OBJECTIVES: A model for predicting respiratory syncytial virus hospitalization in infants born 33-35 weeks' gestational age (wGA) has been developed from the Spanish FLIP study risk factors. The model correctly classified 71% of cases and the area under the receiver operating characteristic (ROC) curve was 0.791. To assess its applicability in Italy, the model was validated against data from the Osservatorio VRS study. METHODS: Discriminant function analysis was used to validate the model by (a) using the predictive variables identified in FLIP to generate a function from the Italian data and (b) applying the coefficients from the FLIP calculations to the Italian data. RESULTS: The function calculated from the Italian data provided 77% accurate classification (ROC: 0.773). Applying the FLIP coefficients to the Italian data resulted in correctly classifying 68% of cases and a ROC of 0.760. The number needed to treat to prevent hospitalization of 80% of at risk infants was 13.4, based on a hospitalization rate of 5% and 80% treatment efficacy. CONCLUSIONS: The Italian data confirm the predictive ability of the model, which could be used to target palivizumab prophylaxis in Italian infants born 33-35 wGA.
Simões, E.A.F., Carbonell-Estrany, X., Fullarton, J.R., Rossi, G.A., Barberi, I., Lanari, M. (2011). European risk factors' model to predict hospitalization of premature infants born 33-35 weeks' gestational age with respiratory syncytial virus: validation with Italian data. THE JOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE, 24(1), 152-157 [10.3109/14767058.2010.482610].
European risk factors' model to predict hospitalization of premature infants born 33-35 weeks' gestational age with respiratory syncytial virus: validation with Italian data
BARBERI, IGNAZIO;LANARI, MARCELLO
2011
Abstract
OBJECTIVES: A model for predicting respiratory syncytial virus hospitalization in infants born 33-35 weeks' gestational age (wGA) has been developed from the Spanish FLIP study risk factors. The model correctly classified 71% of cases and the area under the receiver operating characteristic (ROC) curve was 0.791. To assess its applicability in Italy, the model was validated against data from the Osservatorio VRS study. METHODS: Discriminant function analysis was used to validate the model by (a) using the predictive variables identified in FLIP to generate a function from the Italian data and (b) applying the coefficients from the FLIP calculations to the Italian data. RESULTS: The function calculated from the Italian data provided 77% accurate classification (ROC: 0.773). Applying the FLIP coefficients to the Italian data resulted in correctly classifying 68% of cases and a ROC of 0.760. The number needed to treat to prevent hospitalization of 80% of at risk infants was 13.4, based on a hospitalization rate of 5% and 80% treatment efficacy. CONCLUSIONS: The Italian data confirm the predictive ability of the model, which could be used to target palivizumab prophylaxis in Italian infants born 33-35 wGA.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.