• Brett Ley, Christopher J Ryerson, Eric Vittinghoff, Jay H Ryu, Sara Tomassetti, Joyce S Lee, Venerino Poletti, Matteo Buccioli, Brett M Elicker, Kirk D Jones, Talmadge E King, and Harold R Collard.
• Department of Medicine, University of California, San Francisco, 505 Parnassus Avenue, Box 0111, San Francisco, CA 94143, USA. brett.ley@ucsf.edu
• Ann. Intern. Med. 2012 May 15;156(10):684-91.

BackgroundIdiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease with an overall poor prognosis. A simple-to-use staging system for IPF may improve prognostication, help guide management, and facilitate research.ObjectiveTo develop a multidimensional prognostic staging system for IPF by using commonly measured clinical and physiologic variables.DesignA clinical prediction model was developed and validated by using retrospective data from 3 large, geographically distinct cohorts.SettingInterstitial lung disease referral centers in California, Minnesota, and Italy.Patients228 patients with IPF at the University of California, San Francisco (derivation cohort), and 330 patients at the Mayo Clinic and Morgagni-Pierantoni Hospital (validation cohort).MeasurementsThe primary outcome was mortality, treating transplantation as a competing risk. Model discrimination was assessed by the c-index, and calibration was assessed by comparing predicted and observed cumulative mortality at 1, 2, and 3 years.ResultsFour variables were included in the final model: gender (G), age (A), and 2 lung physiology variables (P) (FVC and Dlco). A model using continuous predictors (GAP calculator) and a simple point-scoring system (GAP index) performed similarly in derivation (c-index of 70.8 and 69.3, respectively) and validation (c-index of 69.1 and 68.7, respectively). Three stages (stages I, II, and III) were identified based on the GAP index with 1-year mortality of 6%, 16%, and 39%, respectively. The GAP models performed similarly in pooled follow-up visits (c-index ≥71.9).LimitationPatients were drawn from academic centers and analyzed retrospectively.ConclusionThe GAP models use commonly measured clinical and physiologic variables to predict mortality in patients with IPF.

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