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Chinese Journal of Thoracic Surgery(Electronic Edition) ›› 2024, Vol. 11 ›› Issue (01): 31-39. doi: 10.3877/cma.j.issn.2095-8773.2024.01.04

• Original Article • Previous Articles    

Large-scale retrospective study of positive surgical margins in esophageal squamous cell carcinoma and the establishment and validation of a clinical predictive model

Zhiyu Li1, Changding Li2, Xin Nie2, Kunhan Ni2, Yongtao Han2,(), Xuefeng Leng2,()   

  1. 1. Department of Thoracic Surgery, The People’s Hospital of Leshan, Leshan 614000, China
    2. Department of Thoracic Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu 610041, China
  • Received:2023-07-20 Revised:2023-11-16 Accepted:2024-02-04 Online:2024-02-28 Published:2024-03-26
  • Contact: Yongtao Han, Xuefeng Leng

Abstract:

Objective

Esophageal squamous cell carcinoma (ESCC) has a high incidence and mortality rate in China. The presence of positive surgical margins (PSM) after surgery suggests a poor prognosis. Therefore, this study aims to establish a feasible clinical prediction model to predict and verify the likelihood of PSM after surgery in ESCC patients.

Methods

By searching the Sichuan Cancer Hospital and Institute Esophageal Cancer Case Management Database (SCH-ECCM database) from January 2010 to December 2017, a total of 2 846 patients who underwent ESCC radical surgery at the hospital were reviewed. After retrospectively analyzing the postoperative pathological data and clinical information, patients who have visible residual tumor on the surgical margin with the naked eye (R2) or microscopic residual tumor (R1) are identified and defined as having PSM. Logistic regression analysis was used to determine independent risk factors. Nomogram was used to construct a predictive model, and a calibration curve was plotted to compare actual risk with predicted risk. A decision curve analysis (DCA) was performed to evaluate the clinical utility of nomogram. Receiver operating characteristic (ROC) curve can be plotted to evaluate the validity of prediction model, and Bootstrap Method was used for internal validation.

Results

This study included 205 patients (7.2%) diagnosed with PSM. Logistic regression analysis showed that gender, number of lymph nodes examined, tumor location, pathological TNM stage, and thoracic surgical incision were independent risk factors for PSM. We used a nomogram to evaluate the performance of the predictive model, with a ROC area of 0.796 (95% CI 0.763~0.828, P<0.001) and a calibration curve showing good consistency between predicted and actual probabilities.

Conclusions

PSM is one of the important factors that influence postoperative treatment decisions and prognosis of patients. The nomogram we established to predict positive resection margin in patients with esophageal squamous cell carcinoma has potential clinical application value for preoperative assessment and treatment decision-making.

Key words: Esophageal squamous cell carcinoma, Surgical margin, Nomogram, Tumor residue, Prediction model

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