QCT Fibrosis Score Thresholds Predict Transplant-Free Survival in IPF

Quantifying Progression in Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease whose unpredictable trajectory complicates prognostication and monitoring [1]. While antifibrotic agents can slow its course, the heterogeneity of the disease presents a clinical challenge [2, 3]. High-resolution computed tomography (HRCT) is integral to diagnosis, but visual interpretation is subject to interobserver variability and offers limited prognostic precision [4]. Quantitative computed tomography (QCT) provides an automated, objective measure of fibrotic burden that has shown potential for predicting outcomes [5]. However, its clinical adoption has been hindered by the absence of standardized, validated thresholds that define a clinically meaningful change in fibrosis extent [5].

Defining Meaningful Change in Fibrosis Extent

To address the lack of clear benchmarks for quantitative CT, a new study sought to define what constitutes a clinically significant change in fibrosis over one year. The primary goals were to establish the minimal clinically important difference (MCID) for 1-year change in QCT-derived fibrosis scores and to identify a separate threshold that was specifically prognostic for patient survival. The investigation was a multicenter retrospective study of IPF patients with baseline and 1-year follow-up CT scans. To calculate the MCID for the change in fibrosis score (ΔFS), the researchers used an anchor-based approach. This method correlates the imaging data (ΔFS) with changes in established clinical measures, in this case, 1-year changes in forced vital capacity (FVC) and diffusing capacity for carbon monoxide (DLco). A distinct prognostic threshold was also estimated using maximally selected log-rank statistics, a statistical technique that searches the data to find the optimal cut-point that most effectively separates patients into different survival outcome groups.

Establishing Clinical and Prognostic Thresholds

The researchers first identified these critical thresholds in a discovery cohort of 524 patients (mean age, 66.8 years; 79% men) and then confirmed their findings in a separate external validation cohort of 224 patients (mean age, 69.6 years; 83% men). This two-cohort design enhances the generalizability of the results. Using the anchor-based method, the study determined that the minimal clinically important difference, representing the smallest change in fibrosis likely to be perceptible to patients or clinicians, was a 1-year ΔFS of 2.72% when anchored to FVC changes. When anchored to DLco changes, the MCID was a 1-year ΔFS of 4.52%. Distinct from these MCIDs, the analysis identified a specific prognostic threshold. A 1-year increase in fibrosis score of 4.05% or more was found to be the optimal cut-point for predicting a significant difference in survival outcomes.

Predicting Transplant-Free Survival

The prognostic value of these quantitative thresholds was clearly demonstrated in the survival analyses. In the initial discovery cohort, the 1-year change in fibrosis score (ΔFS) was independently associated with transplant-free survival (TFS). The risk of death or transplant was significantly greater when ΔFS exceeded either the MCID or the prognostic thresholds (all, P < .001), confirming that even modest increases in fibrosis over one year carry prognostic weight. These findings held true in the external validation cohort, where ΔFS remained a significant predictor of TFS (adjusted hazard ratio [HR], 1.11; 95% confidence interval [CI], 1.04-1.18). All the prespecified ΔFS thresholds were prognostic for overall TFS in this second cohort, underscoring their reliability. The prognostic threshold of ΔFS ≥ 4.05% showed the most consistent and powerful association with survival. This level of progression was linked to a nearly threefold increase in the risk of death or transplant, with an adjusted HR of 2.78 (95% CI, 1.36-5.68) for overall TFS. The effect was durable over time, with a similarly strong association with 3-year TFS (adjusted HR, 2.88; 95% CI, 1.11-7.48).

Clinical Implications for Monitoring and Risk Stratification

This study provides strong evidence that the one-year change in QCT-derived fibrosis score is significantly associated with transplant-free survival in patients with IPF. The validation of specific thresholds offers clinicians objective, quantitative tools to supplement traditional pulmonary function tests. The findings support the use of annual CT scans with QCT analysis for monitoring and risk stratification. By measuring the change in fibrosis against these predefined benchmarks, such as the MCIDs (2.72% and 4.52%) or the powerful prognostic threshold (≥4.05%), physicians can more accurately track disease progression. This objective data can facilitate more precise prognostication, inform discussions with patients about their disease trajectory, and help guide decisions regarding the timing and escalation of therapy for individuals identified as being at higher risk of progression.

References

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2. Amati F, Stainer A, Polelli V, et al. Efficacy of Pirfenidone and Nintedanib in Interstitial Lung Diseases Other than Idiopathic Pulmonary Fibrosis: A Systematic Review. International Journal of Molecular Sciences. 2023. doi:10.3390/ijms24097849

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4. Manjappachar N, Sura H, Nates L, et al. B79-11 From Fibrosis Burden to Outcome Prediction in Progressive Interstitial Lung Disease: A Systematic Review of CT and Radiograph-based Artificial Intelligence/Deep Learning Models. American Journal of Respiratory and Critical Care Medicine. 2026. doi:10.1093/ajrccm/aamag162.2611

5. Dixon G, Thould H, Wells M, et al. A systematic review of the role of quantitative CT in the prognostication and disease monitoring of interstitial lung disease.. European respiratory review : an official journal of the European Respiratory Society. 2025. doi:10.1183/16000617.0194-2024