Derivation and validation of a noninvasive prediction tool to identify pulmonary hypertension in patients with IPF: Evolution of the model FORD

Background: The administration of inhaled prostanoids to patients with pulmonary hypertension (PH) related to idiopathic pulmonary fibrosis (IPF) and other fibrotic lung diseases improves functional outcomes. Selection of patients with IPF at risk for concomitant PH to undergo right heart catheterization (RHC) remains challenging. We sought to develop a clinical prediction tool based on common noninvasive parameters to identify PH in patients with IPF. Methods: A prediction model based on noninvasive parameters was derived from patients enrolled in the ARTEMIS-IPF randomized, placebo-controlled clinical trial. Predictor variables were tested for association with the presence of PH diagnosed based on RHC. The derived multivariable logistic regression model and associated point-score index were then externally validated in a real-world cohort of patients with IPF. Results: Of the 481 patients included in the ARTEMIS-IPF study, 9.8% (N = 47) were diagnosed with PH related to IPF. Four variables were associated with PH and were included in the final model: forced vital capacity/diffusing capacity for carbon monoxide ratio (F), oxygen saturation nadir during 6-minute walk test (6MWT) (O), race (R), and distance ambulated during 6MWT (D). A model containing continuous predictors (FORD calculator) and a simple point-score system (FORD index) performed similarly well in the derivation cohort (area under the curve [AUC]: 0.75 and 0.75, respectively) and validation cohort (AUC: 0.69 and 0.69, respectively). Conclusions: The FORD models are simple, validated tools incorporating noninvasive parameters that can be applied to identify patients at risk of PH related to IPF who may benefit from invasive testing.