Background: Inadequate tuberculosis (TB) diagnostics are a major hurdle in the reduction of disease burden and accurate point-of-care tests (POCT) are urgently needed. We assessed the diagnostic accuracy of Fujifilm SILVAMP TB LAM (FujiLAM) for TB diagnosis in HIV-negative outpatients compared to Alere Determine TB LAM Ag (AlereLAM) and a laboratory-based ultrasensitive electrochemiluminescence LAM research assay (EclLAM). Methods: In this multicentre diagnostic test accuracy study, we recruited HIV-negative adults with symptoms suggestive of pulmonary TB presenting to outpatient healthcare centres in Peru and South Africa. Urine samples were tested using FujiLAM, AlereLAM and EclLAM and the diagnostic accuracy was assessed against microbiological (MRS) and composite reference standards. Results: 372 HIV-negative participants were included and the prevalence of microbiologically confirmed TB was 30%. Compared to the MRS, the sensitivities of AlereLAM, FujiLAM and EclLAM were 10.8% (95% CI 6.3to18.0), 53.2% (43.9to62.1), and 66.7% (57.5to74.7) respectively. The specificities of AlereLAM, FujiLAM and EclLAM were 92.3% (88.5to95.0), 98.9% (96.7to99.6), and 98.1% (95.6to99.2) respectively. Positive Likelihood Ratio of AlereLAM, FujiLAM and EclLAM were 1.4, 46.2, and 34.8 and positive predictive values 37.5%, 95.2%, and 93.7% respectively. Conclusion: Compared to AlereLAM, FujiLAM detected five times more TB patients in HIV-negative participants, has a high positive predictive value and has the potential to improve rapid diagnosis of TB at the point-of-care. EclLAM demonstrated that additional sensitivity gains are possible, which highlights LAMs potential as a biomarker. Additional research is required to assess FujiLAMs performance in prospective cohorts, its cost-effectiveness, and its impact in real-world clinical settings.
Tobias Broger, Mark Nicol, George Sigal, Eduardo Gotuzzo, Alexandra J. Zimmer, Shireen Surtie, Tatiana Caceres-Nakiche, Anna Mantsoki, Elena Ivanova Reipold, Rita Székely, Michael Tsionsky, Judith van Heerden, Tatiana Plisova, Kinuyo Chikamatsu, Todd L. Lowary, Abraham Pinter, Satoshi Mitarai, Emmanuel Moreau, Samuel G Schumacher, Claudia M. Denkinger