Prognostic significance of the lymphocyte-to-high-density lipoprotein ratio in long-term efficacy of combined immunotherapy for advanced non-small cell lung cancer - Ma, Gaolei; Ma, Lijie; Zhang, Yuan; Chen, Yuanyuan; Zhang, Yingnan; Guo, Wenwen; Yao, Zhiyuan; Ji, Guijuan (Frontiers in Oncology, 2025)
BackgroundLung cancer remains the leading cause of cancer incidence and mortality worldwide. Non-small cell lung cancer (NSCLC) accounts for approximately 80%–85% of cases, and the majority of patients are diagnosed at an advanced stage with poor prognosis. Immune checkpoint inhibitors (ICIs) combined with chemotherapy have become the standard first-line treatment for advanced NSCLC, significantly improving survival outcomes. However, considerable inter-individual variability in treatment response persists, underscoring the urgent need for novel predictive biomarkers. Systemic inflammation and immune status are closely associated with immunotherapy efficacy. Lymphocytes play a critical role as effector cells in antitumor immunity, while high-density lipoprotein (HDL), beyond its role in lipid metabolism, also exerts anti-inflammatory and immunomodulatory functions. The lymphocyte-to-HDL ratio (LHR), a composite indicator integrating immune and metabolic status, has demonstrated prognostic value in several malignancies. Nevertheless, its predictive significance in advanced NSCLC patients receiving chemo-immunotherapy remains unclear. This study aims to evaluate the prognostic value of LHR for long-term outcomes in this population, thereby providing insights for individualized treatment strategies.AimTo investigate the predictive value of the lymphocyte-to-high-density lipoprotein ratio (LHR) for long-term outcomes in patients with advanced non-small cell lung cancer (NSCLC) receiving chemo-immunotherapy, and to evaluate its potential as a convenient and cost-effective biomarker for guiding individualized clinical treatment.MethodsThis single-center retrospective study included 287 patients with advanced non-small cell lung cancer (NSCLC) who received first-line treatment with immune checkpoint inhibitors (ICIs) combined with platinum-based chemotherapy. Pretreatment lymphocyte-to-high-density lipoprotein ratio (LHR) levels were calculated, and the optimal cutoff value was determined using receiver operating characteristic (ROC) curve analysis. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent prognostic factors associated with progression-free survival (PFS) and overall survival (OS). Based on these factors, a nomogram prediction model was developed. Variable selection was guided by clinical relevance, routine applicability, and data availability. Model performance was evaluated using the concordance index (C-index), area under the ROC curve (AUC), and calibration plots.ResultsBased on the optimal cutoff value determined by ROC curve analysis, 287 patients with advanced NSCLC were stratified into a low LHR group (<35.3) and a high LHR group (≥35.3). The median progression-free survival (PFS) was significantly longer in the low LHR group compared with the high LHR group (17.00 [14.00–22.00] vs. 11.80 [9.80–14.50] months; p = 0.028). Similarly, the median overall survival (OS) was 24.00 (21.00–29.00) months in the low LHR group and 18.00 (16.00–20.00) months in the high LHR group (p < 0.001). The objective response rate (ORR) and disease control rate (DCR) were also higher in the low LHR group than in the high LHR group (ORR: 48.92% vs. 35.81%, p = 0.025; DCR: 87.77% vs. 78.38%, p = 0.035). Multivariate Cox regression analysis identified LHR, PD-L1 expression, distant metastasis, and carcinoembryonic antigen (CEA) as independent prognostic factors for both PFS and OS (all p < 0.05). A nomogram prediction model for PFS and OS was subsequently developed based on these factors. In the training cohort, the C-index of the PFS model was 0.73 (95% CI: 0.69–0.78), with an internal validation C-index of 0.78 (95% CI: 0.71–0.85), indicating good discriminative ability. The AUCs for 6- and 12-month PFS prediction were 0.82 (95% CI: 0.76–0.89) and 0.86 (95% CI: 0.75–0.96) in the training cohort, and 0.87 (95% CI: 0.80–0.93) and 0.89 (95% CI: 0.81–0.97) in the validation cohort, respectively. For OS prediction, the C-index values were 0.80 (95% CI: 0.76–0.84) in the training cohort and 0.82 (95% CI: 0.77–0.86) in the validation cohort. The model demonstrated high accuracy in predicting OS at 12, 18, and 24 months: training cohort AUCs of 0.81 (95% CI: 0.74–0.89), 0.85 (95% CI: 0.74–0.91), and 0.94 (95% CI: 0.90–0.98), and validation cohort AUCs of 0.89 (95% CI: 0.80–0.98), 0.88 (95% CI: 0.80–0.96), and 0.82 (95% CI: 0.71–0.93), respectively. Calibration plots showed strong agreement between predicted and observed outcomes, confirming the model’s robustness and clinical applicability.ConclusionThis study demonstrated that the lymphocyte-to-high-density lipoprotein ratio (LHR) is an independent predictor of long-term outcomes in patients with advanced NSCLC receiving chemo-immunotherapy. A low LHR was associated with improved progression-free survival, overall survival, and higher objective response and disease control rates. The nomogram model incorporating LHR showed favorable predictive accuracy and clinical applicability.