PURPOSE: Several factors have been shown to correlate with prognosis of patients with breast carcinoma. Among the most useful are node involvement, tumor size, and pathologic grade. These factors retained their prognostic value when assessed after neoadjuvant chemotherapy. METHODS: Previously we used a revised Nottingham prognostic index and defined 3 related indices (breast grading index, modified Nottingham prognostic index, and modified breast grading index) that were also significantly related to overall survival and disease-free survival. To assess the postchemotherapy risk globally, we have combined the 3 pathologic factors to design a specific classification to evaluate residual disease. This new classification includes 4 risk levels (levels 1-4) according to residual disease magnitude after neoadjuvant chemotherapy in 710 patients with operable breast cancer. RESULTS: This classification resulted in significantly different results for overall survival (P < 10(-7)) and disease-free survival (P = 8.3 x 10(-7)). CONCLUSION: This classification should help us in the selection of subgroups of patients for further adjuvant treatment.
PURPOSE: Several factors have been shown to correlate with prognosis of patients with breast carcinoma. Among the most useful are node involvement, tumor size, and pathologic grade. These factors retained their prognostic value when assessed after neoadjuvant chemotherapy. METHODS: Previously we used a revised Nottingham prognostic index and defined 3 related indices (breast grading index, modified Nottingham prognostic index, and modified breast grading index) that were also significantly related to overall survival and disease-free survival. To assess the postchemotherapy risk globally, we have combined the 3 pathologic factors to design a specific classification to evaluate residual disease. This new classification includes 4 risk levels (levels 1-4) according to residual disease magnitude after neoadjuvant chemotherapy in 710 patients with operable breast cancer. RESULTS: This classification resulted in significantly different results for overall survival (P < 10(-7)) and disease-free survival (P = 8.3 x 10(-7)). CONCLUSION: This classification should help us in the selection of subgroups of patients for further adjuvant treatment.
Authors: Daniel J Farrugia; Alessandra Landmann; Li Zhu; Emilia J Diego; Ronald R Johnson; Marguerite Bonaventura; Atilla Soran; David J Dabbs; Beth Z Clark; Shannon L Puhalla; Rachel C Jankowitz; Adam M Brufsky; Barry C Lembersky; Gretchen M Ahrendt; Priscilla F McAuliffe; Rohit Bhargava Journal: Mod Pathol Date: 2017-05-26 Impact factor: 7.842
Authors: Elena Provenzano; Veerle Bossuyt; Giuseppe Viale; David Cameron; Sunil Badve; Carsten Denkert; Gaëtan MacGrogan; Frédérique Penault-Llorca; Judy Boughey; Giuseppe Curigliano; J Michael Dixon; Laura Esserman; Gerd Fastner; Thorsten Kuehn; Florentia Peintinger; Gunter von Minckwitz; Julia White; Wei Yang; W Fraser Symmans Journal: Mod Pathol Date: 2015-07-24 Impact factor: 7.842
Authors: Shudong Jiang; Brian W Pogue; Colin M Carpenter; Steven P Poplack; Wendy A Wells; Christine A Kogel; Jorge A Forero; Lori S Muffly; Gary N Schwartz; Keith D Paulsen; Peter A Kaufman Journal: Radiology Date: 2009-06-09 Impact factor: 11.105
Authors: T J Stankowski-Drengler; J R Schumacher; B Hanlon; D Livingston-Rosanoff; K Van de Walle; C C Greenberg; L G Wilke; H B Neuman Journal: Ann Surg Oncol Date: 2020-01-03 Impact factor: 5.344
Authors: Hee Jin Lee; In Ah Park; In Hye Song; Sung-Bae Kim; Kyung Hae Jung; Jin-Hee Ahn; Sei-Hyun Ahn; Hak Hee Kim; Gyungyub Gong Journal: PLoS One Date: 2015-09-22 Impact factor: 3.240