Related Experiment Video
Updated: Aug 12, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Racial and marital status influences on 10 year survival from breast cancer
1Department of Family Medicine, Wayne State University School of Medicine, Detroit, MI 48201, USA.
Abstract:
The association of race and marital status with survival during a 10 year period after a breast cancer diagnosis is described. The data for this study were obtained from the Metropolitan Detroit Cancer Surveillance System, a participant in the National Cancer Institute's SEER program. The study sample was 10,778 women (85.6% white and 14.4% black) diagnosed with incident invasive breast cancer between 1973 and 1978. Marital status was significantly associated with race, but had only a weak relationship with length of survival in a multivariate model predicting 10 year survival. However, race was strongly related to survival. African American women were significantly more likely than white women to die from breast cancer after controlling for age at diagnosis, marital status, tumor stage, histologic type, treatment status, and the interaction of age with stage. Ten years after being diagnosed with breast cancer, 38.2% of whites, compared with 33.3% of blacks were still living. These data confirm a body of literature which finds that blacks experience a shorter survival period following a cancer diagnosis than do whites. However, the relationship of marital status to cancer survival is still unclear and needs further study.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
Related Concept Videos
Longitudinal Research
Assumptions of Survival Analysis
Comparing the Survival Analysis of Two or More Groups
The Mantel-Cox Log-Rank Test
Applications of Life Tables
Cancer Survival Analysis