Objectives To predict peak oxygen uptake (VO_2peak) from the peak work rate (W_peak) obtained during a cycle ergometry test using the Godfrey protocol in adolescents with cystic fibrosis (CF), and assess the accuracy of the model for prognostication clustering.

Methods Out of our database of anthropometric, spirometric and maximal exercise data from adolescents with CF (N=363; 140 girls and 223 boys; age 14.77±1.73 years; mean expiratory volume in 1 s (FEV_1%pred) 86.82±17.77%), a regression equation was developed to predict VO_2peak (mL/min). Afterwards, this prediction model was validated with cardiopulmonary exercise data from another 60 adolescents with CF (28 girls, 32 boys; mean age 14.6±1.67 years; mean FEV_1%pred 85.43±20.01%).

Results We developed a regression model VO_2peak (mL/min)=216.3–138.7×sex (0=male; 1=female)+11.5×W_peak; R²=0.91; SE of the estimate (SEE) 172.57. A statistically significant difference (107 mL/min; p<0.001) was found between predicted VO_2peak and measured VO_2peak in the validation group. However, this difference was not clinically relevant because the difference was within the SEE of the model. Furthermore, we found high positive predictive and negative predictive values for the model for prognostication clustering (PPV 50–87% vs NPV 82–94%).

Conclusions In the absence of direct VO_2peak assessment it is possible to estimate VO_2peak in adolescents with CF using only a cycle ergometer. Furthermore, the regression model showed to be able to discriminate patients in different prognosis clusters based on exercise capacity.