Predicting survival in idiopathic pulmonary fibrosis: scoring system and survival model

Am J Respir Crit Care Med. 2001 Oct 1;164(7):1171-81. doi: 10.1164/ajrccm.164.7.2003140.


Our purpose was to identify clinical, radiological and physiological (CRP) determinants of survival and to develop a CRP scoring system that predicts survival in newly diagnosed cases of idiopathic pulmonary fibrosis (IPF). The study population consisted of 238 patients with biopsy confirmed usual interstitial pneumonia. For each patient, clinical manifestations, chest radiographs, and pulmonary physiology were prospectively assessed. We used Cox proportional-hazards models to assess the effect of these parameters on survival. The effects of age and smoking were included in the analysis. Survival was related to age, smoking status (longer in current smokers), clubbing, the extent of interstitial opacities and presence of pulmonary hypertension on the chest radiograph, reduced lung volume, and abnormal gas exchange during maximal exercise. A mathematical CRP score for predicting survival was derived from these parameters. We showed that this CRP score correlated with the extent and severity of the important histopathologic features of IPF, i.e., fibrosis, cellularity, the granulation/connective tissue deposition, and the total pathologic derangement. Using these models, clinicians are in a better position to provide prognostic information to patients with IPF and to improve the selection of the most appropriate patients for lung transplantation or other standard or novel therapeutic interventions.

Publication types

  • Comparative Study
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Female
  • Humans
  • Male
  • Middle Aged
  • Models, Statistical
  • Multivariate Analysis
  • Prognosis
  • Prospective Studies
  • Pulmonary Fibrosis / diagnosis
  • Pulmonary Fibrosis / mortality*
  • Pulmonary Fibrosis / physiopathology
  • Respiratory Insufficiency / etiology
  • Respiratory Insufficiency / mortality
  • Survival Analysis
  • Survival Rate