Fiche publication
Date publication
janvier 2014
Auteurs
Membres identifiés du Cancéropôle Est :
Pr GRAESSLIN Olivier
Tous les auteurs :
Koskas M, Genin AS, Graesslin O, Barranger E, Haddad B, Darai E, Rouzier R
Lien Pubmed
Résumé
OBJECTIVE: We recently developed an algorithm based on five clinical and pathological characteristics to predict lymph node (LN) metastasis in endometrial cancer. The aim of this study was to evaluate the accuracy of using this algorithm with preoperative characteristics. STUDY DESIGN: In this retrospective multicenter study, we evaluated the accuracy of using an algorithm to predict LN metastasis using preoperative tumor characteristics provided by endometrial sampling pathological characteristics (histological subtype and grade) and by magnetic resonance imaging (MRI) for primary site tumor extension. RESULTS: In total, 181 patients were included in this study, and 14 patients had pelvic LN metastasis (7.7%). Using preoperative tumor characteristics, the algorithm showed good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.83 (95% confidence interval (IC95)=0.79-0.87) and was well calibrated (average error=1.9% and maximal error=8.5%). LN metastasis prediction by the algorithm using preoperative data was as accurate as that obtained using the final tumor characteristics (AUC=0.77 (CI95=0.70-0.83), average error=2.8% and maximal error=23.2%). CONCLUSION: Our algorithm was accurate in predicting pelvic LN metastasis even with the use of preoperative tumor characteristics provided by endometrial sampling and MRI. These findings, however, should be verified in a larger database before our algorithm is implemented for widespread use.
Référence
Eur J Obstet Gynecol Reprod Biol. 2014 Jan;172:115-9
