Development and Validation of a Clinical Diagnostic Scoring System for the Diagnosis of Idiopathic Pulmonary Fibrosis.

Rationale: Interpreting the radiologic data in conjunction with an objective clinical score could help to harmonize idiopathic pulmonary fibrosis (IPF) diagnosis and improve accuracy. Objectives: We sought to establish and validate a multivariable objective scoring model based on clinical parameters by stratifying the risk of patients having IPF diagnosed versus having other forms of interstitial lung disease (ILD) diagnosis. Methods: A clinical score was derived from review of patients evaluated at the Inova Fairfax ILD Program and validated in three distinct cohorts. On the basis of known IPF clinical characteristics, a multivariable model was created and assessed by using receiver operating characteristic curves. Results: There were 844 patients with ILD with either IPF ( n = 347, 41%) or non-IPF ILD ( n = 497, 59%) diagnosis. On the basis of calculated odds ratios, a score was assigned to each of the following clinical parameters: age, sex, smoking history, race or ethnicity, ILD family history, exposures, presence of connective tissue disease signs or symptoms, and velcro crackles. The final Fairfax IPF Clinical Score (FICS) ranged from 1 to 25. The clinical diagnostic score system was accurate in predicting IPF, as measured by the area under the curve (0.88) in the derivation cohort, with similar areas under the curve of 0.91, 0.81, and 0.71 being demonstrated in the respective validation cohorts. Conclusions: The FICS appears to be an accurate tool for estimating the pretest probability of IPF in patients with ILD. How the FICS performs in conjunction with the various high-resolution computed tomographic patterns remains to be determined. This model could ultimately be useful for increasing the degree of confidence in the final diagnosis and could help to obviate the need for lung biopsy in cases with non-usual interstitial pneumonia patterns on high-resolution computed tomographic images.