Pan-Immune-Inflammatory Value in Patients with Non-Small-Cell Lung Cancer Undergoing Neoadjuvant Immunochemotherapy - Zhai WY; Duan FF; Lin YB; Lin YB; Zhao ZR; Wang JY; Rao BY; Zheng L; Long H (Dove Medical Press, 2023)
Wen-Yu Zhai,1,2,* Fang-Fang Duan,3,* Yao-Bin Lin,1,2,* Yong-Bin Lin,1,2 Ze-Rui Zhao,1,2 Jun-Ye Wang,1,2 Bing-Yu Rao,1,2 Lie Zheng,4 Hao Long1,2 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, People's Republic of China; 2Lung Cancer Research Center, Sun Yat-Sen University, Guangzhou, People's Republic of China; 3Department of Medical oncology, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China; 4Medical Imaging Division, Department of Medical Imaging and Interventional Radiology, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China*These authors contributed equally to this workCorrespondence: Hao Long, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, and Department of Thoracic Surgery, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China, Email longhao@sysucc.org.cn Lie Zheng, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, and Medical Imaging Division, Department of Medical Imaging and Interventional Radiology, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China, Email zhenglie@sysucc.org.cnBackground: We aimed to investigate the predictive value of a systematic serum inflammation index, pan-immune-inflammatory value (PIV), in pathological complete response (pCR) of patients treated with neoadjuvant immunotherapy to further promote ideal patients' selection.Methods: The clinicopathological and baseline laboratory information of 128 NSCLC patients receiving neoadjuvant immunochemotherapy between October 2019 and April 2022 were retrospectively reviewed. We performed least absolute shrinkage and selection operator (LASSO) algorithm to screen candidate serum biomarkers for predicting pCR, which further entered the multivariate logistic regression model to determine final biomarkers. Accordingly, a diagnostic model for predicting individual pCR was established. Kaplan-Meier method was utilized to estimate curves of disease-free survival (DFS), and the Log rank test was analyzed to compare DFS differences between patients with and without pCR.Results: Patients with NSCLC heterogeneously responded to neoadjuvant immunotherapy, and those with pCR had a significant longer DFS than patients without pCR. Through LASSO and the multivariate logistic regression model, PIV was identified as a predictor for predicting pCR of patients. Subsequently, a diagnostic model integrating with PIV, differentiated degree and histological type was constructed to predict pCR, which presented a satisfactory predictive power (AUC, 0.736), significant agreement between actual and our nomogram-predicted pathological response.Conclusion: Baseline PIV was an independent predictor of pCR for NSCLC patients receiving neoadjuvant immunochemotherapy. A significantly longer DFS was achieved in patients with pCR rather than those without pCR; thus, the PIV-based diagnostic model might serve as a practical tool to identify ideal patients for neoadjuvant immunotherapeutic guidance.Keywords: non-small-cell lung cancer, pan-immune-inflammatory value, neoadjuvant immunochemotherapy, pathological complete response, survival benefits