Meaningful Thresholds for Change in Quantitative CT–Derived Fibrosis Extent in Idiopathic Pulmonary Fibrosis

RATIONALE: Validated thresholds for clinically meaningful change in quantitative CT (QCT) for fibrosis extent across algorithms remain unclear in idiopathic pulmonary fibrosis (IPF). OBJECTIVES: To evaluate minimal clinically important difference (MCID) for 1-year change in QCT metrics in IPF using different algorithms than previously reported, and to identify prognostically meaningful thresholds for effective risk stratification. METHODS: This multicenter retrospective study included IPF patients with baseline and 1-year follow-up CT. MCIDs for change in fibrosis score (ΔFS) derived from fully-automated CT quantification were estimated using an anchor-based approach with 1-year changes in forced vital capacity (FVC) and diffusing capacity for carbon monoxide (DLco), and a prognostic threshold was estimated using maximally selected log-rank statistics. Prognostic significance of ΔFS was evaluated in discovery and validation cohorts. RESULTS: The discovery cohort included 524 patients (mean age, 66.8 years; 79% men), and the external validation cohort included 224 patients (mean age, 69.6 years; 83% men). Anchor-based MCIDs were 2.72% for FVC and 4.52% for DLco, with a prognostic threshold of 4.05%. In the discovery cohort, 1-year ΔFS were independently associated with transplant-free survival (TFS), with greater risk when ΔFS exceeded MCID or prognostic thresholds (all, P < .001). In the validation cohort, ΔFS remained associated with TFS (adjusted HR, 1.11; 95%CI, 1.04-1.18), and all prespecified ΔFS thresholds were prognostic for overall TFS, with the prognostic threshold of ΔFS ≥ 4.05% showing the most consistent associations with both overall (adjusted HR, 2.78; 95%CI, 1.36-5.68) and 3-year TFS (adjusted HR, 2.88; 95%CI, 1.11-7.48). CONCLUSION: One-year change in FS and its thresholds were significantly associated with TFS, supporting annual CT follow-up with predefined QCT thresholds for monitoring and risk stratification in IPF.