Xingxi Pan1, Wen Yang2, Yongfa Chen3, Lihua Tong4, Churong Li5, Hui Li6. 1. Department of Oncology, Nanhai Hospital Affiliated to Southern Medical University, Foshan, Guangdong, 528200, PR China. Electronic address: pxx6797@163.com. 2. Department of Oncology, Nanhai Hospital Affiliated to Southern Medical University, Foshan, Guangdong, 528200, PR China. Electronic address: fsnhyangwen@126.com. 3. Department of Oncology, Nanhai Hospital Affiliated to Southern Medical University, Foshan, Guangdong, 528200, PR China. Electronic address: 63486410@qq.com. 4. Department of Oncology, Nanhai Hospital Affiliated to Southern Medical University, Foshan, Guangdong, 528200, PR China. Electronic address: xiaotong45@yeah.net. 5. Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610041, PR China. Electronic address: mylcr2009@163.com. 6. Department of General Surgery, Chengdu Second People's Hospital, Chengdu, Sichuan, 610017, PR China. Electronic address: lichanghehui@gmail.com.
Abstract
OBJECTIVES: Inflammatory breast cancer (IBC) is a rare malignancy that is a unique biologic subtype of breast cancer. A nomogram to predict the overall survival (OS) of IBC patients is lacking. The aim of the study was to construct and validate a nomogram to predict the OS of IBC patients based on the Surveillance, Epidemiology, and End Results (SEER) Program. METHODS: Patients diagnosed with IBC between 2010 and 2016 were selected from the SEER database. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. A nomogram was constructed to predict the 1-, 3- and 5-year OS of these patients. The nomogram was internally and externally validated by Harrell's C-indexes and calibration plots. RESULTS: Patients were randomly divided into a training set (n = 2464) and a validation set (n = 1052). The training set was used to establish a nomogram. Multivariate analysis identified that race, age at diagnosis, breast cancer subtype, grade, N stage, M stage, radiation, chemotherapy, and surgery were significant prognostic factors for the OS. The internally and externally validated Harrell's C-indexes were 0.763 and 0.786, respectively. The calibration plots for predictions of the 1-, 3-, and 5-year OS were in excellent agreement. CONCLUSIONS: A nomogram was constructed to predict the OS for IBC patients based on the SEER database and to provide accurate and individualised survival predictions.
OBJECTIVES:Inflammatory breast cancer (IBC) is a rare malignancy that is a unique biologic subtype of breast cancer. A nomogram to predict the overall survival (OS) of IBCpatients is lacking. The aim of the study was to construct and validate a nomogram to predict the OS of IBCpatients based on the Surveillance, Epidemiology, and End Results (SEER) Program. METHODS:Patients diagnosed with IBC between 2010 and 2016 were selected from the SEER database. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. A nomogram was constructed to predict the 1-, 3- and 5-year OS of these patients. The nomogram was internally and externally validated by Harrell's C-indexes and calibration plots. RESULTS:Patients were randomly divided into a training set (n = 2464) and a validation set (n = 1052). The training set was used to establish a nomogram. Multivariate analysis identified that race, age at diagnosis, breast cancer subtype, grade, N stage, M stage, radiation, chemotherapy, and surgery were significant prognostic factors for the OS. The internally and externally validated Harrell's C-indexes were 0.763 and 0.786, respectively. The calibration plots for predictions of the 1-, 3-, and 5-year OS were in excellent agreement. CONCLUSIONS: A nomogram was constructed to predict the OS for IBCpatients based on the SEER database and to provide accurate and individualised survival predictions.
Authors: Theresa Relation; Yaming Li; James L Fisher; Allan Tsung; Bridget Oppong; Mariam F Eskander; Samilia Obeng-Gyasi Journal: Surgery Date: 2021-11-30 Impact factor: 3.982
Authors: J C Chen; Yaming Li; James L Fisher; Oindrila Bhattacharyya; Allan Tsung; Jose G Bazan; Samilia Obeng-Gyasi Journal: Ann Surg Oncol Date: 2022-06-08 Impact factor: 4.339