A Statistical Analysis of the Role of Various Co-variables in Determining the Number of Nodes to be Dissected in Endometrial Cancer Using the CART Model, AHGPIC - Parija, Jita; Nayak, Bhagyalaxmi; Padhi, Ashok; Pattnaik, Smruti Sudha; Mohapatra, Manoranjan; Mohaptra, Janmejaya; Das, Rekha; Devi, Padmalaya; Kumar Giri, Sushil; Samantray, Sagarika; et al. (Asian Pacific Journal of Cancer Biology, 2024)
Background: The main objective of this paper is to predict the role of covariables in determining the number of nodes to be dissected in endometrial cancer, using the best regression model. Additionally, the study aims to compare the accuracy of the CART model with the traditional regression model, to accurately find and predict the co-variable in determining the number of nodes to be dissected. Material and Methods: Data on 170 endometrial cancer patients, along with their covariates, were collected from the institute AHGPIC and used for the study. The data includes the dependent variable (total number of lymph nodes involved) and 10 co-variates (independent variables): age, postmenopausal bleeding, obstetrics history, nodal status, tumor size, histology, grade, myometrial invasion, lymphovascular space invasion, and cervical extension. The methods used include multiple regression and the CART model. Results: The average number of lymph nodes dissected among patients with a tumor size less than 1.9 cm is 3.73 (approximately 4), while patients with a tumor size of 1.9 cm have an average of 12.4 nodes (approximately 13) dissected. Among patients with prior b/l pelvic lymphadenectomy, the average number of nodes dissected is 10.9 (approximately 11), while those with prior b/l para-aortic + b/l pelvic lymphadenectomy have an average of 14.1 nodes (approximately 14) dissected. The CART model predicts with an accuracy of 95.9%, which is higher than the multiple regression model’s accuracy of 88.3%, based on the selected covariates and validated by the receiver operating characteristics (ROC) curve. Conclusion: The study concludes that if the tumor size is greater than 1.9 cm (approximately > 2 cm), then 12 nodes should be dissected, and if it is less than 1.9 cm (approximately < 2 cm), then approximately 4 nodes should be dissected. The classification and regression tree (CART) model is able to predict the role of the covariate, i.e., tumor size, in deciding the number of lymph nodes to be dissected for endometrial cancer patients with an accuracy of 95.9%, based on the selected covariates and validated by the ROC curve. The CART model predicts with more accuracy (95.9%) compared to the multiple regression model (88.3%).