Construction of A Survival Prediction Model for Immunotherapy in Locally Advanced or Metastatic Non-Small Cell Lung Cancer Based on PD-L1 Expression Combined with Nutritional Status Score
10.3971/j.issn.1000-8578.2026.25.0897
- VernacularTitle:PD-L1表达水平联合营养状况评分构建局部晚期或转移性非小细胞肺癌免疫治疗的生存预测模型
- Author:
Jinhua LI
1
;
Ping QI
1
;
Jili MA
1
;
Yaxia LYU
1
;
Caihong FU
2
;
Longxia ZHANG
3
;
Hui QIAO
4
Author Information
1. The First Clinical Medical College of Lanzhou University, Lanzhou 730000, China.
2. Department of Respiratory Oncology, The Gansu Provincial Cancer Hospital, Lanzhou 730000, China.
3. Department of Oncology, The First Hospital of Lanzhou University, Lanzhou 730000, China.
4. The First Clinical Medical College of Lanzhou University, Lanzhou 730000, China;Department of Oncology, The First Hospital of Lanzhou University, Lanzhou 730000, China.
- Publication Type:CLINICALRESEARCH
- Keywords:
Non-small cell lung cancer;
Immunotherapy;
Controlling nutritional status score;
Survival analysis;
Prognostic prediction model
- From:
Cancer Research on Prevention and Treatment
2026;53(6):457-466
- CountryChina
- Language:Chinese
-
Abstract:
Objective To analyze the factors affecting the prognosis of patients with locally advanced or metastatic non-small cell lung cancer (NSCLC) undergoing immunotherapy and construct an individualized prognostic nomogram prediction model. Methods A retrospective analysis was conducted on the clinical data of 385 patients with driver gene-negative, locally advanced or metastatic NSCLC who received first-line immune checkpoint inhibitors. Univariate and multivariate Cox regression analyses were used to identify prognostic risk factors, and a prognostic nomogram model was established. The predictive performance of the model was evaluated using the concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves and area under the curve (AUC), and calibration curves. The cutoff value of the nomogram was calculated to stratify patients by risk. Survival curves were calculated by Kaplan-Meier analysis. Results Age (HR=1.775, 95%CI: 1.265-2.490), degree of differentiation (HR=0.365, 95%CI: 0.257-0.519), low PD-L1 expression (HR=0.661, 95%CI: 0.455-0.960), high PD-L1 expression (HR=0.423, 95%CI: 0.297-0.603), SCC-Ag (HR=1.549, 95%CI: 1.109-2.163), and CONUT score (HR=2.527, 95%CI: 1.797-3.554) were independent risk factors affecting overall survival (OS) of patients with NSCLC undergoing immunotherapy. The nomogram prediction model constructed on the basis of these factors had a C-index of 0.767. Time-dependent ROC curves for survival showed that the AUCs for 1-, 2-, and 3-year OS were 0.830, 0.853, and 0.886, respectively. Calibration curves indicated that the nomogram-predicted survival rates were in good agreement with the actual outcomes. The cutoff value for the study’s nomogram prediction model was 136.60 points, and survival curves showed statistically significant differences between different risk groups (P<0.05). Conclusion The nomogram model established in this study can effectively predict the prognosis of patients with driver gene-negative locally advanced or metastatic NSCLC treated with first-line immunosuppressive therapy. It provides a new tool for assessing prognosis and aids clinicians in formulating individualized treatment plans.
