Derivation and validation of a non-invasive prediction tool to identify pulmonary hypertension in patients with IPF: evolution of the model FORD.

RATIONALE: The administration of inhaled prostanoids to patients with pulmonary hypertension (PH) related to idiopathic pulmonary fibrosis (IPF) and other fibrotic interstitial lung diseases improves functional outcomes. Selection of patients with IPF at high risk for concomitant PH to undergo right heart catheterization (RHC) remains challenging.

OBJECTIVE: To develop a simple clinical prediction tool based on commonly measured non-invasive parameters to facilitate the identification of PH in patients with IPF METHODS: A clinical prediction model based on non-invasive parameters was derived in 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 from 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: FVC%/DLCO% ratio (F), oxygen saturation nadir during 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 (AUC: 0.75 and 0.75, respectively) and validation cohort (AUC: 0.69 and 0.69, respectively).

CONCLUSION: The FORD models are simple, validated tools incorporating non-invasive parameters that can be applied to identify patients at high risk of PH related to IPF who may benefit from invasive testing.