Feilin Qu1,2, Xiaosong Chen1, Xiaochun Fei3, Lin Lin4, Weiqi Gao1, Yu Zong1, Jiayi Wu1, Ou Huang1, Jianrong He1, Li Zhu1, Weiguo Chen1, Yafen Li1, Kunwei Shen1. 1. Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China. 2. Department of General Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China. 3. Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China. 4. Department of Clinical Laboratory, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Abstract
OBJECTIVE: The indication of adjuvant chemotherapy recommendation (ACR) in breast cancer patients with intermediate recurrence score (RS) is controversial. This study investigated the relationship between routine clinicopathological indicators and ACR, and established a nomogram for predicting the probability of ACR in this subset of patients. METHODS: Data for a total of 504 consecutive patients with intermediate RS from January 2014 to December 2016 were retrospectively reviewed. A nomogram was constructed using a multivariate logistic regression model based on data from a training set (378 cases) and validated in an independent validation set (126 cases). A Youden-derived cut-off value was assigned to the nomogram for accuracy evaluation. RESULTS: The multivariate logistic regression analysis identified that age, histological grade, tumor size, lymph node (LN) status, molecular subtype, and RS were independent predictors of ACR. A nomogram based on these predictors performed well. The P value of the Hosmer-Lemeshow test for the prediction model was 0.286. The area under the curve (AUC) values were 0.905 [95% confidence interval (95% CI): 0.876-0.934] and 0.883 (95% CI: 0.824-0.942) in the training and validation sets, respectively. The accuracies of the nomogram for ACR were 84.4% in the training set and 82.1% in the validation set. CONCLUSIONS: We developed a nomogram to predict the probability of ACR in breast cancer patients with intermediate RS. This model may aid the individual risk assessment and guide treatment decisions in clinical practice.
OBJECTIVE: The indication of adjuvant chemotherapy recommendation (ACR) in breast cancer patients with intermediate recurrence score (RS) is controversial. This study investigated the relationship between routine clinicopathological indicators and ACR, and established a nomogram for predicting the probability of ACR in this subset of patients. METHODS: Data for a total of 504 consecutive patients with intermediate RS from January 2014 to December 2016 were retrospectively reviewed. A nomogram was constructed using a multivariate logistic regression model based on data from a training set (378 cases) and validated in an independent validation set (126 cases). A Youden-derived cut-off value was assigned to the nomogram for accuracy evaluation. RESULTS: The multivariate logistic regression analysis identified that age, histological grade, tumor size, lymph node (LN) status, molecular subtype, and RS were independent predictors of ACR. A nomogram based on these predictors performed well. The P value of the Hosmer-Lemeshow test for the prediction model was 0.286. The area under the curve (AUC) values were 0.905 [95% confidence interval (95% CI): 0.876-0.934] and 0.883 (95% CI: 0.824-0.942) in the training and validation sets, respectively. The accuracies of the nomogram for ACR were 84.4% in the training set and 82.1% in the validation set. CONCLUSIONS: We developed a nomogram to predict the probability of ACR in breast cancer patients with intermediate RS. This model may aid the individual risk assessment and guide treatment decisions in clinical practice.
Authors: A S Coates; E P Winer; A Goldhirsch; R D Gelber; M Gnant; M Piccart-Gebhart; B Thürlimann; H-J Senn Journal: Ann Oncol Date: 2015-05-04 Impact factor: 32.976
Authors: Scott D Ramsey; William E Barlow; Ana M Gonzalez-Angulo; Sean Tunis; Laurence Baker; John Crowley; Patricia Deverka; David Veenstra; Gabriel N Hortobagyi Journal: Contemp Clin Trials Date: 2012-09-18 Impact factor: 2.226
Authors: Mitch Dowsett; Jack Cuzick; Christopher Wale; John Forbes; Elizabeth A Mallon; Janine Salter; Emma Quinn; Anita Dunbier; Michael Baum; Aman Buzdar; Anthony Howell; Roberto Bugarini; Frederick L Baehner; Steven Shak Journal: J Clin Oncol Date: 2010-03-08 Impact factor: 44.544
Authors: A Goldhirsch; E P Winer; A S Coates; R D Gelber; M Piccart-Gebhart; B Thürlimann; H-J Senn Journal: Ann Oncol Date: 2013-08-04 Impact factor: 32.976