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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

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...

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Autores principales: Feng, Jifeng, Wang, Liang, Yang, Xun, Chen, Qixun, Cheng, Xiangdong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9271687/
https://www.ncbi.nlm.nih.gov/pubmed/35832830
http://dx.doi.org/10.2147/JIR.S367964
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author Feng, Jifeng
Wang, Liang
Yang, Xun
Chen, Qixun
Cheng, Xiangdong
author_facet Feng, Jifeng
Wang, Liang
Yang, Xun
Chen, Qixun
Cheng, Xiangdong
author_sort Feng, Jifeng
collection PubMed
description 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.
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spelling pubmed-92716872022-07-12 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 Feng, Jifeng Wang, Liang Yang, Xun Chen, Qixun Cheng, Xiangdong J Inflamm Res Original Research 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. Dove 2022-07-06 /pmc/articles/PMC9271687/ /pubmed/35832830 http://dx.doi.org/10.2147/JIR.S367964 Text en © 2022 Feng et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Feng, Jifeng
Wang, Liang
Yang, Xun
Chen, Qixun
Cheng, Xiangdong
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9271687/
https://www.ncbi.nlm.nih.gov/pubmed/35832830
http://dx.doi.org/10.2147/JIR.S367964
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