Risk factors, prognostic factors, and nomograms for bone metastasis in patients with newly diagnosed infiltrating duct carcinoma of the breast: a population-based study

Abstract Background Breast cancer is the most common malignancy in women, and it is also the leading cause of death in female patients; the most common pathological type of BC is infiltrating duct carcinoma (IDC). Some nomograms have been developed to predict bone metastasis (BM) in patients with breast cancer. However, there are no studies on diagnostic and prognostic nomograms for BM in newly diagnosed IDC patients. Methods IDC patients with newly diagnosed BM from 2010 to 2016 in the Surveillance, Epidemiology and End Results (SEER) database were reviewed. Multivariate logistic regression analysis was used to identify risk factors for BM in patients with IDC. Univariate and multivariate Cox proportional hazards regression analysis were used to explore the prognostic factors of BM in patients with IDC. We then constructed nomograms to predict the risk and prognosis of BM for patients with IDC. The results were validated using bootstrap resampling and retrospective research on 113 IDC patients with BM from 2015 to 2018 at the Affiliated Hospital of Chengde Medical University. Results This study included 141,959 patients diagnosed with IDC in the SEER database, of whom 2383 cases were IDC patients with BM. The risk factors for BM in patients with IDC included sex, primary site, grade, T stage, N stage, liver metastasis, race, brain metastasis, breast cancer subtype, lung metastasis, insurance status, and marital status. The independent prognostic factors were brain metastases, race, grade, surgery, chemotherapy, age, liver metastases, breast cancer subtype, insurance status, and marital status. Through calibration, receiver operating characteristic curve and decision curve analyses, we found that the nomogram for predicting the prognosis of IDC patients with BM displayed great performance both internally and externally. Conclusion These nomograms are expected to be a precise and personalized tool for predicting the risk and prognosis for BM in patients with IDC. This will help clinicians develop more rational and effective treatment strategies.

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Risk and prognostic factors of breast cancer with liver metastases

BMC Cancer ◽

10.1186/s12885-021-07968-5 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Lei Ji ◽

Lei Cheng ◽

Xiuzhi Zhu ◽

Yu Gao ◽

Lei Fan ◽

...

Keyword(s):

Breast Cancer ◽

Risk Factors ◽

Prognostic Factors ◽

Targeted Therapy ◽

Liver Metastasis ◽

Cancer Patients ◽

Triple Negative ◽

Seer Database ◽

Breast Cancer Patients ◽

Death Risk

Abstract Background Liver metastasis is a significant adverse predictor of overall survival (OS) among breast cancer patients. The purpose of this study was to determine the risk and prognostic factors of breast cancer with liver metastases (BCLM). Methods Data on 311,573 breast cancer patients from the Surveillance, Epidemiology, and End Results (SEER) database and 1728 BCLM patients from Fudan University Shanghai Cancer Center (FUSCC) were included. Logistic regression was used to identify risk factors for liver metastasis. Cox proportional hazards regression model was adopted to determine independent prognostic factors in BCLM patients. Results Young age, invasive ductal carcinoma, higher pathological grade, and subtype of triple-negative and human epidermal growth factor receptor 2 positive (HER2+) were risk factors for developing liver metastasis. The median OS after liver metastasis was 20.0 months in the SEER database and 27.3 months in the FUSCC dataset. Molecular subtypes also played a critical role in the survival of BCLM patients. We observed that hormone receptor-positive (HR+)/HER2+ patients had the longest median OS (38.0 for SEER vs. 34.0 months for FUSCC), whereas triple-negative breast cancer had the shortest OS (9.0 vs. 15.6 months) in both SEER and FUSCC. According to the results from the FUSCC, the subtype of HR+/HER2+ (hazard ratio (HR) = 2.62; 95% confidence interval (CI) = 1.88–3.66; P < 0.001) and HR−/HER2+ (HR = 3.43; 95% CI = 2.28–5.15; P < 0.001) were associated with a significantly increased death risk in comparison with HR+/HER2- patients if these patients did not receive HER2-targeted therapy. For those who underwent HER2-targeted therapy, however, HR+/HER2+ subtype reduced death risk compared with HR+/HER2- subtype (HR = 0.74; 95% CI = 0.58–0.95; P < 0.001). Conclusions Breast cancer patients at a high risk for developing liver metastasis deserve more attention during the follow-up. BCLM patients with HR+/HER2+ subtype displayed the longest median survival than HR+/HER2- and triple-negative patients due to the introduction of HER2-targeted therapy and therefore it should be recommended for HER2+ BCLM patients.

