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。
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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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