A predictive nomogram improved diagnostic accuracy and interobserver agreement of perirectal lymph nodes metastases in rectal cancer.

Objective: To develop a predictive nomogram to improve the diagnostic accuracy and interobserver agreement of pre-therapeutic lymph nodes metastases in patients with rectal cancer.

Materials And Methods: An institutional database of 411 patients with rectal cancer was used to develop a nomogram to predict perirectal lymph nodes metastases. Patients' clinicopathological and MRI-assessed imaging variables were included in the multivariate logistic regression analysis. The model was externally validated and the performance was assessed by area under curve (AUC) of the receiver operator characteristics (ROC) curves. The interobserver agreement was measured between two independent radiologists.

Results: The diagnostic accuracy of the conventional MRI-assessed cN stage was 68%; 14.2% of the patients were over-staged and 17.8% of the patients were under-staged. A total of 35.1% of the patients had disagreed diagnosis for the cN stage between the two radiologists, with a kappa value of 0.295. A nomogram for predicting pathological lymph nodes metastases was successfully developed, with an AUC of 0.78 on the training data and 0.71 on the validation data. The predictors included in the nomogram were MRI cT stage, CRM involvement, preoperative CEA, tumor grade and lymph node size category. This nomogram yielded improved prediction in cN stage than the conventional MRI-based assessment.

Conclusions: By incorporating clinicopathological and MRI imaging features, we established a nomogram that improved the diagnostic accuracy and remarkably minimized the interobserver disagreement in predicting lymph nodes metastases in rectal cancers.