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Published on: May 20, 2020
Margin quality analysis for wedge resection of lung cancer and construction of a predictive model
Yuyan Zheng1, Xinyi Wang1, Chengqiang Li1
1Department of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Background:
Insufficient pulmonary wedge resection margin is associated with malignant positive margins and high local recurrence risk for lung cancer. This study aimed to identify the risk factors of insufficient or guideline discordant resection margin distance and establish a predictive model to preoperatively estimate the risk of discordant margin for individual patient.
Methods:
Guideline discordant resection margin was defined as ratio of resection margin distance to tumor size less than one. Patients who had pulmonary malignancies and underwent wedge resection between April 2014 and February 2023 were enrolled and stratified by quality of resection margin. Multivariable logistic regression analysis was employed to identify risk factors of guideline discordant margin and a predictive model was developed. Data from March 2023 to January 2024 were collected for internal validation.
Results:
A total of 530 patients were included. The incidence of guideline discordant wedge resection margin was 37.2%. Longer tumor's max distance to pleura and larger tumor size were variables associated with increased risk and included in the final model. Preoperative localization and right-side surgery were protective variables in the predictive model. A nomogram was built based on the predictive model. The model showed satisfying predictive performance with a concordance index of 0.720 for the predictive model, and 0.761 for internal validation. The goodness-if-fit tests were non-significant for both model development and internal validation data set.
Conclusions:
The preoperative predictive model and nomogram show good predictive performance to estimate the risk of guideline discordant wedge resection margin. Individualized surgical plans or preoperative nodule localization can be made for high-risk patients.
