Fig. 4

Predictors of drug resistance in Mycobacterium tuberculosis isolates from extra-pulmonary sites. The variable importance scores and proportion of the variance explained by interactions between the variables that were obtained from stochastic gradient modeling for any drug resistance are shown in Fig. 4a, while those for MDR-TB/Rifampin monoresistance are shown in Fig. 4b. Multivariate adaptive regression trees (MARS) for binary outcomes with two-way interactions detection were made in the TreeNet software. The optimal representative classification and regression trees (CART) are shown in Fig. 4c for any resistance and in Fig. 4d for MDR-TB/Rifampin monoresistance. The primary node (disease site) for any drug in Fig. 4c is almost identical to that for MDR-TB/Rifampin monoresistance in Fig. 4d, the difference being addition of meninges to the former group. The sensitivity for both is 0.72 (95% CI: 0.56–0.84). However, positive predictive value for the former is 0.44 (95% 0.32–0.57) and for the latter is 0.36 (95% 0.25–0.48). The MDR-TB/Rifampin monoresistance group necessarily excludes the three isoniazid monoresistance isolates, hence the overall number of isolates analyzed in Figs. 4c/d are 67 and not 70