Value of urinary lipoarabinomannan levels for tuberculosis diagnosis and monitoring of therapy - Xiong, Yiqun; Shen, Zhihong; Dong, Bo; Wang, Ying; Zhu, Ying; Wei, Hongxia; Zhang, Dongliang; Che, Yang (Frontiers in Microbiology, 2025)
BackgroundThe urinary lipoarabinomannan (LAM) assay has emerged as a promising tool for tuberculosis (TB) diagnosis and treatment monitoring. This study aimed to evaluate the diagnostic and monitoring performance of LAM compared to Acid-fast bacilli (AFB), Mycobacteria Growth Indicator Tube (MGIT), and GeneXpert, and to establish its clinical utility in a stratified TB population.MethodsA prospective cohort study included TB patients stratified by AFB/MGIT status into three groups. Diagnostic accuracy was tested against composite reference standard (CRS). Early monitoring performance was assessed via serial LAM measurements during 12-week treatment. ROC/KM/Cox analyses determined optimal thresholds and predictors of LAM conversion.ResultsAgainst CRS, LAM demonstrated a sensitivity of 58.75%, which was numerically higher than AFB smear (45.00%, p = 0.082) and comparable to MGIT culture (58.75%, p = 1.00), but numerically lower than GeneXpert (61.25%, p = 0.205). In the early monitoring phase, LAM showed sustained positivity in 11.54–51.72% at week 12, compared to <15% for other methods. The diagnostic-monitoring quadrant analysis revealed LAM’s optimal positioning for monitoring (mean conversion time 4.63–11.49 weeks), compared to 0–8.25 weeks for other methods. A combined model incorporating baseline PreLAM and week 4 change (ΔLAM) showed the highest predictive value for 12 weeks conversion (AUC = 0.871–0.943). Multivariate cox analysis identified ΔLAM as independent predictors in total cohort (HR = 0.013, p = 0.001) and double positive group (HR = 0.020, p = 0.002).ConclusionUrinary LAM serves as a dual-role biomarker, providing moderate diagnostic sensitivity and dynamic monitoring signals reflecting early bacillary response to therapy. The PreLAM+ΔLAM model enables early treatment response assessment for personalized therapy.