Nomogram prediction model of cervical anastomotic leakage after esophageal cancer surgery.
10.3760/cma.j.cn112152-20201127-01026
- Author:
Shan Rui MA
1
;
Hao FENG
2
;
Ge Fei ZHAO
3
;
Hui Jun BAI
2
;
Liang ZHAO
1
;
Zi Ran ZHAO
1
Author Information
1. Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100021, China.
2. Administration Office of Science and Technology Projects, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China.
3. Department of Thoracic Surgery, Zhongshan Hospital of Fudan University, Shanghai 200433, China.
- Publication Type:Journal Article
- Keywords:
Anastomotic leakage;
Esophageal neoplasms;
Nomogram;
Risk factors
- MeSH:
Humans;
Anastomotic Leak/etiology*;
Nomograms;
Retrospective Studies;
Esophageal Neoplasms/surgery*;
Esophagectomy/methods*;
Risk Factors;
Anastomosis, Surgical/adverse effects*
- From:
Chinese Journal of Oncology
2023;45(12):1065-1076
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To retrospectively analyze the risk factors of anastomotic leakage in the neck after esophageal cancer and establish a nomogram prediction model that can accurately predict the occurrence of anastomotic leakage in the neck of the patient. Methods: The study retrospectively analyzed 702 patients who underwent radical esophageal cancer surgery between January 2010 and May 2015 at Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. A multivariate logistic regression model was used to determine the risk factors for neck anastomotic leak, and a nomogram model was constructed, internal validation methods were used to evaluate and verify the predictive effectiveness of the nomogram. Results: There were 702 patients in the whole group, 492 in the training group and 210 in the validation group. The incidence of postoperative cervical anastomotic leak was 16.1% (79/492) in 492 patients with esophageal cancer in the training group. Multifactorial analysis revealed calcification of the descending aorta (OR=2.12, 95% CI: 1.14, 3.94, P=0.018), calcification of the celiac artery (OR=2.29, 95% CI: 1.13, 4.64, P=0.022), peripheral vascular disease (OR=5.50, 95% CI: 1.64, 18.40, P=0.006), postoperative ventilator-assisted breathing (OR=5.33, 95% CI: 1.83, 15.56, P=0.002), pleural effusion or septic chest (OR=3.08, 95% CI: 1.11, 8.55, P=0.031), incisional fat liquefaction and infection (OR=3.49, 95% CI: 1.68, 7.27, P=0.001) were independent risk factors for the development of cervical anastomotic leak after esophageal cancer surgery. The results of the nomogram prediction model showed that the consistency indices of the training and external validation groups were 0.73 and 0.74, respectively (P<0.001), suggesting that the prediction model has good predictive efficacy. Conclusion: The nomogram prediction model can intuitively predict the incidence of postoperative cervical anastomotic leakage in patients with high prediction accuracy, which can help provide a clinical basis for preventing cervical anastomotic leak and individualized treatment of patients.
