Approach of five-year-average hazard rates for the breast cancer patients and analyses of prognostic factors—an application of cox regression model

1998 ◽  
Vol 10 (2) ◽  
pp. 134-137
Author(s):  
Xueliang Gai ◽  
Zhimin Fan ◽  
Guojin Liu ◽  
Jacques Brisson
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Regression Model ◽  
Cancer Patients ◽  
Cox Regression ◽  
Hazard Rates ◽  
Breast Cancer Patients ◽  
Cox Regression Model

Factors associated with mortality after breast cancer metastasis.

2011 ◽  
Vol 29 (27_suppl) ◽  
pp. 174-174
Author(s):  
S. Y. Jung ◽  
M. Q. Rosenzweig ◽  
S. M. Sereika ◽  
F. Linkov ◽  
A. Brufsky ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Metastatic Breast Cancer ◽  
Cancer Patients ◽  
Cancer Metastasis ◽  
Cox Regression ◽  
Metastatic Breast ◽  
Breast Cancer Metastasis ◽  
Her2 Status ◽  
Breast Cancer Patients

174 Background: It is generally accepted that patients with breast cancer metastases have poor survival. Metastatic breast cancer patients can be considered a heterogeneous population with a varied clinical course, which underscores the need for accurate prediction of survival based on prognostic factors. The purpose of the present study was to identify factors related to survival in breast cancer patients after diagnosis with metastatic disease. Methods: A total of 557 patients with breast cancer metastasis diagnosis seen at one large urban practice have been followed up between January 1, 1999 and June 30, 2008. Demographic, tumor characteristics, clinical factors as predictors of survival were analyzed using Cox regression model. Results: The median survival length was 40 months (range 1-114 months) with 269 (48.3%) alive and 288 (51.7%) dead. This study demonstrated that hypertension, estrogen receptor (ER) and/or progesterone receptor (PR) status, human epidermal growth factor receptor-2 (HER2) status, number of metastatic sites, and body mass index (BMI) at diagnosis with metastatic breast cancer were the most relevant prognostic factors for survival after metastasis. Conclusions: Findings of this study may form a foundation for the corpus of knowledge explaining the outcome differences in treatment of patients with metastatic breast cancer, potentially helping to create tailored counseling and personalized treatment approaches for this vulnerable group. [Table: see text]

scholarly journals Prognostic factors and survival outcomes according to tumor subtype in patients with breast cancer lung metastases

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8298
Author(s):  
Siying Chen ◽  
Jin Yang ◽  
Yang Liu ◽  
Haisheng You ◽  
Yalin Dong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Metastatic Breast Cancer ◽  
Cancer Patients ◽  
Triple Negative ◽  
Cox Regression ◽  
Lung Metastases ◽  
Metastatic Breast ◽  
Breast Cancer Patients ◽  
Metastatic Sites

Background Reports on the incidence and prognoses of lung metastases when diagnosing breast cancer patients with different subtypes are limited. Our study investigated the effect of molecular sub-typing stratification on the prognoses of lung metastatic breast caner patients. Methods Patients with breast cancer and lung metastases were identified from Surveillance, Epidemiology and End Results population-based data between 2010 and 2015. Univariate and multivariate Cox regression analyses were performed to identify risk factors and prognoses, overall survival (OS) and breast cancer-specific survival for patients with breast cancer lung metastases. Results We identified 6,516 patients with lung metastatic breast cancer, representing 1.7% of the entire cohort and 30.4% of the subset with metastatic disease. This included 2,940 hormone receptor (HR)+/HER2− patients, 852 HR+/HER2+ patients, 547 HR−/HER2+ patients and 983 triple-negative patients. The median OS for all lung metastatic patients was 13 months. Multivariate analysis revealed that those lung metastatic breast cancer patients of older age (>80), black race, with poorly differentiated tumors, carcinoma histology, triple-negative subtype, more metastatic sites and no surgery, and no chemotherapy showed significantly poor survival, both overall and breast cancer-specific. Conclusions Our findings show that molecular sub-type and more metastatic sites might have significant influence on the incidence and prognosis of breast cancer lung metastases. We also identified several prognostic factors that could guide therapy selection in the treatment of lung metastatic patients.

scholarly journals A Nomogram Predicting Survival in Patients with Breast Ductal Carcinoma in Situ with Microinvasion

2021 ◽  
Author(s):  
Yi-Zi Zheng ◽  
Hong-Bin Qin ◽  
Zi-Zheng Li ◽  
He-Sheng Jiang ◽  
Greg Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Regression Model ◽  
Cancer Patients ◽  
Ductal Carcinoma In Situ ◽  
Carcinoma In Situ ◽  
Ductal Carcinoma ◽  
Multivariate Logistic Regression Model ◽  
Breast Cancer Patients

