Intestinal schistosomiasis: Can a urine sample decide the infection?

Area of Science:

• Neglected tropical diseases
• Parasitology
• Diagnostic accuracy

Background:

• Intestinal schistosomiasis diagnosis relies on the Kato-Katz (KK) method, which has low sensitivity, especially in low transmission areas.
• Accurate prevalence estimation is vital for controlling neglected tropical diseases like schistosomiasis.
• Bayesian latent class analysis offers a method to compare diagnostic tests without a gold standard.

Purpose of the Study:

• To compare the diagnostic accuracy of two urine-based tests (POC-CCA and PCR) against the KK method for detecting Schistosoma mansoni.
• To evaluate diagnostic performance using Bayesian latent class analysis, considering different models for POC-CCA trace results.

Main Methods:

• Bayesian latent class analysis framework was employed to compare KK, POC-CCA, and PCR.
• Two models were used for POC-CCA: trace results considered positive and trace results considered negative.
• Sensitivity and specificity of each test were estimated.

Main Results:

• In the trace-positive POC-CCA model, disease prevalence was estimated at 26%. POC-CCA showed 74% sensitivity and 20% specificity, while KK had lower sensitivity (≤22%) but higher specificity.
• In the trace-negative POC-CCA model, POC-CCA demonstrated 77% sensitivity and 81% specificity. PCR showed 80% sensitivity and 69% specificity.
• KK consistently had the lowest sensitivity across both models.

Conclusions:

• Urine-based POC-CCA (trace-negative model) and PCR are highly sensitive and specific for diagnosing intestinal schistosomiasis, surpassing the KK method.
• A single urine sample may be sufficient for accurate diagnosis in low endemicity settings.
• However, relying on a single diagnostic tool may limit disease management strategies in areas with low endemicity.