Predicting anastomotic leak in patients with esophageal squamous cell cancer treated with neoadjuvant chemoradiotherapy using a nomogram based on CT radiomic and clinicopathologic factors.

IF 3.4 2区 医学 Q2 ONCOLOGY BMC Cancer Pub Date : 2025-03-15 DOI:10.1186/s12885-025-13884-9
Junfeng Zhao, Guanli Yang, Ying Li, Shanshan Li, Haining Luo, Dan Han, Baosheng Li, Qiang Cao
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引用次数: 0

Abstract

Background: Anastomotic leak (AL) is a common complication in patients with operable esophageal squamous cell carcinoma (ESCC) treated with neoadjuvant chemoradiotherapy (NCRT) and radical esophagectomy. Therefore, this study aimed to establish and validate a nomogram to predict the occurrence of AL.

Methods: Between March 2016 and December 2022, ESCC patients undergoing NCRT and radical esophagectomy were retrospectively collected in China. Clinicopathologic and radiomics characteristics were included in the univariate logistic regression analysis, and statistically significant factors were enrolled to develop the nomogram, which was evaluated by the area under the curve (AUC) of the receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA).

Results: 231 eligible patients were divided into training (n = 159) and validation cohorts (n = 72). Univariate and multivariate analyses revealed that dose at the anastomosis ≥ 24 Gy, gross tumor volume ≥ 60 cm3, postoperative albumin < 35 g/L, comorbidities, duration of surgery ≥ 270 min, and computed tomography-based radiomics characteristics were independent predictors of AL. The nomogram AUC in the training and validation cohorts was 0.845 (95% confidence interval [CI]: 0.770-0.920) and 0.839 (95% CI: 0.718-0.960), respectively, indicating good discriminatory ability. The calibration curves showed good agreement between the predicted and actual AL occurrence and the DCA demonstrated favorable clinical outcomes.

Conclusions: We developed and validated a nomogram based on radiomics and clinicopathologic characteristics. This predictive model could be a powerful tool to predict AL occurrence in patients with ESCC treated with NCRT.

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利用基于 CT 放射线学和临床病理学因素的提名图预测接受新辅助化放疗的食管鳞状细胞癌患者的吻合口漏。
背景:吻合口漏(AL)是可手术食管鳞状细胞癌(ESCC)接受新辅助放化疗(NCRT)和根治性食管切除术的常见并发症。因此,本研究旨在建立并验证预测al发生的nomogram。方法:回顾性收集2016年3月至2022年12月在中国接受NCRT和根治性食管切除术的ESCC患者。将临床病理和放射组学特征纳入单因素logistic回归分析,并纳入有统计学意义的因素形成nomogram,通过受试者工作特征曲线、校准曲线和决策曲线分析(decision curve analysis, DCA)的曲线下面积(area under the curve, AUC)进行评价。结果:231例符合条件的患者被分为训练组(n = 159)和验证组(n = 72)。单因素和多因素分析显示,吻合口剂量≥24 Gy,肿瘤总体积≥60 cm3,术后白蛋白。结论:我们建立并验证了基于放射组学和临床病理特征的nomographic。该预测模型可能是预测NCRT治疗ESCC患者AL发生的有力工具。
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来源期刊
BMC Cancer
BMC Cancer 医学-肿瘤学
CiteScore
6.00
自引率
2.60%
发文量
1204
审稿时长
6.8 months
期刊介绍: BMC Cancer is an open access, peer-reviewed journal that considers articles on all aspects of cancer research, including the pathophysiology, prevention, diagnosis and treatment of cancers. The journal welcomes submissions concerning molecular and cellular biology, genetics, epidemiology, and clinical trials.
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