)a2/42 (4.8)2/137 (1.5)4/68 (5.9)2/48 (4.2)0/47 (0)9/154 (5.8)20/105 (19.0)13/74 (17.6)10/49 (20.4)54/157 (34.4)29/76 (38.2)
Proportion of day 4 blood slide positive (%)a0/42 (0)0/137 (0)0/68 (0)0/48 (0)0/47 (0)3/151 (2.0)4/104 (3.8)1/72 (1.4)3/48 (6.3)14/153 (9.2)6/74 (8.1)
Unadjusted cure rate % (95% CI)10073.2 (62.4,81.3)81.1 (65.4,90.2)86.9 (67.6,95.1)91.0 (74.6,97.0)91.6 (84.6,95.5)79.3 (67.0,87.5)84.4 (72.7,91.3)43.6 (23.9,61.9)67.6 (59.3,74.6)61.4 (47.0,73.0)
Polymerase chain reaction–adjusted cure rates (95% CI)10089.8 (82.3,94.2)89.5 (74.9,95.8)94.2 (78.8,98.5)94.1 (78.5,98.5)94.6 (89.0,97.4)89.3 (79.5,94.5)84.4 (72.7,91.3)50.9 (32.9,66.4)70.3 (62.0,77.0)81.1 (68.4,89.1)
Days to recrudescence Median (range)21 (15,24)24 (14,49)22 (22)31 (28,34)22 (19,26)24 (14,37)24.5 (17,38)21 (14,41)21 (7,36)21 (21,35)
Days to reinfection Median (range)37 (13,49)40 (28,49)42 (21,49)41 (35,47)37 (32,42)36.5 (22,49)45.5 (44,49)30 (25,32)21 (14,42)

Abbreviation: CI, confidence interval.

a Excluding patients not attending who were positive at the previous visit.

Table 2.

Predictors for Persistent Day 3 Asexual Parasitemia Following Mefloquine–Artesunate Treatment

Risk FactorAdjusted Odds Ratio95% Confidence IntervalP Value
Hematocrit on admission1.041.00, 1.09.04
Year of recruitment1.141.02, 1.27.02
Log parasitemia on admission1.421.20, 1.68<.001
Fever (threshold of 37.5°C on admission)2.501.50, 4.18<.001
Any K13 mutant6.593.53, 12.30<.001
Subsets of K13 mutantsa
 Any K13 propeller mutant9.604.86, 18.95<.001
 Isolates with E252Q2.25.91, 5.58.08
 Isolates with C580Y7.613.42, 16.95<.001
 Isolates with N458Y8.753.10, 24.75<.001
 Isolates with R561H14.985.35, 41.92<.001

The analysis of K13 mutant subsets produced similar (within 10%) adjusted odds ratios for fever, year of recruitment, parasitemia, and hematocrit compared with those obtained for any K13 mutant.

a Compared with wild type.

Parasitological Responses to MefloquineArtesunate by Year Abbreviation: CI, confidence interval. a Excluding patients not attending who were positive at the previous visit. Predictors for Persistent Day 3 Asexual Parasitemia Following MefloquineArtesunate Treatment The analysis of K13 mutant subsets produced similar (within 10%) adjusted odds ratios for fever, year of recruitment, parasitemia, and hematocrit compared with those obtained for any K13 mutant. a Compared with wild type.

Cure Rates

Of the 186 patients with recurrent P. falciparum infections, there were 117 (62.9%) recrudescences and 53 (28.5%) reinfections, with 2 indeterminate results, 1 amplification failure, and 13 missing samples. PCR-adjusted parasitological efficacy at day 42 remained above or close to 90% from 2003 to 2009 but declined sharply thereafter (test for trend, P < .001; Table 1, Figure 3). There was a similar trend for recurrence (PCR unadjusted) rate. The lowest cure rates were recorded in 2011 when PCR-adjusted and unadjusted cure rates fell to 43.6% and 50.9%, respectively.

Predictors for Recrudescence

In a Cox regression model, increased Pfmdr1 copy number and K13 mutation were significant independent predictors of falciparum malaria recrudescence (with a multiplicative effect when in combination) along with year of recruitment and age (Table 3). The risk of recrudescence was even higher for K13 propeller mutations as a group and for the 3 most common individual propeller mutations (C580Y, N458Y, and R561H; Table 3).
Table 3.

