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Войти в исследования PLoS neglected tropical diseases · 2026
Evaluation of six different tests for Schistosoma haematobium diagnosis in a near-elimination setting: A prospective observational diagnostic accuracy study.
СтатьяНаблюдательное исследованиеОценочное исследованиеНазвание и аннотация: Перевод в очереди
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Ndum Naomi C, Ali Said M, Ali Mohammed N, Bergelin John, Hattendorf Jan, Hoekstra Pytsje T, van Lieshout Lisette, Pennance Tom, Suleiman Khamis R, Utzinger Jürg, Ward Peter, Webster Bonnie L, Knopp Stefanie
Аннотация
BACKGROUND: Accurate diagnostic tools are needed in schistosomiasis elimination settings to determine prevalence thresholds for assigning or stopping interventions, guide pre- and post-elimination surveillance, and verify whether elimination has been reached. We assessed the accuracy of six different diagnostic tests in Pemba, Tanzania, a setting approaching Schistosoma haematobium elimination.
METHODOLOGY: A prospective diagnostic accuracy study was conducted from February to April 2025. From an initial cross-sectional single-day urine filtration (UF)-microscopy screening of 784 students, 69 S. haematobium-positive and 212 negative students were randomly selected for longitudinal follow-up. Four additional urine samples collected over four different days, were available from 262/281 participants and subjected to UF-microscopy. One sample per participant was analysed in parallel with five additional diagnostics: microscopy-based artificial intelligence (AI) scanner, Schistosoma-ITS-2 qPCR, S. haematobium-Dra-1 recombinase polymerase amplification (RPA), Hemastix reagent strips, and up-converting particle lateral flow circulating anodic antigen assay (UCP-LF CAA). We assessed the sensitivity and specificity of the different diagnostics, using 5-day UF-microscopy as reference test.
PRINCIPAL FINDINGS: A total of 85/262 participants were S. haematobium-positive using 5-day UF-microscopy. Directly compared with the reference test, the sensitivity for single-sample examination was: AI scanner: 76.7% (95% confidence interval (CI): 71.0-82.5%), qPCR: 76.0% (95% CI: 70.1-81.4%), UF-microscopy: 61.2% (95% CI: 55.3-67.1%), RPA: 56.1% (95% CI: 50.0-62.2%), Hemastix: 44.6% (95% CI: 38.5-50.7%), and UCP-LF CAA: 30.6% (95% CI: 24.9-36.3%). Sensitivity increased with increasing infection intensity. The specificity of all investigated diagnostics was >92%, except for qPCR and RPA.
CONCLUSIONS/SIGNIFICANCE: In near-elimination settings, multiple-day urine examination with standard UF-microscopy substantially improves case detection but is operationally challenging. For single-sample testing, among the six diagnostics investigated, the AI scanner proved to be the most accurate. Hence, the AI scanner might offer a promising alternative for research, clinical and programme use, but requires further validation in other settings and cost-effectiveness analyses. Trial registration: clinicaltrials.gov, NCT06808750. Registered 08 January 2025, https://clinicaltrials.gov/study/NCT06808750.
METHODOLOGY: A prospective diagnostic accuracy study was conducted from February to April 2025. From an initial cross-sectional single-day urine filtration (UF)-microscopy screening of 784 students, 69 S. haematobium-positive and 212 negative students were randomly selected for longitudinal follow-up. Four additional urine samples collected over four different days, were available from 262/281 participants and subjected to UF-microscopy. One sample per participant was analysed in parallel with five additional diagnostics: microscopy-based artificial intelligence (AI) scanner, Schistosoma-ITS-2 qPCR, S. haematobium-Dra-1 recombinase polymerase amplification (RPA), Hemastix reagent strips, and up-converting particle lateral flow circulating anodic antigen assay (UCP-LF CAA). We assessed the sensitivity and specificity of the different diagnostics, using 5-day UF-microscopy as reference test.
PRINCIPAL FINDINGS: A total of 85/262 participants were S. haematobium-positive using 5-day UF-microscopy. Directly compared with the reference test, the sensitivity for single-sample examination was: AI scanner: 76.7% (95% confidence interval (CI): 71.0-82.5%), qPCR: 76.0% (95% CI: 70.1-81.4%), UF-microscopy: 61.2% (95% CI: 55.3-67.1%), RPA: 56.1% (95% CI: 50.0-62.2%), Hemastix: 44.6% (95% CI: 38.5-50.7%), and UCP-LF CAA: 30.6% (95% CI: 24.9-36.3%). Sensitivity increased with increasing infection intensity. The specificity of all investigated diagnostics was >92%, except for qPCR and RPA.
CONCLUSIONS/SIGNIFICANCE: In near-elimination settings, multiple-day urine examination with standard UF-microscopy substantially improves case detection but is operationally challenging. For single-sample testing, among the six diagnostics investigated, the AI scanner proved to be the most accurate. Hence, the AI scanner might offer a promising alternative for research, clinical and programme use, but requires further validation in other settings and cost-effectiveness analyses. Trial registration: clinicaltrials.gov, NCT06808750. Registered 08 January 2025, https://clinicaltrials.gov/study/NCT06808750.