Developing and validating a screening tool for female genital schistosomiasis in urban Zambia - Rogers, Erin Q.; Mwangelwa, Sepo; Kabengele, Chishiba; Kilembe, William; Vwalika, Bellington; Inambao, Mubiana; Mumba, Kawela; Chanda, Chama; Secor, William Evan; Musale, Vernon; Himukumbwa, Constance; Parker, Rachel; et al. (Frontiers in Tropical Diseases, 2024)
Background The World Health Organization estimates that 56 million women and girls live with female genital schistosomiasis (FGS) in sub-Saharan Africa. FGS is often confused with symptoms of other genital abnormalities, and gold standard diagnosis with colposcopy is infeasible in most health facilities. Schistosomiasis haematobium is endemic in Zambia, yet routine screening or diagnostic efforts for FGS remain unavailable. Our study aimed to develop and pilot test a feasible FGS screening algorithm to implement in Zambian government clinics. Methodology/Principal Findings We recruited 499 women from a longitudinal cohort of HIV-negative adult women in Lusaka and Ndola, Zambia. We used demographic, risk factor, and symptom data collected from standardized surveys, gynecological exams, and laboratory tests to develop a screening algorithm for FGS among a derivation cohort (n=349). After cross-validation using 5-fold iterative resampling, the algorithm was applied in a holdout sample of the cohort (n=150). The prevalence of FGS (ascertained by expert review) was 23.4% in the study population. The screening algorithm included childhood and travel exposure to rivers and streams; testing positive for visual inspection of the cervix with acetic acid; hematuria; reporting less than the median average age at sexual debut (<17 years); when asked what diseases can be transmitted via freshwater exposure, reporting ‘none’; being born outside of Lusaka or Copperbelt Province; and reporting occupation as ‘Housekeeper’. The screening algorithm had reasonable discrimination in the derivation cohort (area under the curve [AUC]=0.69, 95% confidence interval [CI]: 0.66-0.79, p-value<0.001). Using a score cut off ≥ 2 the risk algorithm in the derivation cohort had 77% sensitivity, 48% specificity, 35% positive predictive value, and 85% negative predictive value. Conclusions/Significance Given the prevalence of FGS and associated morbidities, improved screening for FGS is imperative. We developed a simple screening algorithm to improve the diagnosis and treatment of FGS among adult women in Zambian government clinics.