OPEN-IPF: Observational Prediction modEl for cliNical Outcomes in Idiopathic Pulmonary Fibrosis

OPEN-IPF addresses the current limitation of AI/ML research in IPF-namely, the lack of large multicentre real-world datasets with harmonised variables and robust external validation. The study will retrospectively include adult patients with IPF followed in routine practice in participating Italian referral centres from 1 January 2015 to 31 December 2025 (data lock). No study-specific procedures will be performed. De-identified/pseudonymised data will be collected using a common data model, including demographics, smoking history, comorbidities, pulmonary function (FVC, DLCO), oxygen requirement, 6-minute walk test (where available), antifibrotic treatment exposure, HRCT features routinely reported, basic laboratory parameters, and clinical outcomes. The primary modelling targets are disease progression, acute exacerbations of IPF (AE-IPF), and real-world response to antifibrotic treatment. Model development will be performed using multicentre data with explicit external validation across centres

Inclusion criteria

• Age ≥18 years
• Diagnosis of idiopathic pulmonary fibrosis established according to international guidelines and local multidisciplinary team (MDT) assessment
• Availability of baseline clinical and functional data
• Availability of follow-up data for at least 12 months, or until a clinically relevant event (e.g., death, lung transplantation)

Exclusion criteria

• Interstitial lung disease other than IPF
• Lung transplantation performed before the baseline (index) date
• Absence of any follow-up information after baseline