Performance of Various Pelvic-Derived Samples for the Diagnosis of Female Genital Tract Tuberculosis by Conventional and Molecular Methods: A Systematic Review and Meta-Analysis

Abstract

Female genital tuberculosis (FGTB) is a challenging extrapulmonary manifestation of tuberculosis, often presenting with nonspecific symptoms and a paucibacillary profile, complicating diagnosis. This systematic review and meta-analysis evaluated the diagnostic performance of various pelvic-derived samples using conventional and molecular tests. A comprehensive literature search was conducted across multiple databases from inception up to August 2024, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies assessing the sensitivity, specificity, or positivity rates of tests such as Ziehl-Neelsen (ZN) staining, culture, histopathology, polymerase chain reaction (PCR), and GeneXpert MTB/RIF on samples including endometrial biopsy, aspirates, menstrual blood, and peritoneal fluid were included. Meta-analysis using bivariate random-effects models was undertaken where feasible. Endometrial samples were the most commonly evaluated among the included studies. ZN staining and culture demonstrated high specificity (pooled specificity: 1.00) but poor sensitivity (ZN: 10%; culture: 23%). Histopathology exhibited variable sensitivity (2.56-75%) and high specificity (98%). PCR showed pooled sensitivity and specificity of 54% and 97%, respectively, with considerable heterogeneity. GeneXpert demonstrated excellent specificity (pooled 100%) but low sensitivity (14%). Menstrual blood and pelvic washings were explored with variable results; other sample types had limited diagnostic value. In conclusion, endometrial biopsy/aspirate remains the most suitable specimen for FGTB diagnosis. Molecular methods, particularly PCR, offer superior sensitivity over conventional tests, while GeneXpert's high specificity supports its role in exclusion. A multimodal diagnostic approach is recommended to enhance diagnostic yield, especially in resource-limited, high-TB-burden settings.