Validation of a model to predict hospitalization due to RSV of infants born at 33-35 weeks' gestation

J Perinat Med. 2010 Jul;38(4):411-7. doi: 10.1515/jpm.2010.074.

Abstract

Background: A model to predict hospitalization due to respiratory syncytial virus (RSV) of infants born at 33- 35 weeks' gestation was developed using seven risk factors from the Spanish FLIP study "birth +/-10 weeks from the beginning of the RSV season", "birth weight", "breast fed <or=2 months", "number of siblings >or=2 years", "number of family members with atopy", "number of family members with wheezing", and "gender". The aim of this study was to validate the model using French data.

Methods: The FLIP model [predictive accuracy 71%, receiver operating characteristic (ROC) 0.791] was tested against the French data (77 hospitalized infants with RSV born at 33-35 weeks and 154 age-matched controls) using discriminatory function analysis by applying the FLIP coefficients to the French data and by generating the seven variable model from the French data.

Results: Applying the FLIP coefficients to the French dataset, the model correctly classified 69% of cases (ROC 0.627). The predictive power increased to 73% (ROC 0.654) when "number of siblings >or=2 years" was substituted for "number of children at school". The number needed to treat (NNT) in order to prevent 70% of hospitalizations was 18. The model derived using French data could correctly classify 62% of cases in the French data (ROC 0.658).

Conclusions: The model was successfully validated and may potentially optimize immunoprophylaxis in French infants born at 33-35 week's gestation.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Case-Control Studies
  • Databases, Factual
  • Female
  • France
  • Gestational Age
  • Hospitalization*
  • Humans
  • Infant
  • Infant, Newborn
  • Infant, Premature
  • Models, Biological
  • Pregnancy
  • Respiratory Syncytial Virus Infections / therapy*
  • Respiratory Syncytial Virus, Human*
  • Risk Factors