Pathologic Complete Response Prediction to Neoadjuvant Immunotherapy Combined with Chemotherapy in Resectable Locally Advanced Esophageal Squamous Cell Carcinoma: Real-World Evidence from Integrative Inflammatory and Nutritional Scores

Jifeng Feng; Liang Wang; Xun Yang; Qixun Chen; Xiangdong Cheng

doi:10.2147/JIR.S367964

Pathologic Complete Response Prediction to Neoadjuvant Immunotherapy Combined with Chemotherapy in Resectable Locally Advanced Esophageal Squamous Cell Carcinoma: Real-World Evidence from Integrative Inflammatory and Nutritional Scores

J Inflamm Res. 2022 Jul 6:15:3783-3796. doi: 10.2147/JIR.S367964. eCollection 2022.

Authors

Jifeng Feng^{1

2

3}, Liang Wang¹, Xun Yang¹, Qixun Chen¹, Xiangdong Cheng²

Affiliations

¹ Department of Thoracic Oncological Surgery, Cancer Hospital of University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, People's Republic of China.
² Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Key Laboratory of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer of Zhejiang Province, Cancer Hospital of University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, People's Republic of China.
³ The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, People's Republic of China.

Abstract

Purpose: Neoadjuvant immunotherapy and chemotherapy (nICT) is an emerging hotspot that has been shown to be safe and feasible for locally advanced esophageal squamous cell carcinoma (LA-ESCC). This real-world study aimed to develop and validate a novel predictive model [integrative inflammatory and nutritional score (IINS)] in LA-ESCC patients receiving nICT to predict the pathologic complete response (pCR).

Patients and methods: Patients with LA-ESCC who received nICT followed by surgery from Jun 2019 to Dec 2021 were enrolled and randomly divided into two sets (7:3). Using least absolute shrinkage and selection operator (LASSO) logistic regression analysis, the IINS was constructed in LA-ESCC patients received nICT to predict pCR. A nomogram based on IINS for pCR prediction was generated in the training cohort and verified in the validation cohort.

Results: Of the 285 enrolled LA-ESCC patients received nICT followed by radical resection, 84 (29.5%) patients achieved pCR. A predictive index of IINS based on 8 inflammatory and nutritional indicators was constructed using the LASSO model. According to the cutoff finder, patients were then stratified into two groups (high and low). The pCR rates were significantly higher in high-IINS group than in low-IINS group in both the training cohort (44.7% vs 17.4%, P < 0.001) and validation cohort (50.0% vs 13.3%, P < 0.001). The IINS [odds ratio (OR) = 0.237, 95% confidence interval (CI) = 0.117-0.480, P < 0.001] was an independent significant predictor for pCR in multivariate logistic analyses. The IINS-based nomogram showed an excellent discrimination for pCR prediction (C-indexes = 0.759 and 0.812 for training and validation cohorts, respectively).

Conclusion: Pretreatment IINS is an independent predictor for pCR in LA-ESCC patients who are treated with nICT. To our knowledge, the IINS-based nomogram is the first model for pCR prediction and may serve as a simple and potential risk stratification model in LA-ESCC who are treated with nICT.

Keywords: chemotherapy; esophageal squamous cell carcinoma; immunotherapy; inflammatory and nutritional score; neoadjuvant therapy; pathologic complete response.

Grants and funding

This study was supported by Zhejiang Medical and Health Science and Technology Project (2017KY237, 2018KY022 and 2019RC129). This study was also supported by Zhejiang TCM Science and Technology Project (2020ZB036, 2021ZB034 and 2022ZB051).