METHODS: This was a meta-analysis of diagnostic accuracy. Relevant studies that assessed the diagnostic performance of LAMP for the detection of malaria in pregnancy were searched in health-related electronic databases including PubMed, Ovid, and Google Scholar. The methodological quality of the studies included was evaluated using the QUADAS-2 tool.
RESULTS: Of the 372 studies identified, eight studies involving 2999 pregnant women in five endemic countries that assessed the accuracy of LAMP were identified. With three types of PCR as reference tests, the pooled sensitivity of LAMP was 91% (95%CI 67-98%) and pooled specificity was 99% (95%CI 83-100%, 4 studies), and the negative likelihood ratio was 9% (2-40%). Caution is needed in the interpretation as there was substantial between-study heterogeneity (I2: 80%), and a low probability that a person without infection is tested negative. With microscopy as a reference, the pooled sensitivity of LAMP was 95% (95%CI 26-100%) and pooled specificity was 100% (95%CI 94-100%, 4 studies). There was a wide range of sensitivity and substantial between-study heterogeneity (I2: 83.5-98.4%). To investigate the source of heterogeneity, a meta-regression analysis was performed with covariates. Of these potential confounding factors, reference test (p: 0.03) and study design (p:0.03) had affected the diagnostic accuracy of LAMP in malaria in pregnancy. Overall, there was a low certainty of the evidence in accuracy estimates.
CONCLUSION: The findings suggest that LAMP is more sensitive than traditional tests used at facilities, but the utility of detecting and treating these low-density infections is not well understood. Due to the limited number of studies with bias in their methodological quality, variation in the study design, and different types of reference tests further research is likely to change the estimate. Well-conceived large prospective studies with blinding of the index test results are recommenced.
METHODS: This study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Diagnostic Test Accuracy (PRISMA-DTA) guideline. Relevant studies in the health-related electronic databases were searched. According to the criteria set for this study, eligible studies were identified. The quality of included studies was evaluated with the use of a quality assessment checklist. A summary performance estimates such as pooled sensitivity and specificity were stratified by type of LAMP. Bivariate model for data analyses was applied. Summary receiver operating characteristics plots were created to display the results of individual studies in a receiver operating characteristics space. Meta-regression analysis was performed to investigate the sources of heterogeneity among individual studies.
RESULTS: Twenty-seven studies across 17 endemic countries were identified. The vast majority of studies were with unclear risk of bias in the selection of index test. Overall, the pooled test performances were high for Pan LAMP (sensitivity: 0.95, 95% CI 0.91 to 0.97; specificity: 0.98, 95% CI 0.95 to 0.99), Plasmodium falciparum (Pf) LAMP (sensitivity: 0.96, 95% CI 0.94 to 0.98; specificity: 0.99, 95% CI 0.96 to 1.00) or for Plasmodium vivax (Pv) LAMP from 6 studies (sensitivity: 0.98, 95% CI 0.92 to 0.99; specificity: 0.99, 95% CI 0.72 to 1.00). The area under the curve for Pan LAMP (0.99, 95% CI 0.98-1.00), Pf LAMP (0.99, 95% CI 0.97-0.99) and Pv LAMP was (1.00, 95% CI 0.98-1.00) indicated that the diagnostic performance of these tests were within the excellent accuracy range. Meta-regression analysis showed that sample size had the greatest impact on test performance, among other factors.
CONCLUSIONS: The current findings suggest that LAMP-based assays are appropriate for detecting low-level malaria parasite infections in the field and would become valuable tools for malaria control and elimination programmes. Future well-designed larger sample studies on LAMP assessment in passive and active malaria surveillances that use PCR as the reference standard and provide sufficient data to construct 2 × 2 diagnostic table are needed.