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Diagnostic and Prognostic Nomograms for Bone Metastasis in Patients With Newly Diagnosed Renal Cell Carcinoma

10.21203/rs.3.rs-76729/v1 ◽

2020 ◽

Author(s):

Zhangheng Huang ◽

Chuan Hu ◽

Yuexin Tong ◽

Chengliang Zhao

Keyword(s):

Renal Cell Carcinoma ◽

Regression Analysis ◽

Prognostic Factors ◽

Brain Metastasis ◽

Roc Curve ◽

Renal Cell ◽

Histologic Type ◽

Seer Database ◽

Newly Diagnosed ◽

N Stage

Abstract BackgroundBone metastasis (BM) is one of the common sites of renal cell carcinoma (RCC), and patients with BM have a worse prognosis than those without it. We aimed to develop two nomograms to quantify the risk of BM and predict the prognosis of RCC patients with BM.MethodsWe reviewed patients with newly diagnosed RCC with BM in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. Multivariate logistic regression analysis was used to determine independent predictors of BM in RCC patients. Univariate and multivariate Cox proportional hazards regression analysis was used to determine independent prognostic factors for BM in RCC patients. Diagnostic and prognostic nomograms were established and evaluated by calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA).ResultsThe study included 37554 patients newly diagnosed with RCC in the SEER database, 537 of whom were BM patients. Risk factors for BM in RCC patients included sex, tumor size, liver metastasis, lung metastasis, brain metastasis, N stage, T stage, histologic type, and grade. Independent prognostic factors for RCC with BM were grade, histologic type, N stage, surgery, brain metastasis, and lung metastasis. Calibration, ROC curve, and DCA showed that both diagnostic and prognostic nomograms showed good performance.ConclusionsDiagnostic and prognostic nomograms were established to predict the risk of BM in RCC and the prognosis of RCC with BM, respectively. These nomograms strengthen each patient's prognosis-based decision making, which is of great significance in improving the prognosis of patients.

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Analyzing mRNAsi-Related Genes Identifies Novel Prognostic Markers and Potential Drug Combination for Patients with Basal Breast Cancer

Disease Markers ◽

10.1155/2021/4731349 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Kai Huang ◽

Yu Wu ◽

YunQing Xie ◽

LiYing Huang ◽

Hong Liu

Keyword(s):

Breast Cancer ◽

Prognostic Factors ◽

Prognostic Model ◽

Drug Sensitivity ◽

Learning Algorithm ◽

Breast Cancer Subtype ◽

Metabolic Reprogramming ◽

Cancer Subtypes ◽

Basal Breast Cancer ◽

Cancer Subtype

Basal breast cancer subtype is the worst prognosis subtypes among all breast cancer subtypes. Recently, a new tumor stemness index-mRNAsi is found to be able to measure the degree of oncogenic differentiation of tissues. The mRNAsi involved in a variety of cancer processes is derived from the innovative application of one-class logistic regression (OCLR) machine learning algorithm to the whole genome expression of various stem cells and tumor cells. However, it is largely unknown about mRNAsi in basal breast cancer. Here, we find that basal breast cancer carries the highest mRNAsi among all four subtypes of breast cancer, especially 385 mRNAsi-related genes are positively related to the high mRNAsi value in basal breast cancer. This high mRNAsi is also closely related to active cell cycle, DNA replication, and metabolic reprogramming in basal breast cancer. Intriguingly, in the 385 genes, TRIM59, SEPT3, RAD51AP1, and EXO1 can act as independent protective prognostic factors, but CTSF and ABHD4B can serve as independent bad prognostic factors in patients with basal breast cancer. Remarkably, we establish a robust prognostic model containing the 6 mRNAsi-related genes that can effectively predict the survival rate of patients with the basal breast cancer subtype. Finally, the drug sensitivity analysis reveals that some drug combinations may be effectively against basal breast cancer via targeting the mRNAsi-related genes. Taken together, our study not only identifies novel prognostic biomarkers for basal breast cancers but also provides the drug sensitivity data by establishing an mRNAsi-related prognostic model.