Predictors for Plasmodium falciparum Recrudescence by Day 42 Following Mefloquine–Artesunate

Risk FactorAdjusted Hazard Ratio95% Confidence IntervalP Value
Age0.97.95, .99.003
Year of recruitment1.201.10, 1.44.001
Multiple Pfmdr1 copy number (>1)2.681.52, 4.75.001
Any K13 mutant3.841.77, 8.36.001
Subsets of K13 mutantsa
 Any K13 propeller mutant4.762.11, 10.75<.001
K13 E252Q2.831.03, 7.75.04
K13 C580Y5.042.00, 12.75.001
K13 R561H5.882.24, 15.40<.001
K13 N458Y7.202.56, 20.24<.001
Compound genotypesb
 Multiple Pfmdr1 + wild type K133.27.84, 12.65.09
 Single Pfmdr1 + K13 propeller mutant5.731.54, 21.26.009
 Multiple Pfmdr1 + K13 propeller mutant14.053.99, 49.48<.001

The analysis of K13 mutant subsets and compound K13/Pfmdr1 genotypes produced similar (within 10%) adjusted hazard ratios for age and year of recruitment compared with the main model.

a Compared with wild type.

b Compared with single Pfmdr1 copy number and wild-type K13.

Predictors for Plasmodium falciparum Recrudescence by Day 42 Following MefloquineArtesunate The analysis of K13 mutant subsets and compound K13/Pfmdr1 genotypes produced similar (within 10%) adjusted hazard ratios for age and year of recruitment compared with the main model. a Compared with wild type. b Compared with single Pfmdr1 copy number and wild-type K13. Cure rates were highest for infections with isolates with single-copy Pfmdr1 gene and wild-type K13 (97.8%) and lowest in patients with multiple copies of Pfmdr1 and any K13 propeller SNP (57.8%; Table 4, Figures 4 and Supplementary Figure 2). Cure rates declined markedly in recent years as the prevalence of K13 mutations rose (Supplementary Figure 2).
Table 4.

Day 42 Polymerase Chain Reaction–Adjusted Adequate Clinical and Parasitological Response Rates Determined by Survival Analysis for 4 Compound Genotypes

GenotypeCure Rate95% Confidence Interval
Single Pfmdr1 + wild-type K1397.8(93.3, 99.3)
Multiple Pfmdr1 + wild-type K1393.1(86.0, 96.7)
Single Pfmdr1 + K13 propeller mutant78.5(65.6, 87.0)
Multiple Pfmdr1 + K13 propeller mutant57.8(45.4, 68.3)
Figure 4.

Kaplan–Meier curves showing cumulative proportions of patients free from recrudescence stratified by presence of Pfmdr1 copy number and K13 genotype. The numbers in parentheses are the recrudescences during the indicated time. K13 Prop refers to samples with mutation in the K13 propeller.

Day 42 Polymerase Chain Reaction–Adjusted Adequate Clinical and Parasitological Response Rates Determined by Survival Analysis for 4 Compound Genotypes Kaplan–Meier curves showing cumulative proportions of patients free from recrudescence stratified by presence of Pfmdr1 copy number and K13 genotype. The numbers in parentheses are the recrudescences during the indicated time. K13 Prop refers to samples with mutation in the K13 propeller. The PAFs (equivalent to the percentage reduction in recrudescent infections that would occur if these mutations were not present) for K13 and Pfmdr1 amplification were 69.0 and 41.9%, respectively. The PAF for the 2 factors in combination was 82%. Hence these 2 factors alone explain almost entirely the increased ACT treatment failure rate observed in this population.

Pre- and Post-treatment Gametocytemia

The proportions of patients presenting with pre-treatment gametocytes or with post-treatment gametocytemia and the associated risk factors are shown in the Supplementary Materials (Supplementary Tables 1, 1.1 and 1.2). There was no association between the presence of K13 propeller mutations (aOR 1.02; 95% CI, .47, 2.19) or multiple copies of Pfmdr1 (aOR 1.28; 95% CI, .75, 2.17) and gametocytemia, either at admission or during follow-up.

