Monitoring of high-density lipoprotein cholesterol level is predictive of EGFR mutation and efficacy of EGFR-TKI in patients with advanced lung adenocarcinoma.

High-density lipoprotein cholesterol (HDL-C) has an inverse association with the incidence of lung cancer. However, whether it can be used as a predictive factor in advanced lung adenocarcinoma patients treated with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI) still remains undefined. This research aimed at studying the relationship of serum HDL-C baseline level and HDL-C kinetics to EGFR mutation, the efficacy of EGFR-TKI, and the predictive value of PFS. The presence of mutation rate in the 192 patients with lung adenocarcinoma was compared within stratified groups. Levels of baseline HDL-C and kinetics of HDL-C were analyzed retrospectively in patients treated with EGFR-TKI harboring EGFR mutation. Univariate and multivariate analyses were performed to investigate the prognostic value of HDL-C. EGFR mutation rate of HDL-C high-level group was significantly higher than that of low-level group (59.0% vs 35.6%, P=0.001). Multivariate logistic analysis showed that high-level HDL-C was an independent predictive factor for EGFR gene mutation (P=0.005; odds ratio =0.417; 95% confidence interval [CI], 0.227-0.768). Patients with a low level of HDL-C before therapy showed a progression of disease in most cases (P<0.001). According to HDL-C kinetics, patients who received EGFR-TKI treatment harboring EGFR mutation were divided into four groups. Univariate analysis showed that patients in nondecreased group had longer progression-free survival (P<0.001; hazard ratio =0.003; 95% CI, 0.001-0.018). Multivariate Cox proportional hazards model analyses showed the same result (P<0.001; hazard ratio =0.003; 95% CI, 0.001-0.018). Current results suggest that HDL-C seems to be a good independent predictive biomarker for advanced lung adenocarcinoma patients treated with the first-line EGFR-TKI. Roles of this biomarker include indicating EGFR mutation, assessing the efficacy of EGFR-TKI, and predicting the progression-free survival.