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Updated: May 10, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Disparities in survival after female breast cancer diagnosis: a population-based study
Stacey L Tannenbaum1, Tulay Koru-Sengul, Feng Miao
1Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA. STannenbaum@med.miami.edu
Background:
Despite advances in treatment and increased screening, female breast cancer survival is affected by race, ethnicity, and socioeconomic status (SES). The purpose of this study was to substantiate disparities in breast cancer mortality in a large and unique dataset containing 7 distinct racial groups, 31 comorbidities, demographic and clinical/pathological patient characteristics, and neighborhood poverty information.
Methods:
Florida Cancer Data System registry (1996-2007) linked with the Agency for Health Care Administration and U.S. Census tract (n = 127,754) explored median survival and 1-, 3-, and 5-year survival rates by the Kaplan-Meier method. Log-rank tests compared survival curves by race/ethnicity/SES. Cox proportional hazards regression models were used to obtain unadjusted and adjusted hazard ratios (HR) and 95% confidence intervals.
Results:
Native Americans had the lowest median survival (7.4 years) and Asians had the highest (12.6 years). For the univariate analysis, worse survival was seen for blacks (HR = 1.44; p < 0.001) and better survival for Asians (HR = 0.71; p < 0.001), Asian Indians or Pakistanis (HR = 0.65; p = 0.013), and Hispanics (HR = 0.92; p < 0.001). Multivariate analysis demonstrated sustained survival detriment for blacks (HR = 1.28; p < 0.001) and improved survival for Hispanics (HR = 0.90; p = 0.001). For SES, there was an incremental improvement in survival for each higher SES category in all analyses (p < 0.001).
Conclusions:
Utilizing a large enriched state cancer registry controlling for multiple demographic, clinical, and comorbidities, we fully explored survival disparities in female breast cancer and found certain aspects of race, ethnicity, and SES to remain significantly associated with breast cancer survival. More research is needed to uncover the source of these ongoing disparities.
Related Concept Videos
Cancer Survival Analysis
Comparing the Survival Analysis of Two or More Groups
Disorders of the Female Reproductive System
Kaplan-Meier Approach
Truncation in Survival Analysis
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are observed.
