Comorbidity in Patients with Idiopathic Pulmonary Fibrosis: Evaluation Using the Charlson, TORVAN and GAP Indices

Introduction: Idiopathic pulmonary fibrosis (IPF) is associated with high morbidity and mortality and a substantial burden of comorbidities, which may influence prognosis and survival. This study aimed to evaluate the burden of comorbidity in patients with IPF receiving antifibrotic therapy using the Charlson, TORVAN, and GAP indices and to analyse their relationships and prognostic impact on survival. Methods: Retrospective observational study including patients with IPF diagnosed according to ATS/ERS/JRS/ALAT criteria. Patients receiving antifibrotic therapy between June 2010 and September 2025 were included. Baseline comorbidities were recorded, and the Charlson, TORVAN, and GAP indices were calculated. Associations between indices were assessed using chi-square tests and kappa statistics. Survival was analysed using Kaplan–Meier curves and compared with the log-rank test. Cox proportional hazards regression and model comparison metrics (Harrell’s C-index and Akaike Information Criterion) were also performed to assess the independent prognostic value of each index. Results: Seventy-two patients were included (76.7% male; mean age 73.8 ± 7.4 years). Pirfenidone was prescribed in 63.9% and nintedanib in 36.1%. The most frequent comorbidities were gastro-oesophageal reflux disease (62.5%), arterial hypertension (57.5%), pulmonary hypertension (32.9%), diabetes mellitus (24.7%), and non-metastatic solid tumours (17.6%), including lung cancer. Survival differed significantly according to GAP stage (p = 0.020) and Charlson categories (p = 0.006). The TORVAN stage was associated with the GAP stage (p < 0.001; kappa = 0.246), whereas the Charlson index showed no association with GAP or TORVAN. Conclusions: In this cohort of patients with IPF receiving antifibrotic therapy, both the GAP and Charlson indices were associated with survival. These findings suggest that combining disease-specific and comorbidity indices may provide a more comprehensive prognostic assessment, although further validation in larger cohorts is required.