Abstract Background: Ductal carcinoma in situ with microinvasion (DCISM) can be challenging to balance the risks of overtreatment versus undertreatment. We aim to identify prognostic factors in patients with DCISM and construct a nomogram to predict breast cancer-specific survival (BCSS).Methods: Women diagnosed with DCISM were selected from the Surveillance, Epidemiology and End Results database (1998-2015). Clinical variables and tumor characteristics were evaluated and Cox proportional-hazards regression model was performed. A nomogram was con­structed from the multivariate logistic regression model to combine all the prognostic factors to predict the prognosis of DCISM patients at 5 years, 10 years, and 15 years. Results: We identified 5,438 total eligible breast cancer patients with a median and max survival time of 78 and 227 months, respectively. Here, patients with poorer survival outcomes were those diagnosed between 1988-2001, African-American race, under 40 years of age, higher tumor N stage, progesterone receptor-negative tumor, and received no surgery (all P < 0.05). The nomogram was constructed by the seven variables and passed the calibration and validation steps. The area under the receiver operating characteristic (ROC) curve (AUC) of both the training set and the validating set (5-year AUC: 0.77 and 0.88, 10-year AUC: 0.75 and 0.73, 15-year AUC: 0.72 and 0.65) demonstrated excellent reliability and robust performance.Conclusion: Our current study is the first to construct nomograms of patients with DCISM which could help physicians identify breast cancer patients that more likely to benefit from more intensive treatment and follow-up.

scholarly journals Prognostic factors and survival according to tumour subtype in women presenting with breast cancer bone metastases at initial diagnosis: a SEER-based study

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Xiao Li ◽  
Xiaoli Zhang ◽  
Jie Liu ◽  
Yinzhong Shen
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Bone Metastases ◽  
Cancer Patients ◽  
Cox Regression ◽  
Stage Iv ◽  
Significant Prognostic Factor ◽  
Breast Cancer Patients ◽  
Cox Regression Analysis ◽  
Stage Iv Breast Cancer

Abstract Background Tumour subtype has a significant effect on bone metastasis in breast cancer, but population-based estimates of the prognosis of patients with bone metastases at breast cancer diagnosis are lacking. The aim of this study was to analyse the influence of tumour subtype and other factors on the prognosis and survival of patients with bone metastases of breast cancer. Methods Using the Surveillance, Epidemiology, and End Results (SEER) Program data from 2012 to 2016, a retrospective cohort study was conducted to investigate stage IV breast cancer patients with bone metastases. Stage IV patient characteristics according to subtype were compared using chi-square tests. Overall survival (OS) and prognostic factors were compared using the Kaplan-Meier method and the Cox proportional hazards model, respectively. Results A total of 3384 stage IV patients were included in this study; 63.42% were HR+/HER2-, 19.86% were HR+/HER2+, 9.34% were HR−/HER2-, and 7.39% were HR−/HER2+. The median OS for the whole population was 38 months, and 33.9% of the patients were alive at 5 years. The median OS and five-year survival rate were significantly different among stage IV breast cancer patients with different molecular subtypes (p < 0.05). Multivariate Cox regression analysis showed that age of 55–59 (HR = 1.270), black race (HR = 1.317), grade III or IV (HR = 1.960), HR−/HER2- (HR = 2.808), lung metastases (HR = 1.378), liver metastases (HR = 2.085), and brain metastases (HR = 1.903) were independent risk factors for prognosis; married status (HR = 0.819), HR+/HER2+ (HR = 0.631), HR−/HER2+ (HR = 0.716), insurance (HR = 0.587) and surgery (HR = 0.504) were independent protection factors of prognosis. There was an interaction between the HR+/HER2+ subtype and other metastases (except bone metastases, HR = 0.694, 95% CI: 0.485–0.992), but the interaction between race and subtype did not reach significance for prognosis. Conclusions There were substantial differences in OS according to tumour subtype. In addition to tumour subtype, other independent predictors of OS were age at diagnosis, race, marital status, insurance, grade, surgery and visceral metastases. There was an interaction between the HR+/HER2+ subtype and other metastases (except bone metastases) for prognosis. Tumour subtype, as a significant prognostic factor, warrants further investigation.

scholarly journals Prognostic factors and survival according to tumour subtype in women presenting with breast cancer bone metastases at initial diagnosis: a SEER-based study

