A clinical predictive model for the long-term survival of progressive fibrosis interstitial lung disease patients.

BACKGROUND

In patients with chronic fibrosing interstitial lung disease (ILD), some may develop a progressive fibrosing (PF) phenotype, which presents as rapid progression and often results in poor clinical outcomes.

OBJECTIVE

The objective of this study was to construct and test a model to identify independent predictors of mortality in PF-ILD and to trace the lung function trajectory of patients with PF-ILD.

DESIGN

This multicenter retrospective cohort study enrolled patients with PF-ILD from two distinct centers with 8-year follow-up to develop and validate a prognostic nomogram based on clinical factors and assess longitudinal lung function trajectories.

METHODS

We enrolled patients diagnosed with PF-ILD from China-Japan Friendship Hospital (training cohort) and Jiulongpo Hospital of Traditional Chinese Medicine (validation cohort). Survival status was recorded during the 8-year follow-up period. Clinical demographics, laboratory data, pulmonary function test (PFT) results, and high-resolution computed tomography results were collected for analysis. A training cohort of patients with PF-ILD was used to identify predictors of mortality, which were then validated in an external cohort. A nomogram was established based on multivariate factors. The predictive performance of the model was evaluated using receiver operating characteristic curves and calibration curves. Survival estimates were performed using the Kaplan-Meier method and compared using the log-rank test. The PFT trajectory was estimated using a linear mixed model.

RESULTS

A total of 1419 patients with PF-ILD from China-Japan Friendship Hospital (training cohort) and 282 patients with PF-ILD from Jiulongpo Hospital of Traditional Chinese Medicine (validation cohort) were enrolled. During the 8-year follow-up, 150 (10.57%) patients received lung transplantation, while 43.55% ( = 618) of cases reached mortality, with a median survival time of 53 months in the BJ cohort. A predictive model was built based on ILD subgroups, baseline Forced Vital Capacity% (FVC%pred), baseline Diffusing Capacity of the Lung for Carbon Monoxide% (DLCO%pred), age at diagnosis, antifibrosis treatment, gastroesophageal reflux complication, C-Reactive Protein levels, and BMI. We also found AEs and progressive declines in FVC and DLCO, particularly after the third year post-diagnosis, were strongly associated with poor prognosis and may serve as important longitudinal biomarkers for risk stratification in PF-ILD.

CONCLUSION

A predictive model incorporating multiple factors effectively predicted 8-year survival in patients with PF-ILD. In addition to these baseline predictors, AEs and progressive declines in FVC and DLCO were strongly associated with poor prognosis and may serve as valuable longitudinal biomarkers for ongoing risk stratification.