Use of nonlinear mixed-effects analysis for improved precision of early pharmacodynamic measures in tuberculosis treatment

Nonlinear mixed-effects analysis of serial sputum colony-counting data supports the existence of two bacillary subpopulations in sputum, eliminated at different rates. It distinguishes between combination regimens, removes bias, and greatly improves precision, with significant implications for the analysis of surrogate endpoints of sterilization in the development of new antituberculosis regimens.