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A scoring system to predict the technical difficulty of endoscopic resection for cardial submucosal tumors
Zi-Han Geng1,2, Yi-Fan Qu1,2, Pei-Yao Fu1,2
1Endoscopy Center and Endoscopy Research Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
Insights
A new clinical scoring model predicts technical difficulty for endoscopic resection of cardial submucosal tumors (SMTs). Factors include male gender, extraluminal growth, and tumor diameter, aiding procedural planning.
Area of Science:
- Gastroenterology
- Surgical Oncology
- Medical Technology
Background:
- Endoscopic resection is effective for digestive submucosal tumors (SMTs).
- The cardia presents unique challenges for endoscopic resection due to anatomical constraints.
- Predicting technical difficulty is crucial for successful cardial SMT removal.
Purpose of the Study:
- To develop a clinical scoring model for grading the technical difficulty of endoscopic resection for cardial SMTs.
- To provide clinicians with a tool for better procedural planning and risk assessment.
Main Methods:
- Retrospective analysis of 246 patients undergoing endoscopic resection for cardial SMTs.
- Patients were divided into training (n=123) and validation (n=123) cohorts.
- Logistic regression identified predictors (male gender, extraluminal growth, tumor diameter ≥3 cm) for a scoring system.
Main Results:
- The developed scoring model incorporates male gender (2 points), extraluminal growth (3 points), and maximum diameter ≥3 cm (3 points).
- The model demonstrated strong discriminatory power (AUC=0.860) and good fit (Hosmer-Lemeshow P=0.979).
- The model accurately predicted varying probabilities of technical difficulty across different score categories in both training and validation cohorts.
Conclusions:
- The established clinical scoring system is a valuable tool for predicting the technical difficulty of endoscopic resection for cardial SMTs.
- This model can assist clinicians in anticipating challenges and optimizing surgical strategies.
Background And Aim:
Endoscopic resection has been successfully used for the removal of digestive submucosal tumors (SMTs). However, the cardia has been considered a challenging location for endoscopic resection due to its narrow lumen and sharp angle. The objective of this study was to establish a clinical scoring model to grade the technical difficulty of endoscopic resection for cardial SMTs.
Methods:
A total of 246 patients who suffered cardial SMTs and received endoscopic resection were included in this retrospective study. All of them were randomized into the training cohort (n = 123) or internal validation cohort (n = 123). Potential predictors were analyzed using univariate analysis. Then, covariates with P < 0.05 were selected for the multivariate logistic regression model. The β coefficients from the logistic regression model were used to create a scoring system for technical difficulty prediction by rounding the score to the nearest integer of the absolute β coefficient value.
Results:
The clinical score consisted of the following factors: male gender (2 points), extraluminal growth (3 points), and maximum diameter ≥3 cm (3 points). The scoring model demonstrated good discriminatory power, with an area under the receiver operating characteristic curve of 0.860 and a 95% confidence interval of 0.763-0.958. The model also showed a good goodness of fit in the Hosmer-Lemeshow test (P = 0.979). In the training cohort, the probability of encountering technical difficulty in the easy (score = 0), intermediate (score = 1-3), difficult (score = 4-6), and very difficult (score >6) categories was 0, 6.8%, 33.3%, and 100.0%, respectively; similarly, in the validation cohort, it was 0, 5.6%, 22.2%, and 50.0%, respectively.
Conclusions:
This scoring system could serve as a valuable tool for clinicians in predicting the technical difficulty of endoscopic resection for cardial SMTs.