DISCUSSION

MAS3 for the treatment of uncomplicated P. falciparum malaria has had a remarkable therapeutic longevity and a dramatic impact on morbidity and mortality on the Thailand–Myanmar border. When artesunate was introduced in 1991, mefloquine was a failing drug, the incidence of falciparum malaria was rising, and most parasite isolates had multiple copies of Pfmdr1 associated with mefloquine resistance [4]. After deployment of this ACT in 1994, mefloquine recovered its efficacy, and less fit isolates with multiple Pfmdr1 copies were replaced by single copy–containing isolates [31]. High cure rates were then sustained for more than a decade [22, 32]. In 2006, 53% of patients presenting with uncomplicated falciparum malaria had infections with multiple copies of Pfmdr1 [22]. The rise in prevalence of P. falciparum parasites with K13 propeller mutations was the definitive event that led to the demise of MAS3. The temporal sequence of K13 selection is informative. The E252Q mutation (which is located on the stem region of the K13 gene; Figure 2A), associated with moderate slowing of parasite clearance [15], predominated before 2010. Then parasites with the E252Q mutation were progressively overtaken by parasites with K13 propeller mutations, conferring greater reductions in parasite clearance rates. The main propeller mutation was C580Y, a polymorphism common in Cambodia [14, 15]. The E252Q mutation was associated with a moderate increase in risk of treatment failure, suggesting that the selective advantage of the K13 mutation is proportional to the degree of parasite clearance prolongation. It is possible that genetic changes outside the K13 locus have contributed to the emergence of artemisinin resistance and the selection of K13 mutations [20]. It remains to be seen whether parasite genotypes with even slower clearance will become established while ACTs remain the mainstay of antimalarial treatment. The large body of data presented here strongly support the hypothesis that there is a substantial impact of K13 mutations on treatment failure. K13 mutations in admission samples are associated with a failure rate of 21.5%. In combination with multiple copies of Pfmdr1, this rises to 42.2%. The sharp decline in MAS3 cure rates temporally corresponds with the emergence of K13 propeller mutant isolates on a long-standing genetic background of Pfmdr1 amplification. The proportion of treatment failures that can be attributed to K13 mutations and multiple copies of Pfmdr1 (ie, PAF) is 82%. Hence, these 2 factors alone explain the majority of increase in treatment failure observed. Other parasite genetic factors that our study was not designed to detect or changes in the demographics of the patient population may have contributed to the 18% of unexplained variation in treatment failure. We highlight 3 additional features of particular interest. First, K13 mutations and Pfmdr1 amplification have a multiplicative (rather than an additive) effect on risk of treatment failure. Synergy between these 2 resistance determinants may help to explain why failure rate declined precipitously in 2009—parasites carrying both markers only became common as K13 mutations rose in frequency. Second, in contrast to the 2 Cambodian studies, we observed multiple K13 mutations in this study. These data demonstrate significant heterogeneity in the impact of different K13 mutations on treatment failure. A mutation outside the K13 propeller (E252Q) increased treatment failure relative to wild-type parasites, but the 3 common propeller mutations had a much greater effect (Table 3). These data suggest that surveillance for emergence of K13 mutations should be expanded to include K13 regions outside the propeller domain. Third, 2 studies [15, 19] provide evidence that gametocyte carriage is elevated in parasites bearing K13 mutations, leading to the suggestion that such parasites may have a transmission advantage. In contrast, in this large study from a single location, we observed no association between gametocyte carriage and K13 mutations. What are the implications of these data for the therapeutic life span of ACTs in Southeast Asia and beyond? The most widely deployed ACT is the coformulation of artemether and lumefantrine (AL), which has a resistance mechanism that is similar to that of mefloquine, involving Pfmdr1 amplification [29, 33, 34]. In most areas where AL is used, there is no evidence for resistance to either component. However, in Myanmar where AL has recently been introduced, K13 propeller mutants and Pfmdr1 amplification are widespread [28, 35–38]. The therapeutic lifetime of AL in Myanmar and other areas with a high prevalence of K13 mutations may be relatively short. ACTs containing an alternative partner drug should provide relief in the short term. In 2012 the first-line treatment of uncomplicated P. falciparum malaria in our treatment centers on the Thailand–Myanmar border was changed from MAS3 to DHApiperaquine, which is currently highly efficacious in this area but relies increasingly on the piperaquine component. The recent emergence of piperaquine resistance in Cambodia [39] and associated rising failure rates with DHApiperaquine [19, 21, 40] also cast doubt over the long-term future of this combination. Alternatives are needed desperately. With new antimalarials still years from deployment, there is an urgent need to eliminate P. falciparum from the area before the recent and substantial gains in malaria control are reversed.

