Sensitivity and specificity of molecular methods for detecting markers of antimalarial drug resistance in clinical samples of Plasmodium falciparum: a systematic review

Background Each year infection with Plasmodium causes millions of clinical cases of malaria, and hundreds of thousands of deaths. Resistance to different antimalarial medications continues to develop and spread, threatening effective prophylaxis and treatment. Monitoring of resistance is required to inform health policy and preserve effective antimalarials; molecular methods can be used to determine likely parasite susceptibility. There is no consensus on the most accurate methods; large variation exists in practice. The goal of this systematic review was to identify the sensitivity and specificity of each molecular method for detecting antimalarial resistance markers. Methods All diagnostic accuracy studies that examine at least two molecular methods for detecting selected markers of antimalarial resistance in blood samples from patients diagnosed with, or suspected of having malaria were included. MEDLINE, EMBASE, BIOSIS, and Science Citation Index were searched. Methodological quality was evaluated using QUADAS-2. Sensitivity and specificity were calculated and results synthesised and compared narratively. Results 27,575 search results returned 18 eligible studies, examining 13 index tests, against five reference tests, for their accuracy in detecting 24 molecular markers. Some markers and tests were investigated multiple times, but rarely in the same combinations. Characteristics of studies were poorly reported. Generally, risk of bias and applicability concerns were unclear. Estimates of sensitivity and specificity were calculable for most evaluations, confidence intervals were generally wide. Discussion Estimates of the accuracy of molecular methods are generally imprecise, contributing to uncertainty. Many methods may be close to 100% in sensitivity or specificity. Most methods require specialist equipment unlikely to be available in many low resource settings. High quality study design focusing on methods useable in low resource settings, prospective registration, and reporting according to STARD 2015 guidelines are essential for future studies.