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The impact of young age at diagnosis (age <40 years) on prognosis varies by breast cancer subtype: A U.S. SEER database analysis

The Breast ◽

10.1016/j.breast.2021.12.006 ◽

2021 ◽

Author(s):

Hee Jeong Kim ◽

Seonok Kim ◽

Rachel A. Freedman ◽

Ann H. Partridge

Keyword(s):

Breast Cancer ◽

Breast Cancer Subtype ◽

Young Age ◽

Age At Diagnosis ◽

Seer Database ◽

Database Analysis ◽

Cancer Subtype ◽

Subtype A ◽

The Impact ◽

Diagnosis Age

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Abstract C064: Hormone-related risk factors and breast cancer subtype in African American women

10.1158/1538-7755.disp18-c064 ◽

2020 ◽

Author(s):

Jennifer Davis ◽

Cecilia Jimenez ◽

Chrystina Clinton ◽

Mary Kay Fadden ◽

Loren Lipworth ◽

...

Keyword(s):

Breast Cancer ◽

Risk Factors ◽

African American ◽

African American Women ◽

Breast Cancer Subtype ◽

American Women ◽

Related Risk ◽

Cancer Subtype

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Risk factors associated with the triple-negative breast cancer subtype within four race/ethnicities

Breast Cancer Research and Treatment ◽

10.1007/s10549-017-4159-y ◽

2017 ◽

Vol 163 (1) ◽

pp. 151-158 ◽

Cited By ~ 7

Author(s):

Carol A. Parise ◽

Vincent Caggiano

Keyword(s):

Breast Cancer ◽

Risk Factors ◽

Triple Negative Breast Cancer ◽

Triple Negative ◽

Breast Cancer Subtype ◽

Factors Associated ◽

Cancer Subtype

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Risk and prognostic factors of breast cancer with liver metastases

10.21203/rs.3.rs-17121/v2 ◽

2020 ◽

Author(s):

Lei ji ◽

Lei Cheng ◽

Xiuzhi Zhu ◽

Yu Gao ◽

Lei Fan ◽

...

Keyword(s):

Breast Cancer ◽

Risk Factors ◽

Prognostic Factors ◽

Targeted Therapy ◽

Liver Metastasis ◽

Cancer Patients ◽

Triple Negative ◽

Seer Database ◽

Breast Cancer Patients ◽

Death Risk

Abstract Background: Liver metastasis is a significant adverse predictor of overall survival (OS) among breast cancer patients. The purpose of this study was to determine the risk and prognostic factors of breast cancer with liver metastases (BCLM). Methods: Data on 311,573 breast cancer patients from the Surveillance, Epidemiology, and End Results (SEER) database and 1728 BCLM patients from Fudan University Shanghai Cancer Center (FUSCC) were included. Logistic regression was used to identify risk factors for liver metastasis. Cox proportional hazards regression model was adopted to determine independent prognostic factors in BCLM patients.Results: Young age, invasive ductal carcinoma, higher pathological grade, and subtype of triple-negative and human epidermal growth factor receptor 2 positive (HER2+) were risk factors for developing liver metastasis. The median OS after liver metastasis was 20.0 months in the SEER database and 27.3 months in the FUSCC dataset. Molecular subtypes also played a critical role in the survival of BCLM patients. We observed that hormone receptor-positive (HR+)/HER2+ patients had the longest median OS (38.0 for SEER vs. 34.0months for FUSCC), whereas triple-negative breast cancer had the shortest OS (9.0 vs. 15.6 months) in both SEER and FUSCC. According to the results from the FUSCC, the subtype of HR+/HER2+ (hazard ratio (HR)=2.62; 95% confidence interval (CI)= 1.88-3.66; P<0.001) and HR-/HER2+ (HR=3.43; 95% CI=2.28-5.15; P<0.001) were associated with a significantly increased death risk in comparison with HR+/HER2- patients if these patients did not receive HER2-targeted therapy. For those who underwent HER2-targeted therapy, however, HR+/HER2+ subtype reduced death risk compared with HR+/HER2- subtype (HR=0.74; 95% CI=0.58-0.95; P<0.001).Conclusions: Breast cancer patients at a high risk for developing liver metastasis deserve more attention during the follow-up. BCLM patients with HR+/HER2+ subtype displayed the longest median survival than HR+/HER2- and triple-negative patients due to the introduction of HER2-targeted therapy and therefore it should be recommended for HER2+ BCLM patients.

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