Supplementary Data

Supplementary materials are available at http://cid.oxfordjournals.org. Consisting of data provided by the author to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the author, so questions or comments should be addressed to the author.
  39 in total

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2.  A molecular marker of artemisinin-resistant Plasmodium falciparum malaria.

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Journal:  Nature       Date:  2013-12-18       Impact factor: 49.962

3.  Malaria on the Thai-Burmese border: treatment of 5192 patients with mefloquine-sulfadoxine-pyrimethamine.

Authors:  F Nosten; S Imvithaya; M Vincenti; G Delmas; G Lebihan; B Hausler; N White
Journal:  Bull World Health Organ       Date:  1987       Impact factor: 9.408

4.  Are transporter genes other than the chloroquine resistance locus (pfcrt) and multidrug resistance gene (pfmdr) associated with antimalarial drug resistance?

Authors:  Timothy J C Anderson; Shalini Nair; Huang Qin; Sittaporn Singlam; Alan Brockman; Lucy Paiphun; François Nosten
Journal:  Antimicrob Agents Chemother       Date:  2005-06       Impact factor: 5.191

5.  A major genome region underlying artemisinin resistance in malaria.

Authors:  Ian H Cheeseman; Becky A Miller; Shalini Nair; Standwell Nkhoma; Asako Tan; John C Tan; Salma Al Saai; Aung Pyae Phyo; Carit Ler Moo; Khin Maung Lwin; Rose McGready; Elizabeth Ashley; Mallika Imwong; Kasia Stepniewska; Poravuth Yi; Arjen M Dondorp; Mayfong Mayxay; Paul N Newton; Nicholas J White; François Nosten; Michael T Ferdig; Timothy J C Anderson
Journal:  Science       Date:  2012-04-06       Impact factor: 47.728

6.  Dihydroartemisinin-piperaquine resistance in Plasmodium falciparum malaria in Cambodia: a multisite prospective cohort study.

Authors:  Chanaki Amaratunga; Pharath Lim; Seila Suon; Sokunthea Sreng; Sivanna Mao; Chantha Sopha; Baramey Sam; Dalin Dek; Vorleak Try; Roberto Amato; Daniel Blessborn; Lijiang Song; Gregory S Tullo; Michael P Fay; Jennifer M Anderson; Joel Tarning; Rick M Fairhurst
Journal:  Lancet Infect Dis       Date:  2016-01-08       Impact factor: 25.071

7.  Treatment of multidrug-resistant Plasmodium falciparum malaria with 3-day artesunate-mefloquine combination.

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Journal:  J Infect Dis       Date:  1994-10       Impact factor: 5.226

8.  Artemisinin resistance in Plasmodium falciparum malaria.

Authors:  Arjen M Dondorp; François Nosten; Poravuth Yi; Debashish Das; Aung Phae Phyo; Joel Tarning; Khin Maung Lwin; Frederic Ariey; Warunee Hanpithakpong; Sue J Lee; Pascal Ringwald; Kamolrat Silamut; Mallika Imwong; Kesinee Chotivanich; Pharath Lim; Trent Herdman; Sen Sam An; Shunmay Yeung; Pratap Singhasivanon; Nicholas P J Day; Niklas Lindegardh; Duong Socheat; Nicholas J White
Journal:  N Engl J Med       Date:  2009-07-30       Impact factor: 91.245

9.  Natural selection of K13 mutants of Plasmodium falciparum in response to artemisinin combination therapies in Thailand.

