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已发表论文
碱性磷酸酶动态变化值及中性粒细胞与淋巴细胞比值在预测非小细胞肺癌新辅助免疫化疗疗效中的价值
Authors Gong L, Yan Q, Liang D, Li L, Yang J, Wong W, Zhang S, Dai S, Zhai W, Wang J
Received 23 May 2025
Accepted for publication 3 October 2025
Published 25 October 2025 Volume 2025:18 Pages 14827—14839
DOI https://doi.org/10.2147/JIR.S542102
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Felix Marsh-Wakefield
Li Gong,1,2,* Qihang Yan,1,2,* Dachuan Liang,1,2,* Liang Li,1,2 Jie Yang,1,2 Wingshing Wong,1,2 Shuyue Zhang,1,2 Shuqin Dai,3 Wenyu Zhai,1,2 Junye Wang1,2
1Department of Thoracic Surgery, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, People’s Republic of China; 2Lung Cancer Research Center, Sun Yat-Sen University, Guangzhou, Guangdong, People’s Republic of China; 3Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Junye Wang; Wenyu Zhai, Department of Thoracic Surgery, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People’s Republic of China, Email wangjy@sysucc.org.cn; diwy@sysucc.org.cn
Background: Currently, reliable and convenient markers for identifying patients with non-small cell lung cancer (NSCLC) who benefit from neoadjuvant immunochemotherapy remains elusive. Established static biomarkers, such as programmed cell death ligand 1 (PD-L1) expression and tumor mutational burden (TMB), exhibit limitations in capturing dynamic changes in the immune microenvironment and predicting treatment efficacy compared to dynamic biomarkers. This study aims to evaluate the value of dynamic peripheral blood markers in predicting pathological complete response (pCR) and survival outcomes in patients with NSCLC undergoing neoadjuvant immunochemotherapy.
Methods: In this retrospective analysis, clinicopathological data, along with baseline and post-treatment laboratory results, were examined from 113 patients with NSCLC who received neoadjuvant immunochemotherapy between October 2019 and April 2023. The least absolute shrinkage and selection operator (LASSO) algorithm was employed to identify candidate dynamic peripheral blood markers, which were then further refined using logistic regression. An integrated nomogram model incorporating the optimal biomarkers was developed to predict individual pCR. Event-free survival (EFS) was analyzed using the Kaplan-Meier method, with comparisons performed via the Log rank test.
Results: Dynamic alkaline phosphatase (dALP) and dynamic neutrophil-to-lymphocyte ratio (dNLR) emerged as independent predictors of pCR following neoadjuvant immunochemotherapy, as confirmed by LASSO and multivariate logistic regression. A predictive model, incorporating dNLR, dALP, degree of differentiation, and smoking history, demonstrated strong predictive capability (AUC = 0.745). Internal validation through bootstrapped resampling yielded a mean AUC of 0.728 (95% CI 0.686– 0.749). Survival analysis revealed that patients who achieved pCR had significantly better EFS, and those with low dNLR and dALP values exhibited superior EFS compared to the high-value group.
Conclusion: The findings indicate that dNLR and dALP can serve as independent predictors of pCR and EFS in patients with NSCLC treated with neoadjuvant immunochemotherapy. The pCR prediction model incorporating these two markers showed excellent predictive performance, providing valuable clinical guidance for selecting patients who are most likely to benefit from neoadjuvant immunochemotherapy.
Keywords: NSCLC, neoadjuvant immunochemotherapy, peripheral blood dynamic indicators, pCR, survival benefit
1Department of Thoracic Surgery, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, People’s Republic of China; 2Lung Cancer Research Center, Sun Yat-Sen University, Guangzhou, Guangdong, People’s Republic of China; 3Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Junye Wang; Wenyu Zhai, Department of Thoracic Surgery, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People’s Republic of China, Email wangjy@sysucc.org.cn; diwy@sysucc.org.cn
Background: Currently, reliable and convenient markers for identifying patients with non-small cell lung cancer (NSCLC) who benefit from neoadjuvant immunochemotherapy remains elusive. Established static biomarkers, such as programmed cell death ligand 1 (PD-L1) expression and tumor mutational burden (TMB), exhibit limitations in capturing dynamic changes in the immune microenvironment and predicting treatment efficacy compared to dynamic biomarkers. This study aims to evaluate the value of dynamic peripheral blood markers in predicting pathological complete response (pCR) and survival outcomes in patients with NSCLC undergoing neoadjuvant immunochemotherapy.
Methods: In this retrospective analysis, clinicopathological data, along with baseline and post-treatment laboratory results, were examined from 113 patients with NSCLC who received neoadjuvant immunochemotherapy between October 2019 and April 2023. The least absolute shrinkage and selection operator (LASSO) algorithm was employed to identify candidate dynamic peripheral blood markers, which were then further refined using logistic regression. An integrated nomogram model incorporating the optimal biomarkers was developed to predict individual pCR. Event-free survival (EFS) was analyzed using the Kaplan-Meier method, with comparisons performed via the Log rank test.
Results: Dynamic alkaline phosphatase (dALP) and dynamic neutrophil-to-lymphocyte ratio (dNLR) emerged as independent predictors of pCR following neoadjuvant immunochemotherapy, as confirmed by LASSO and multivariate logistic regression. A predictive model, incorporating dNLR, dALP, degree of differentiation, and smoking history, demonstrated strong predictive capability (AUC = 0.745). Internal validation through bootstrapped resampling yielded a mean AUC of 0.728 (95% CI 0.686– 0.749). Survival analysis revealed that patients who achieved pCR had significantly better EFS, and those with low dNLR and dALP values exhibited superior EFS compared to the high-value group.
Conclusion: The findings indicate that dNLR and dALP can serve as independent predictors of pCR and EFS in patients with NSCLC treated with neoadjuvant immunochemotherapy. The pCR prediction model incorporating these two markers showed excellent predictive performance, providing valuable clinical guidance for selecting patients who are most likely to benefit from neoadjuvant immunochemotherapy.
Keywords: NSCLC, neoadjuvant immunochemotherapy, peripheral blood dynamic indicators, pCR, survival benefit