Evaluation of models to predict lymph node metastasis in endometrial cancer: A multicentre study

Abstract

Background: Several models (preoperative and postoperative) have been developed to predict lymph node metastasis (LNM) in patients with endometrial cancer. The purpose of our investigation was to compare available models in a multicentre study.

Methods: In a cohort of 519 patients with endometrial cancer who had undergone primary hysterectomy and at least a pelvic lymphadenectomy, we compared the areas under the receiver-operating characteristic curves (AUCs), calibrations, rates of false negatives (FN), and the number of patients at low-risk for LNM using ten different models (three preoperative and seven postoperative).

Results: In all, 17.5% of patients among the study population (91 in 519) had LNM. Only one of the three preoperative models and three of the seven postoperative models had an AUC >0.75. Six models were well calibrated. Eight models yielded an FN rate of <5%. Six models could assign more than a third of patients to the low-risk group. One postoperative (a French nomogram) and one preoperative (the Korean Gynecologic Oncology Group [KGOG]) model had an AUC >0.75, to yield an FN rate of <5%, and could assign more than a third of patients to the low-risk group.

Conclusions: This study supports the use of the KGOG model to decide upon lymphadenectomy preoperatively in patients with endometrial cancer. For patients who did not have lymphadenectomy, a French nomogram could be applied using pathological characteristics to decide on a secondary lymphadenectomy.

Keywords: Endometrial cancer; Lymph node metastasis; Lymphadenectomy; Prediction.