Authors:  C Putaporntip; N Kuamsab; R Kosuwin; W Tantiwattanasub; P Vejakama; T Sueblinvong; S Seethamchai; S Jongwutiwes; A L Hughes
Journal:  Clin Microbiol Infect       Date:  2015-11-05       Impact factor: 8.067

10.  Spread of artemisinin resistance in Plasmodium falciparum malaria.

Authors:  Elizabeth A Ashley; Mehul Dhorda; Rick M Fairhurst; Chanaki Amaratunga; Parath Lim; Seila Suon; Sokunthea Sreng; Jennifer M Anderson; Sivanna Mao; Baramey Sam; Chantha Sopha; Char Meng Chuor; Chea Nguon; Siv Sovannaroth; Sasithon Pukrittayakamee; Podjanee Jittamala; Kesinee Chotivanich; Kitipumi Chutasmit; Chaiyaporn Suchatsoonthorn; Ratchadaporn Runcharoen; Tran Tinh Hien; Nguyen Thanh Thuy-Nhien; Ngo Viet Thanh; Nguyen Hoan Phu; Ye Htut; Kay-Thwe Han; Kyin Hla Aye; Olugbenga A Mokuolu; Rasaq R Olaosebikan; Olaleke O Folaranmi; Mayfong Mayxay; Maniphone Khanthavong; Bouasy Hongvanthong; Paul N Newton; Marie A Onyamboko; Caterina I Fanello; Antoinette K Tshefu; Neelima Mishra; Neena Valecha; Aung Pyae Phyo; Francois Nosten; Poravuth Yi; Rupam Tripura; Steffen Borrmann; Mahfudh Bashraheil; Judy Peshu; M Abul Faiz; Aniruddha Ghose; M Amir Hossain; Rasheda Samad; M Ridwanur Rahman; M Mahtabuddin Hasan; Akhterul Islam; Olivo Miotto; Roberto Amato; Bronwyn MacInnis; Jim Stalker; Dominic P Kwiatkowski; Zbynek Bozdech; Atthanee Jeeyapant; Phaik Yeong Cheah; Tharisara Sakulthaew; Jeremy Chalk; Benjamas Intharabut; Kamolrat Silamut; Sue J Lee; Benchawan Vihokhern; Chanon Kunasol; Mallika Imwong; Joel Tarning; Walter J Taylor; Shunmay Yeung; Charles J Woodrow; Jennifer A Flegg; Debashish Das; Jeffery Smith; Meera Venkatesan; Christopher V Plowe; Kasia Stepniewska; Philippe J Guerin; Arjen M Dondorp; Nicholas P Day; Nicholas J White
Journal:  N Engl J Med       Date:  2014-07-31       Impact factor: 91.245

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  92 in total

Review 1.  Antimalarial drug resistance: linking Plasmodium falciparum parasite biology to the clinic.

Authors:  Benjamin Blasco; Didier Leroy; David A Fidock
Journal:  Nat Med       Date:  2017-08-04       Impact factor: 53.440

2.  Predicting the Disposition of the Antimalarial Drug Artesunate and Its Active Metabolite Dihydroartemisinin Using Physiologically Based Pharmacokinetic Modeling.

Authors:  Ryan Arey; Brad Reisfeld
Journal:  Antimicrob Agents Chemother       Date:  2021-02-17       Impact factor: 5.191

3.  Characterization of the Preclinical Pharmacology of the New 2-Aminomethylphenol, JPC-3210, for Malaria Treatment and Prevention.

Authors:  Geoffrey W Birrell; Gavin D Heffernan; Guy A Schiehser; John Anderson; Arba L Ager; Pablo Morales; Donna MacKenzie; Karin van Breda; Marina Chavchich; Laura R Jacobus; G Dennis Shanks; David P Jacobus; Michael D Edstein
Journal:  Antimicrob Agents Chemother       Date:  2018-03-27       Impact factor: 5.191

4.  Efficacy of Artemisinin-Based Combination Treatments of Uncomplicated Falciparum Malaria in Under-Five-Year-Old Nigerian Children Ten Years Following Adoption as First-Line Antimalarials.

Authors:  Joy C Ebenebe; Godwin Ntadom; Jose Ambe; Robinson Wammanda; Nma Jiya; Finomo Finomo; George Emechebe; Olugbenga Mokuolu; Kazeem Akano; Chimere Agomo; Onikepe A Folarin; Stephen Oguche; Francis Useh; Wellington Oyibo; Temitope Aderoyeje; Mohammed Abdulkadir; Nnenna M Ezeigwe; Christian Happi; Akintunde Sowunmi
Journal:  Am J Trop Med Hyg       Date:  2018-06-21       Impact factor: 2.345

5.  K13 Propeller Alleles, mdr1 Polymorphism, and Drug Effectiveness at Day 3 after Artemether-Lumefantrine Treatment for Plasmodium falciparum Malaria in Colombia, 2014-2015.

