Evaluation of models to predict lymph node metastasis in endometrial cancer: A multicentre study. (July 2016) - Koskas, Martin; Fournier, Marie; Vanderstraeten, Anke; Walker, Francine; Timmerman, Dirk; Vergote, Ignace; Amant, Frédéric
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. Highlights: Models designed to predict lymph node metastasis in endometrial cancer were evaluated. Preoperatively, the Korean Gynecologic Oncology Group model provided the most accurate predictions. Postperatively, the French model provided the most accurate predictions.