BACKGROUND: The current International Federation of Gynecology and Obstetrics (FIGO) grade in endometrial carcinomas requires the evaluation of histologic features with proven prognostic value but with questionable reproducibility. This study tests the prognostic power and reproducibility of a new binary grading system. STUDY DESIGN: Specimens from 254 hysterectomies were graded according to the new 3- and 2-tiered FIGO grading systems described by Alkushi et al. The selected morphologic parameters for the new grading system included the presence of predominant solid or papillary architecture pattern, severe nuclear atypia, tumor necrosis, and vascular invasion. The Cox proportional hazards and κ statistics were used for comparisons. RESULTS: On multivariate analysis, and looking at all tumor cell types, the 4 tested grading systems were independent predictors of survival, with the 3-tiered FIGO grading system being the most predictive (P = 0.005). In the subset of endometrioid tumors, the 3- and 2-tiered FIGO grading systems and the new grading system retained their statistical significance as predictors of survival (P = 0.004, P = 0.03, and P = 0.007, respectively), whereas the grading system of Alkushi et al did not (P = 0.1). In nonendometrioid tumors, the new grading system proved to be the best predictor of survival, reaching near statistical significance (P = 0.06). The new grading system had acceptable intraobserver and interobserver reproducibility assessment (κ = 0.87 and κ = 0.45, respectively). CONCLUSION: The 3-tiered FIGO grading system retained its superior prognostic power. However, available binary grading systems remain an attractive option by being highly reproducible and by eliminating the clinical ambiguity of intermediate grades of disease.
BACKGROUND: The current International Federation of Gynecology and Obstetrics (FIGO) grade in endometrial carcinomas requires the evaluation of histologic features with proven prognostic value but with questionable reproducibility. This study tests the prognostic power and reproducibility of a new binary grading system. STUDY DESIGN: Specimens from 254 hysterectomies were graded according to the new 3- and 2-tiered FIGO grading systems described by Alkushi et al. The selected morphologic parameters for the new grading system included the presence of predominant solid or papillary architecture pattern, severe nuclear atypia, tumor necrosis, and vascular invasion. The Cox proportional hazards and κ statistics were used for comparisons. RESULTS: On multivariate analysis, and looking at all tumor cell types, the 4 tested grading systems were independent predictors of survival, with the 3-tiered FIGO grading system being the most predictive (P = 0.005). In the subset of endometrioid tumors, the 3- and 2-tiered FIGO grading systems and the new grading system retained their statistical significance as predictors of survival (P = 0.004, P = 0.03, and P = 0.007, respectively), whereas the grading system of Alkushi et al did not (P = 0.1). In nonendometrioid tumors, the new grading system proved to be the best predictor of survival, reaching near statistical significance (P = 0.06). The new grading system had acceptable intraobserver and interobserver reproducibility assessment (κ = 0.87 and κ = 0.45, respectively). CONCLUSION: The 3-tiered FIGO grading system retained its superior prognostic power. However, available binary grading systems remain an attractive option by being highly reproducible and by eliminating the clinical ambiguity of intermediate grades of disease.
Authors: Marie Boennelycke; Elke E M Peters; Alicia Léon-Castillo; Vincent T H B M Smit; Tjalling Bosse; Ib Jarle Christensen; Gitte Ørtoft; Claus Høgdall; Estrid Høgdall Journal: Virchows Arch Date: 2021-06-11 Impact factor: 4.064
Authors: Aline Talhouk; Lien N Hoang; Melissa K McConechy; Quentin Nakonechny; Joyce Leo; Angela Cheng; Samuel Leung; Winnie Yang; Amy Lum; Martin Köbel; Cheng-Han Lee; Robert A Soslow; David G Huntsman; C Blake Gilks; Jessica N McAlpine Journal: Gynecol Oncol Date: 2016-07-14 Impact factor: 5.482
Authors: A Talhouk; M K McConechy; S Leung; H H Li-Chang; J S Kwon; N Melnyk; W Yang; J Senz; N Boyd; A N Karnezis; D G Huntsman; C B Gilks; J N McAlpine Journal: Br J Cancer Date: 2015-06-30 Impact factor: 7.640
Authors: Elke E M Peters; Carla Bartosch; W Glenn McCluggage; Catherine Genestie; Sigurd F Lax; Remi Nout; Jan Oosting; Naveena Singh; Huub C S H Smit; Vincent T H B M Smit; Koen K Van de Vijver; Tjalling Bosse Journal: Histopathology Date: 2019-06-10 Impact factor: 5.087