BACKGROUND: This study was designed to develop a @entity262 ( @entity262 ) for predicting @entity1600 ( @entity1600 ) @entity3 in @entity1 with early-stage @entity1204 ( @entity1204 ). METHODS: Data of 457 @entity1 with early-stage @entity1204 who received primary surgical treatment between January 2001 and December 2012 were abstracted from a prospective, multicentre database (training set). A risk model based on factors impacting @entity1600 @entity3 was developed. To assess the discrimination of the @entity262 , both internal by the bootstrap approach and external validation (validation set) were adopted. RESULTS: Overall the @entity1600 @entity3 rate was 11.8  % (54/457). @entity1600 @entity3 were associated with five variables: age >= 60  years, histological grade 3 and/or type 2, primary @entity5 diameter >= 1.5  cm, depth of myometrial invasion >= 50  %, and the positive lymphovascular space involvement status. These variables were included in the @entity262 and assigned scores ranging from 0 to 9. The discrimination of the @entity262 was 0.81 [95  % confidence interval (CI) 0.78-0.84] in the training set. The area under the curve of the receiver-operating characteristics for predicting @entity1600 @entity3 after internal and external validation was 0.80 (95  % CI 0.77-0.83) and 0.85 (95  % CI 0.81-0.89), respectively. A total score of 6 points corresponded to the optimal threshold of the @entity262 with a rate of @entity1600 @entity3 of 7.5  % (29/385) and 34.7  % (25/72) for low-risk ( <=6 points) and high-risk @entity1 (>6 points), respectively. At this threshold, the diagnostic accuracy was 83  %. CONCLUSIONS: This @entity262 could be useful in clinical practice to determine which @entity1 with early-stage @entity1204 should benefit from secondary surgical staging including complete lymphadenectomy.

French Multicenter Study Evaluating the Risk of Lymph Node XXXX in Early-Stage Endometrial Cancer: Contribution of a Risk Scoring System.

@entity1 :: ('9606', 'Species') :: ['patients'] @entity1204 :: ('MESH:D016889', 'Disease') :: ['endometrial cancer', 'EC'] @entity5 :: ('MESH:D009369', 'Disease') :: ['tumor'] @entity1600 :: ('MESH:D014388', 'Disease') :: ['LN', 'lymph node'] @entity262 :: ('MESH:D034721', 'Disease') :: ['risk scoring system', 'RSS'] @entity3 :: ('MESH:D009362', 'Disease') :: ['metastasis', 'metastases']
@entity3 :: (MESH:D009362,Disease) :: ['Metastases']
