f Our study aims to identify the clinical breakpoints (CBPs) of second-line drugs (SLDs) above which standard therapy fails in order to improve multidrug-resistant tuberculosis (MDR-TB) treatment. MICs of SLDs were determined for M. tuberculosis isolates cultured from 207 MDR-TB patients in a prospective cohort study in China between January 2010 and December 2012. Classification and regression tree (CART) analysis was used to identify the CBPs predictive of treatment outcome. Of the 207 MDR-TB isolates included in the present study, the proportion of isolates above the critical concentration recommended by WHO ranged from 5.3% in pyrazinamide to 62.8% in amikacin. By selecting pyrazinamide as the primary node (CBP, 18.75 mg/ liter), 72.1% of sputum culture conversions at month four could be predicted. As for treatment outcome, pyrazinamide (CBP, 37.5 mg/liter) was selected as the primary node to predict 89% of the treatment success, followed by ofloxacin (CBP, 3 mg/liter), improving the predictive capacity of the primary node by 10.6%. Adjusted by identified confounders, the CART-derived pyrazinamide CBP remained the strongest predictor in the model of treatment outcome. Our findings indicate that the critical breakpoints of some second-line drugs and PZA need to be reconsidered in order to better indicate MDR-TB treatment outcome.M ycobacterium tuberculosis is a major public health problem worldwide (1). The emergence of multidrug-resistant (MDR) M. tuberculosis strains has complicated treatment and is associated with increased treatment failure (2). A reduction in the efficacy of second-line drugs (SLDs) against MDR tuberculosis (MDR-TB) strains with resistance to SLDs has been described in observational studies (2, 3). Subtle changes in drug susceptibility may be predictive of clinical failures, especially when the drug susceptibility testing (DST) result is at the borderline of the susceptibility range.Susceptibility testing for M. tuberculosis is increasingly being utilized in diagnostic laboratories to guide TB treatment. However, there has been considerable debate regarding the critical concentrations used to define resistance of antituberculosis drugs (4, 5). Until now, the standard approach for identifying antibiotic susceptibility breakpoints has been the epidemiological cutoff method. This method is based on the MIC distribution of a drug, which identifies the upper 95% cutoff point on the Gaussian curve of wild-type susceptible M. tuberculosis isolates (6-8). However, Gumbo, using Monte Carlo simulations, concluded that current critical concentrations of first-line drugs were overoptimistic, and new susceptibility breakpoints should be defined considering microbiologic and clinical outcomes (4). Therefore, clinical outcome studies including MIC results are needed. The aim of this study was to identify the clinical breakpoints (CBPs) in a cohort of MDR-TB patients in China and to develop a decision tree to better predict treatment outcomes of MDR-TB patients.
MATERIALS AND METHODS
Study design.We con...