Yan Wang1,2, Yaping Yang1,2, Zhengbo Chen3, Teng Zhu4, Jiannan Wu1,2, Fengxi Su1,2, Heran Deng1,2. 1. Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China. 2. Department of Breast Surgery, Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China. 3. Department of General Surgery, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China. 4. Department of Breast Cancer, Cancer Center, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China.
Abstract
BACKGROUND: Distant metastasis (DM) from breast cancer has a poor prognosis. Our objective was to develop and validate a nomogram to predict individual distant metastasis-free survival (DMFS) and risk stratification in non-metastatic breast cancer patients. METHODS: A nomogram was based on an analysis of 1,201 breast cancer patients treated at Sun Yat-sen Memorial Hospital from 2001 to 2014. Using univariate and multivariate analyses to identify the predictors, this model was externally validated in an independent cohort of 538 patients from the Guangdong General Hospital between 2004 and 2012. The predictive discrimination and calibration ability of this nomogram were assessed using concordance index (C-index), risk group stratification, and calibration curve. RESULTS: The 5-year DMFS in the training and validation cohorts were 95.74% and 91.02%, respectively. On multivariable analysis of training cohort, the prognostic factors in the nomogram comprised age, tumor size, lymph node status, molecular subtype, and lymphovascular invasion (LVI). The C-index of our model was 0.75 [95% confidence interval (CI): 0.67-0.83] for the training cohort and 0.71 (95% CI: 0.64-0.78) for the validation cohort. The calibration curves for 5-year DMFS showed good agreement between the model prediction and actual observation. Based on the risk stratification, Kaplan-Meier curves indicated that the low-risk group had significantly better prognosis than the high-risk group (P<0.001). CONCLUSIONS: Our nomogram can provide an individual prediction of 5-year DMFS in non-metastatic breast cancer patients. This prognostic tool may help clinicians to make appropriate treatment regimens and optimal surveillance plans. 2019 Annals of Translational Medicine. All rights reserved.
BACKGROUND: Distant metastasis (DM) from breast cancer has a poor prognosis. Our objective was to develop and validate a nomogram to predict individual distant metastasis-free survival (DMFS) and risk stratification in non-metastatic breast cancer patients. METHODS: A nomogram was based on an analysis of 1,201 breast cancer patients treated at Sun Yat-sen Memorial Hospital from 2001 to 2014. Using univariate and multivariate analyses to identify the predictors, this model was externally validated in an independent cohort of 538 patients from the Guangdong General Hospital between 2004 and 2012. The predictive discrimination and calibration ability of this nomogram were assessed using concordance index (C-index), risk group stratification, and calibration curve. RESULTS: The 5-year DMFS in the training and validation cohorts were 95.74% and 91.02%, respectively. On multivariable analysis of training cohort, the prognostic factors in the nomogram comprised age, tumor size, lymph node status, molecular subtype, and lymphovascular invasion (LVI). The C-index of our model was 0.75 [95% confidence interval (CI): 0.67-0.83] for the training cohort and 0.71 (95% CI: 0.64-0.78) for the validation cohort. The calibration curves for 5-year DMFS showed good agreement between the model prediction and actual observation. Based on the risk stratification, Kaplan-Meier curves indicated that the low-risk group had significantly better prognosis than the high-risk group (P<0.001). CONCLUSIONS: Our nomogram can provide an individual prediction of 5-year DMFS in non-metastatic breast cancer patients. This prognostic tool may help clinicians to make appropriate treatment regimens and optimal surveillance plans. 2019 Annals of Translational Medicine. All rights reserved.
Entities:
Keywords:
Breast cancer; distant metastasis-free survival (DMFS); nomogram
Authors: F Cardoso; A Costa; L Norton; D Cameron; T Cufer; L Fallowfield; P Francis; J Gligorov; S Kyriakides; N Lin; O Pagani; E Senkus; C Thomssen; M Aapro; J Bergh; A Di Leo; N El Saghir; P A Ganz; K Gelmon; A Goldhirsch; N Harbeck; N Houssami; C Hudis; B Kaufman; M Leadbeater; M Mayer; A Rodger; H Rugo; V Sacchini; G Sledge; L van't Veer; G Viale; I Krop; E Winer Journal: Breast Date: 2012-03-16 Impact factor: 4.380
Authors: Brenda Deyarmin; Jennifer L Kane; Allyson L Valente; Ryan van Laar; Christopher Gallagher; Craig D Shriver; Rachel E Ellsworth Journal: Ann Surg Oncol Date: 2012-08-09 Impact factor: 5.344
Authors: M Barral; A Auperin; A Hakime; V Cartier; V Tacher; Yves Otmezguine; L Tselikas; T de Baere; F Deschamps Journal: Cardiovasc Intervent Radiol Date: 2016-02-09 Impact factor: 2.740
Authors: A M Minisini; S Moroso; L Gerratana; M Giangreco; D Iacono; E Poletto; M Guardascione; C Fontanella; G Fasola; F Puglisi Journal: Clin Exp Metastasis Date: 2013-06-18 Impact factor: 5.150
Authors: Anna L V Johansson; Cassia B Trewin; Kirsti Vik Hjerkind; Merete Ellingjord-Dale; Tom Børge Johannesen; Giske Ursin Journal: Int J Cancer Date: 2018-12-03 Impact factor: 7.396
Authors: C Dilara Savci-Heijink; Hans Halfwerk; Gerrit K J Hooijer; Hugo M Horlings; Jelle Wesseling; Marc J van de Vijver Journal: Breast Cancer Res Treat Date: 2015-03-29 Impact factor: 4.872
Authors: Michael J Duffy; Patricia M McGowan; Nadia Harbeck; Christoph Thomssen; Manfred Schmitt Journal: Breast Cancer Res Date: 2014-08-22 Impact factor: 6.466
Authors: Yann Delpech; Sami I Bashour; Ruben Lousquy; Roman Rouzier; Kenneth Hess; Charles Coutant; Emmanuel Barranger; Francisco J Esteva; Noato T Ueno; Lajos Pusztai; Nuhad K Ibrahim Journal: Br J Cancer Date: 2015-09-22 Impact factor: 7.640
Authors: Therese Sorlie; Robert Tibshirani; Joel Parker; Trevor Hastie; J S Marron; Andrew Nobel; Shibing Deng; Hilde Johnsen; Robert Pesich; Stephanie Geisler; Janos Demeter; Charles M Perou; Per E Lønning; Patrick O Brown; Anne-Lise Børresen-Dale; David Botstein Journal: Proc Natl Acad Sci U S A Date: 2003-06-26 Impact factor: 12.779