Prospective evaluation of a dose prediction algorithm for intravenous tobramycin in adolescent and adult patients with cystic fibrosis

The predictive performance of a new algorithm to calculate the initial daily dose of tobramycin in patients with cystic fibrosis (CF) was prospectively evaluated. Twenty-six patients with CF (15 men, 11 women, 18-45 years of age) with an acute exacerbation of their chronic pulmonary infection were treated with intravenous tobramycin. The initial dose was calculated with a previously presented algorithm. This algorithm was derived from correlation analysis performed on the adjusted daily dose guided by the determination of serum concentrations: dose (mg three times daily) = 90 + 2.13 x LBM (kg), where LBM (male) = (1.1 x body weight [BW]) - (128 x BW2/height2) and LBM (female) = (1.07 x BW) - (148 x BW2/height2). The predictive performance of this algorithm was evaluated comparing the calculated initial daily dose with the adjusted daily dose for peak and trough levels of 9-11 mg/L and 1.0 mg/L, respectively. Mean squared error and mean error were determined as reflections of precision and bias. The predictive performance of the algorithm was compared with historical data on the predictive performance of the standard equation to dose of 3.3 mg/kg body weight three times daily. The dose calculated with the algorithm proved to give peak serum concentrations in a narrower range and to have a greater precision, but bias was equal. Applying the algorithm, more patients had initial peak serum concentrations in the pre-determined range of 9-11 mg/L than when using the standard equation, so fewer dose adjustments had to be made.