2020 ◽  
Author(s):  
Xiao Li ◽  
XiaoLi Zhang ◽  
Jie Liu ◽  
Shen Yin Zhong
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Bone Metastases ◽  
Cancer Patients ◽  
Cox Regression ◽  
Stage Iv ◽  
Significant Prognostic Factor ◽  
Breast Cancer Patients ◽  
Cox Regression Analysis ◽  
Stage Iv Breast Cancer

Abstract Background: Tumour subtype has a significant effect on bone metastasis in breast cancer, but population-based estimates of the prognosis of patients with bone metastases at breast cancer diagnosis are lacking. The aim of this study was to analyse the influence of tumour subtype and other factors on the prognosis and survival of patients with bone metastases of breast cancer.Methods: Using the Surveillance, Epidemiology, and End Results (SEER) Program data from 2012 to 2016, a retrospective cohort study was conducted to investigate stage IV breast cancer patients with bone metastases. Stage IV patient characteristics according to subtype were compared using chi-square tests. Overall survival (OS) and prognostic factors were compared using the Kaplan-Meier method and the Cox proportional hazards model, respectively.Results: A total of 3384 stage IV patients were included in this study; 63.42% were HR+/HER2-, 19.86% were HR+/HER2+, 9.34% were HR-/HER2-, and 7.39% were HR-/HER2+. The median OS for the whole population was 38 months, and 33.9% of the patients were alive at five years. The median OS and five-year survival rate were significantly different among stage IV breast cancer patients with different molecular subtypes (p<0.05). Multivariate Cox regression analysis showed that age of 55-59 (HR=1.270), black race (HR=1.317), grade III or IV (HR=1.960), HR-/HER2- (HR=2.808), lung metastases (HR=1.378), liver metastases (HR=2.085), and brain metastases (HR=1.903) were independent risk factors for prognosis; married status (HR=0.819), HR+/HER2+ (HR=0.631), HR-/HER2+ (HR=0.716), insurance (HR=0.587) and surgery (HR=0.504) were independent protection factors of prognosis. There was an interaction between the HR+/HER2+ subtype and other metastases (except bone metastases, HR=0.694, 95% CI: 0.485-0.992), but the interaction between race and subtype did not reach significance for prognosis.Conclusions: There were substantial differences in OS according to tumour subtype. In addition to tumour subtype, other independent predictors of OS were age at diagnosis, race, marital status, insurance, grade, surgery and visceral metastases. There was an interaction between the HR+/HER2+ subtype and other metastases (except bone metastases) for prognosis. Tumour subtype, as a significant prognostic factor, warrants further investigation.

scholarly journals Surgery for primary tumor benefits survival for breast cancer patients with bone metastases: a large cohort retrospective study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhangheng Huang ◽  
Xin Zhou ◽  
Yuexin Tong ◽  
Lujian Zhu ◽  
Ruhan Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Bone Metastases ◽  
Cancer Patients ◽  
Primary Tumor ◽  
Predictive Accuracy ◽  
Rank Test ◽  
Breast Cancer Patients ◽  
Risk Of Death ◽  
The Impact

Abstract Background The role of surgery for the primary tumor in breast cancer patients with bone metastases (BM) remains unclear. The purpose of this study was to determine the impact of surgery for the primary tumor in breast cancer patients with BM and to develop prognostic nomograms to predict the overall survival (OS) of breast cancer patients with BM. Methods A total of 3956 breast cancer patients with BM from the Surveillance, Epidemiology, and End Results database between 2010 and 2016 were included. Propensity score matching (PSM) was used to eliminate the bias between the surgery and non-surgery groups. The Kaplan-Meier analysis and the log-rank test were performed to compare the OS between two groups. Cox proportional risk regression models were used to identify independent prognostic factors. Two nomograms were constructed for predicting the OS of patients in the surgery and non-surgery groups, respectively. In addition, calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to evaluate the performance of nomograms. Result The survival analysis showed that the surgery of the primary tumor significantly improved the OS for breast cancer patients with BM. Based on independent prognostic factors, separate nomograms were constructed for the surgery and non-surgery groups. The calibration and ROC curves of these nomograms indicated that both two models have high predictive accuracy, with the area under the curve values ≥0.700 on both the training and validation cohorts. Moreover, DCA showed that nomograms have strong clinical utility. Based on the results of the X-tile analysis, all patients were classified in the low-risk-of-death subgroup had a better prognosis. Conclusion The surgery of the primary tumor may provide survival benefits for breast cancer patients with BM. Furthermore, these prognostic nomograms we constructed may be used as a tool to accurately assess the long-term prognosis of patients and help clinicians to develop individualized treatment strategies.

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