Association of idiopathic pulmonary fibrosis with TG/HDL-C and TC/HDL-C: a retrospective cohort study

Accumulating evidence suggests a significant link between dyslipidaemia—characterized by an imbalance in circulating lipids and lipoproteins—and the pathogenesis and progression of various chronic respiratory conditions. However, their mechanistic role in idiopathic pulmonary fibrosis (IPF) pathogenesis has yet to be fully elucidated. This study aimed to explore the associations of idiopathic pulmonary fibrosis (IPF) with TG/HDL-C and TC/HDL-C in Chinese adults. This study included 129 patients in the stable phase of IPF, 85 patients with acute exacerbation (AE-IPF), and 130 non-IPF controls. The evaluation included routine blood tests (encompassing the lipid profile) and pulmonary function assessments. Additionally, a follow-up with a median duration of 5.84 months was conducted in 183 IPF patients. Compared with values observed in stable cases or control subjects, the levels of both TG/HDL-C and TC/HDL-C were markedly elevated in subjects with AE-IPF. Following adjustment for potential confounders, logistic regression models revealed that both TG/HDL-C and TC/HDL-C were independent factors positively correlated with the presence of AE-IPF. In assessing the predictive power for AE-IPF, the area under the ROC curve corresponding to TG/HDL-C exceeded that of TC/HDL-C and all other conventional lipid levels. During a median follow-up of 5.84 months, 81 IPF patients passed away. Nonsurvivors had higher baseline TG/HDL-C and TC/HDL-C levels than survivors did. Multivariate Cox regression analysis adjusted for age, sex, and oxygenation index revealed that the adjusted hazard ratios for overall survival with each 1-SD increase in TG/HDL-C and TC/HDL-C were 1.809 (95% CI: 1.497–2.184, P < 0.001) and 1.486 (95% CI: 1.183–1.867, P = 0.001), respectively. Elevated TG/HDL-C and TC/HDL-C ratios are independently associated with acute exacerbation and poor short-term survival in IPF patients. The TG/HDL-C ratio, in particular, represents a candidate biomarker for risk stratification, which requires further external validation.