The preoperative prediction of lateral pelvic lymph node (LPLN) metastasis is crucial in determining further treatment strategies for advanced lower rectal cancer patients. In this study, we established a nomogram model to preoperatively predict LPLN metastasis and then externally validated the accuracy of this model.
A total of 287 rectal cancer patients who underwent LPLN dissection were included in this study. Among them, 200 patients from the Peking University First Hospital were included in the development set, and 87 patients from the First Affiliated Hospital of Xi’an Jiaotong University were included in the independent external validation set. Multivariate logistic regression analysis was used to develop the nomogram. The performance of the nomogram was assessed based on its calibration, discrimination, and clinical utility.
Five factors (differentiation grade, extramural vascular invasion, distance of the tumor from the anal verge, perirectal lymph node status, and largest short-axis diameter of LPLN) were identified and included in the nomogram. The nomogram developed based on the analysis showed robust discrimination with an area under the receiver operating characteristic curve (AUC) of 0.878 (95% CI, 0.824–0.932). The validation set showed good discrimination with an AUC of 0.863 (95% CI, 0.779–0.948). Decision curve analysis showed that the nomogram was clinically useful.
The present study proposed a clinical-imaging nomogram with a combination of clinicopathological risk factors and imaging features. After external verification, the predictive power of the nomogram model was satisfactory, and it is expected to be a convenient, visual, and personalized clinical tool for assessing the risk of LPLN metastasis in advanced lower rectal cancer patients.