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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Gastrointestinal Cancers: Gastric and Esophageal Cancers
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1347650
This article is part of the Research Topic Immune Checkpoint Inhibitors in Advanced Gastric and Esophageal Cancers View all 11 articles

Radiomics Nomogram Combined with Clinical Factors for Predicting Pathological Complete response in Resectable Esophageal Squamous Cell Carcinoma

Provisionally accepted
Zihao Lu Zihao Lu Yongsen Li Yongsen Li Wenxuan Hu Wenxuan Hu Yonghao Cao Yonghao Cao Xin Lv Xin Lv Xinyu Jia Xinyu Jia Shiyu Shen Shiyu Shen Jun Zhao Jun Zhao Chun Xu Chun Xu *
  • Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China

The final, formatted version of the article will be published soon.

    Predicting the efficacy of neoadjuvant immunochemotherapy (NICT) for esophageal squamous cell carcinoma (ESSC) prior to surgery can minimize unnecessary surgical interventions and facilitate personalized treatment strategies. Our goal is to develop and validate an image-based radiomic model using preoperative computed tomography (CT) scans and clinical data to predict pathological complete response (pCR) in resectable ESSC following neoadjuvant immunotherapy.We retrospectively collected data from patients diagnosed with ESCC at the First Affiliated Hospital of Soochow University between January 2018 and May 2023, who received preoperative neoadjuvant immunochemotherapy. Eligible patients were randomly divided into training and validation sets. Radiomic features extracted from preprocessed CT images were used to develop a radiomic model, incorporating Radiomic score (Rad-score) and clinical factors through multivariate logistic regression analysis. The model's performance was assessed for calibration, discrimination, and clinical utility in an independent validation cohort.We enrolled a total of 105 eligible participants who were randomly divided into two groups: a training set (N=74) and a validation set (N=31). After data dimension reduction and feature selection, we identified 11 radiomic features, which collectively formed the Rad-score. Rad-score had an area under the curve (AUC) of 0.83 (95% CI 0.72-0.93) in the training set and 0.78 (95% CI 0.60-0.95) in the validation set. Multivariate analysis revealed that radiological response and Neutrophil-Lymphocyte Ratio (NLR) were independent predictors of pCR, with p-values of 0.0026 and 0.0414, respectively. We developed and validated a nomogram combining Rad-score and clinical features, achieving AUCs of 0.90 (95% CI 0.82-0.98) in the training set and 0.85 (95% CI 0.70-0.99) in the validation set. The Delong test confirmed the Development and validation of a r 删除[3]:

    Keywords: Radiomics, nomogram, Pathological complete response, ESCC, Neoadjuvant immunochemotherapy

    Received: 01 Dec 2023; Accepted: 03 Oct 2024.

    Copyright: © 2024 Lu, Li, Hu, Cao, Lv, Jia, Shen, Zhao and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Chun Xu, Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu Province, China

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