Evidence map›Paper›PMID 42902192›Full record

SynthesisBMC infectious diseases2026

Performance of recombinase polymerase amplification assay for cutaneous leishmaniasis detection: a systematic review and meta-analysis.

Behailu Taye, Myrthe Pareyn, Eyob Getu, Nicole Berens-Riha

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Behailu TayeDepartment of Medical Laboratory Science, College of Medicine and Health Sciences, Dilla University, Dilla, Ethiopia. behailutaye096@gmail.com.
Myrthe PareynDepartment of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.
Eyob GetuDepartment of Medical Laboratory Science, College of Medicine and Health Sciences, Dilla University, Dilla, Ethiopia.
Nicole Berens-RihaDepartment of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSensitive and robust point-of-care (PoC) assays are urgently needed for the diagnosis of cutaneous leishmaniasis (CL). Recombinase polymerase amplification (RPA), an isothermal molecular assay, has shown promise for CL diagnosis using either a lateral-flow assay (LFA) or a mobile-suitcase-laboratory (MSL) platform. However, its diagnostic performance has been inconsistent across studies. This systematic review and meta-analysis aimed to determine the pooled sensitivity and specificity of RPA for CL diagnosis.

methodsA comprehensive search was conducted in Google Scholar, EMBASE, Web of Science, PubMed, and Scopus to identify studies that evaluated the diagnostic accuracy of RPA in suspected CL cases. The methodological quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Using the GRADE approach, certainty of evidence was evaluated. A bivariate random-effects model was applied to perform the meta-analysis using R and Stata 14.2.

resultsNine articles comprising 14 datasets were included, with sample sizes ranging from 18 to 226 participants. Sensitivity in individual studies ranged from 55% to 100%, while specificity varied from 36% to 100%. The pooled sensitivity and specificity were 86% (95% CI: 72-93%, p < 0.001) and 93% (95% CI: 65-99%, p = 0.01), respectively, with an area under the curve (AUC) of 0.88 against microscopy and PCR. Subgroup analysis revealed that RPA-LFA had higher pooled sensitivity (93%, 95% CI: 78-98%) compared to MSL (69%, 95% CI: 51-83%). Blinding was unreported in 44% of the included studies, resulting in an unclear risk of bias that may skew the diagnostic accuracy results. The certainty of evidence for RPA sensitivity was rated as moderate.

conclusionsRPA demonstrated high specificity and good sensitivity for CL diagnosis but fell short of the 95% sensitivity threshold outlined in the WHO target product profile. In contrast to MSL, LFA appears to be a promising PoC method for diagnosing CL. Data on RPA-MSL remains limited, and its applicability to other Leishmania species causing CL is unclear. Future research should focus on the evaluation of RPA for Old World CL species and strains. PROSPERO REGISTRATION: CRD42023451076. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

LeishmaniaLeishmaniasis, CutaneousMolecular Diagnostic TechniquesNucleic Acid Amplification TechniquesRecombinasesHumansPoint-of-Care SystemsRapid Diagnostic TestsSensitivity and SpecificityRecombinasesCutaneous leishmaniasisMeta-analysisPerformanceRecombinase polymerase amplification assaySystematic review

Identifiers

PMID42902192
PMCPMC13681862

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.