Abstract
BackgroundWe aimed this investigation to screen and analyze the risk factors of postoperative lymphatic leakage of gynecological malignant tumors that contribute to the treatment of the diseases.Material/MethodsAccording to the occurrence of lymphatic leakage after an operation, 655 patients with pelvic lymph node and/or abdominal para-aortic lymph node dissection for gynecological malignant tumor were retrospectively analyzed and divided into a case group and a control group. Univariate and multivariate logistic regression analysis were used to screen the effective independent risk factors and establish a clinical prediction model. The differentiation and calibration of the clinical prediction model were evaluated, and we performed internal and external validation of the model with 207 cases.ResultsThe surgeons, the number of removed lymph nodes, the field and range of lymph nodes to be removed, the method of drainage, and postoperative infection are the independent risk factors of lymphatic leakage after lymph node dissection for gynecological malignant tumors. The area under the ROC curve of the clinical prediction model was 0.839 (P<0.001), the calibration Hosmer-Lemeshow test shows χ2=4.381, P=0.821. Through 10-fold cross-validation, the average correct rate of the prediction model was 0.899, the area under the ROC curve of the external verification group was 0.741, and the calibration Hosmer-Lemeshow test showed χ2=12.728, P=0.122.ConclusionsThe new logistic prediction model showed a good degree of differentiation and calibration in both the modeling and verification groups, and it can be used for early warning of the occurrence of lymphatic leakage after lymph node dissection.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.