Authors:  Madeline Montenegro; Aaron T Neal; Maritza Posada; Briegel De Las Salas; Tatiana M Lopera-Mesa; Rick M Fairhurst; Alberto Tobon-Castaño
Journal:  Antimicrob Agents Chemother       Date:  2017-11-22       Impact factor: 5.191

6.  Efficacy of dihydroartemisinin/piperaquine and artesunate monotherapy for the treatment of uncomplicated Plasmodium falciparum malaria in Central Vietnam.

Authors:  Eduard Rovira-Vallbona; Nguyen Van Hong; Johanna H Kattenberg; Ro Mah Huan; Nguyen Thi Thu Hien; Nguyen Thi Hong Ngoc; Pieter Guetens; Nguyen Luong Hieu; Tran Tuyet Mai; Nguyen Thi Thuy Duong; Tran Thanh Duong; Bui Quang Phuc; Nguyen Xuan Xa; Annette Erhart; Anna Rosanas-Urgell
Journal:  J Antimicrob Chemother       Date:  2020-08-01       Impact factor: 5.790

7.  Artemisinin resistance phenotypes and K13 inheritance in a Plasmodium falciparum cross and Aotus model.

Authors:  Juliana M Sá; Sarah R Kaslow; Michael A Krause; Viviana A Melendez-Muniz; Rebecca E Salzman; Whitney A Kite; Min Zhang; Roberto R Moraes Barros; Jianbing Mu; Paul K Han; J Patrick Mershon; Christine E Figan; Ramoncito L Caleon; Rifat S Rahman; Tyler J Gibson; Chanaki Amaratunga; Erika P Nishiguchi; Kimberly F Breglio; Theresa M Engels; Soundarapandian Velmurugan; Stacy Ricklefs; Judith Straimer; Nina F Gnädig; Bingbing Deng; Anna Liu; Ababacar Diouf; Kazutoyo Miura; Gregory S Tullo; Richard T Eastman; Sumana Chakravarty; Eric R James; Kenneth Udenze; Suzanne Li; Daniel E Sturdevant; Robert W Gwadz; Stephen F Porcella; Carole A Long; David A Fidock; Marvin L Thomas; Michael P Fay; B Kim Lee Sim; Stephen L Hoffman; John H Adams; Rick M Fairhurst; Xin-Zhuan Su; Thomas E Wellems
Journal:  Proc Natl Acad Sci U S A       Date:  2018-11-19       Impact factor: 11.205

Review 8.  The gut microbiome, immunity, and Plasmodium severity.

Authors:  Morgan L Waide; Nathan W Schmidt
Journal:  Curr Opin Microbiol       Date:  2020-09-30       Impact factor: 7.934

9.  Artemether-Lumefantrine and Dihydroartemisinin-Piperaquine Retain High Efficacy for Treatment of Uncomplicated Plasmodium falciparum Malaria in Myanmar.

Authors:  Kay Thwe Han; Khin Lin; Moe Kyaw Myint; Aung Thi; Kyin Hla Aye; Zay Yar Han; Mya Moe; Maria Dorina Bustos; Md Mushfiqur Rahman; Pascal Ringwald; Ryan Simmons; Christine F Markwalter; Christopher V Plowe; Myaing M Nyunt
Journal:  Am J Trop Med Hyg       Date:  2020-03       Impact factor: 2.345

10.  In Silico Investigation of the Decline in Clinical Efficacy of Artemisinin Combination Therapies Due to Increasing Artemisinin and Partner Drug Resistance.

Authors:  Sophie G Zaloumis; Pengxing Cao; Saber Dini; Miles P Davenport; Deborah Cromer; David S Khoury; Freya J I Fowkes; James M McCaw; Julie A Simpson
Journal:  Antimicrob Agents Chemother       Date:  2018-11-26       Impact factor: 5.191

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