Tools for surveillance of anti-malarial drug resistance: an assessment of the current landscape

To limit the spread and impact of anti-malarial drug resistance and react accordingly, surveillance systems able to detect and track in real-time its emergence and spread need to be strengthened or in some places established. Currently, surveillance of anti-malarial drug resistance is done by any of three approaches: (1) in vivo studies to assess the efficacy of drugs in patients; (2) in vitro/ex vivo studies to evaluate parasite susceptibility to the drugs; and/or (3) molecular assays to detect validated gene mutations and/or gene copy number changes that are associated with drug resistance. These methods are complementary, as they evaluate different aspects of resistance; however, standardization of methods, especially for in vitro/ex vivo and molecular techniques, is lacking. The World Health Organization has developed a standard protocol for evaluating the efficacy of anti-malarial drugs, which is used by National Malaria Control Programmes to conduct their therapeutic efficacy studies. Regional networks, such as the East African Network for Monitoring Antimalarial Treatment and the Amazon Network for the Surveillance of Antimalarial Drug Resistance, have been set up to strengthen regional capacities for monitoring anti-malarial drug resistance. The Worldwide Antimalarial Resistance Network has been established to collate and provide global spatial and temporal trends information on the efficacy of anti-malarial drugs and resistance. While exchange of information across endemic countries is essential for monitoring anti-malarial resistance, sustainable funding for the surveillance and networking activities remains challenging. The technology landscape for molecular assays is progressing quite rapidly, and easy-to-use and affordable new techniques are becoming available. They also offer the advantage of high throughput analysis from a simple blood spots obtained from a finger prick. New technologies combined with the strengthening of national reference laboratories in malaria-endemic countries through standardized protocols and training plus the availability of a proficiency testing programme, would contribute to the improvement and sustainability of anti-malarial resistance surveillance networks worldwide

Competing risk events in antimalarial drug trials in uncomplicated Plasmodium falciparum malaria: a WorldWide Antimalarial Resistance Network individual participant data meta-analysis

BACKGROUND: Therapeutic efficacy studies in uncomplicated Plasmodium falciparum malaria are confounded by new infections, which constitute competing risk events since they can potentially preclude/pre-empt the detection of subsequent recrudescence of persistent, sub-microscopic primary infections. METHODS: Antimalarial studies typically report the risk of recrudescence derived using the Kaplan-Meier (K-M) method, which considers new infections acquired during the follow-up period as censored. Cumulative Incidence Function (CIF) provides an alternative approach for handling new infections, which accounts for them as a competing risk event. The complement of the estimate derived using the K-M method (1 minus K-M), and the CIF were used to derive the risk of recrudescence at the end of the follow-up period using data from studies collated in the WorldWide Antimalarial Resistance Network data repository. Absolute differences in the failure estimates derived using these two methods were quantified. In comparative studies, the equality of two K-M curves was assessed using the log-rank test, and the equality of CIFs using Gray's k-sample test (both at 5% level of significance). Two different regression modelling strategies for recrudescence were considered: cause-specific Cox model and Fine and Gray's sub-distributional hazard model. RESULTS: Data were available from 92 studies (233 treatment arms, 31,379 patients) conducted between 1996 and 2014. At the end of follow-up, the median absolute overestimation in the estimated risk of cumulative recrudescence by using 1 minus K-M approach was 0.04% (interquartile range (IQR): 0.00-0.27%, Range: 0.00-3.60%). The overestimation was correlated positively with the proportion of patients with recrudescence [Pearson's correlation coefficient (ρ): 0.38, 95% Confidence Interval (CI) 0.30-0.46] or new infection [ρ: 0.43; 95% CI 0.35-0.54]. In three study arms, the point estimates of failure were greater than 10% (the WHO threshold for withdrawing antimalarials) when the K-M method was used, but remained below 10% when using the CIF approach, but the 95% confidence interval included this threshold. CONCLUSIONS: The 1 minus K-M method resulted in a marginal overestimation of recrudescence that became increasingly pronounced as antimalarial efficacy declined, particularly when the observed proportion of new infection was high. The CIF approach provides an alternative approach for derivation of failure estimates in antimalarial trials, particularly in high transmission settings

Competing risk events in antimalarial drug trials in uncomplicated Plasmodium falciparum malaria: A WorldWide Antimalarial Resistance Network individual participant data meta-analysis

Background: Therapeutic efficacy studies in uncomplicated Plasmodium falciparum malaria are confounded by new infections, which constitute competing risk events since they can potentially preclude/pre-empt the detection of subsequent recrudescence of persistent, sub-microscopic primary infections. Methods: Antimalarial studies typically report the risk of recrudescence derived using the Kaplan-Meier (K-M) method, which considers new infections acquired during the follow-up period as censored. Cumulative Incidence Function (CIF) provides an alternative approach for handling new infections, which accounts for them as a competing risk event. The complement of the estimate derived using the K-M method (1 minus K-M), and the CIF were used to derive the risk of recrudescence at the end of the follow-up period using data from studies collated in the WorldWide Antimalarial Resistance Network data repository. Absolute differences in the failure estimates derived using these two methods were quantified. In comparative studies, the equality of two K-M curves was assessed using the log-rank test, and the equality of CIFs using Gray's k-sample test (both at 5% level of significance). Two different regression modelling strategies for recrudescence were considered: cause-specific Cox model and Fine and Gray's sub-distributional hazard model. Results: Data were available from 92 studies (233 treatment arms, 31,379 patients) conducted between 1996 and 2014. At the end of follow-up, the median absolute overestimation in the estimated risk of cumulative recrudescence by using 1 minus K-M approach was 0.04% (interquartile range (IQR): 0.00-0.27%, Range: 0.00-3.60%). The overestimation was correlated positively with the proportion of patients with recrudescence [Pearson's correlation coefficient (ρ): 0.38, 95% Confidence Interval (CI) 0.30-0.46] or new infection [ρ: 0.43; 95% CI 0.35-0.54]. In three study arms, the point estimates of failure were greater than 10% (the WHO threshold for withdrawing antimalarials) when the K-M method was used, but remained below 10% when using the CIF approach, but the 95% confidence interval included this threshold. Conclusions: The 1 minus K-M method resulted in a marginal overestimation of recrudescence that became increasingly pronounced as antimalarial efficacy declined, particularly when the observed proportion of new infection was high. The CIF approach provides an alternative approach for derivation of failure estimates in antimalarial trials, particularly in high transmission settings