Fibrotic lung diseases have high morbidity and mortality, and established prognostic indicators include thoracic imaging and pulmonary function testing. Metabolic dysfunction and insulin resistance have been proposed as contributors to chronic lung disease pathobiology. The triglyceride-glucose (TyG) index—calculated from fasting triglyceride and glucose levels—is a surrogate marker of insulin resistance that has been associated with cardiovascular outcomes and diabetes risk in other settings. This study aimed to assess whether variability in the TyG index within the non-diabetic range is associated with baseline pulmonary function and all-cause mortality in patients with fibrotic lung disease who initiated antifibrotic therapy.
This is a retrospective cohort study using electronic medical records from a tertiary referral center specialized in respiratory diseases. Eligible patients were adults (≥18 years) with radiological evidence of pulmonary fibrosis who started pirfenidone or nintedanib between 1 January 2015 and 1 June 2023. Data extraction occurred between 15 July 2023 and 20 October 2023. Baseline clinical, laboratory, and functional variables were obtained at the time closest to antifibrotic initiation (or within a one-month window for metabolic labs).
The TyG index was calculated as Ln[(fasting triglycerides (mg/dL) × fasting glucose (mg/dL)) / 2]. Fasting status was recorded per laboratory designation and routine practice but could not be independently verified for every measurement. The primary outcome was all-cause mortality from the date of antifibrotic therapy initiation to death or last clinical follow-up.
From an initial screen of 970 patients, the final analytic cohort comprised 144 patients after excluding individuals with a documented diagnosis of diabetes mellitus, those on fenofibrate, and cases without triglyceride measurements. Radiological inclusion required features such as honeycombing, traction bronchiectasis/bronchiolectasis, or interlobular septal thickening as part of an overall fibrotic pattern. Because retrospective subtype classification was not uniformly available, the cohort included a clinically heterogeneous group of fibrotic lung diseases.
Collected baseline variables included demographics, comorbidities recorded in the medical record (hypertension, COPD, cardiovascular disease, malignancy), smoking status and pack-years, pulmonary function test results (FVC, FVC%, DLCO, DLCO%), 6-minute walk test (6-MWT) distance, and fasting glucose and triglyceride values used to compute TyG.
Diabetes mellitus was identified only by a physician-documented diagnosis in the record; new diabetes was not retrospectively assigned based on laboratory values. Smoking categories followed standard definitions (never, former, current), and pack-years were used to quantify cumulative exposure. The primary study outcome was death from any cause during follow-up. Secondary analyses examined relationships between TyG and baseline PFT measures and 6-MWT distance, and compared metabolic parameters between deceased and surviving patients.
Descriptive statistics characterized the cohort. Correlations between TyG and pulmonary function measures were assessed using Pearson or Spearman correlation coefficients depending on distribution. Univariable Cox regression was performed for candidate predictors. Given the limited number of mortality events (54 deaths), the multivariable Cox model was constrained to five variables chosen for clinical relevance and multicollinearity considerations: sex, smoking pack-years, COPD, FVC%, and TyG index. Continuous variables were entered as continuous terms. Analyses used complete-case data without imputation. A two-sided p-value < 0.05 denoted statistical significance.
The final cohort (n = 144) had a mean age of 67.4 years; 31.9% were female. Current smokers represented 59.7% of the cohort, former smokers 8.3%, and never smokers 25.7%; among ever-smokers the median pack-years was 35 (IQR 20–45). Comorbidities were recorded in 69% of patients, most commonly hypertension (51%), cardiovascular disease (35%), and COPD (24%). Antifibrotic treatment was pirfenidone in 45.1% and nintedanib in 54.9% of patients. Median follow-up time was 33.8 months (IQR 17.0–55.0 months).
Baseline pulmonary function showed mean FEV1% 79%, mean FVC% 74.2%, and mean DLCO% 50.6%. Mean 6-MWT distance was 384 meters. Metabolic measures at baseline included a median triglyceride level of 123 mg/dL (IQR 92–169), median glucose 100 mg/dL (IQR 91–110), and mean TyG index 8.78. During follow-up, 54 patients (37.5%) died.
In multivariable Cox regression adjusted for sex, smoking pack-years, COPD, and FVC%, the TyG index was not significantly associated with all-cause mortality (adjusted hazard ratio 0.80, 95% CI 0.40–1.60, p = 0.54). Lower FVC% and greater cumulative smoking exposure were independently associated with higher mortality in the adjusted model. Exploratory correlation analyses did not reveal consistent associations between TyG and baseline pulmonary function measures; a weak inverse correlation with DLCO was noted but not robust.
In this selected cohort of non-diabetic patients with radiographic fibrotic lung disease who initiated antifibrotic therapy, variability in the TyG index within the non-diabetic range was not significantly associated with all-cause mortality after adjustment for clinical covariates. Standard measures of respiratory impairment—particularly lower FVC%—and cumulative smoking exposure remained associated with mortality. The study does not support a clear prognostic role for TyG in this specific, selected population, although the authors note that limited metabolic variability and statistical precision may have reduced the ability to detect modest associations.
Important limitations include the retrospective design, selection of a tertiary-center antifibrotic-treated cohort, exclusion of patients with diabetes (thereby narrowing metabolic variability), reliance on physician-documented comorbidity entries without independent adjudication, potential uncertainty about fasting status for some laboratory values, and a limited number of events that constrained multivariable modeling. These factors reduce generalizability and statistical precision. The authors recommend prospective studies in broader populations with greater metabolic heterogeneity and standardized data collection to clarify whether the TyG index or other metabolic markers have independent prognostic value in fibrotic lung disease.