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Updated: May 9, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
The Lung Cancer Immune Prognostic Score predicts pathologic complete response and survival in NSCLC patients
Yuyan Xie1, Zhihao Shi1, Tong Chen1
1Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Introduction:
Neoadjuvant immunochemotherapy (nICT) has significantly improved event-free survival (EFS) and pathologic complete response (pCR) in patients with resectable non-small cell lung cancer (NSCLC). However, the lack of validated biomarkers limits their ability to predict therapeutic efficacy and survival outcomes. This study aimed to develop a novel inflammatory and nutritional index, the Lung Cancer Immune Prognostic Score (LCIPS), to predict pCR and survival prognosis in patients with NSCLC.
Methods:
This retrospective study included 131 patients with clinical stage IB-IIIB NSCLC who underwent neoadjuvant immunochemotherapy between May 2020 and May 2024. Baseline clinical data and hematological parameters were collected. Lasso regression analysis was employed to identify hematological indices associated with pCR, and the LCIPS was constructed based on these factors. Kaplan-Meier survival analysis and log-rank tests were used to assess survival differences. Logistic regression was performed to identify the predictors of pCR, while Cox regression analysis determined independent prognostic factors for disease-free survival (DFS) and overall survival (OS). The predictive performance of the LCIPS was validated using a nomogram.
Results:
Lasso regression identified three core hematological indices: the albumin-to-globulin ratio (A/G), absolute monocyte count (MONO), and absolute lymphocyte count (LYM). The LCIPS formula was as follows: LCIPS=0.900×A/G+0.761×MONO (109/L) -0.065×LYM (109/L). Receiver operating characteristic (ROC) curve analysis showed that the LCIPS had superior predictive efficacy (area under the curve (AUC) = 0.68) compared to other classical markers. Univariate and multivariate logistic regression analyses identified intraoperative lymph node dissection status and A/G and LCIPS as independent predictors of pCR (p < 0.05). Multivariate Cox regression analysis demonstrated that smoking status and LCIPS were independent prognostic factors for DFS and OS. Nomogram validation indicated robust predictive accuracy for LCIPS. Notably, among immune-related adverse events (irAEs), endocrine- and cardiac-related irAEs significantly affected DFS (p < 0.05).
Discussion:
LCIPS is an independent predictor of pCR in patients with NSCLC receiving neoadjuvant immunochemotherapy and is associated with improved DFS and survival outcomes. This novel index offers valuable guidance for personalized treatment strategies.
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