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In Association with
CONDITIONAL SURVIVAL AMONG FEMALE BREAST CANCER PATIENTS IN THE UNITED STATES
6th International Conference on EPIDEMIOLOGY & PUBLIC HEALTH
Ray M Merrill
Brigham Young University, USA
Keynote: Epidemiology (Sunnyvale)
DOI:
Abstract
The relative cancer survival rate may be more meaningful to patients because it indicates the chance they will not die from the specific disease. This measure can be further tailored to patients by updating it according to time already survived and for selected personal characteristics. In the current study, conditional relative survival for female breast cancer is presented, based on cases diagnosed during 2000-2008 and followed up through 2013, using population-based data from the Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute. Five-year relative survival improved from 89% at diagnosis to 93% (4.9%) for patients who had already survived 5 years. Five-year relative survival was 98% for local disease, 85% regional disease, and 30% for distant disease; 100% for Grade I, 94% for Grade II, 81% for Grade III, and 80% for Grace IV; 90% for Whites, 78% for Blacks, 82% for American Indians/Alaska Natives, and 91% for Asians; and 93% for married and 85% for singles. Improvement in 5-year relative survival from diagnosis to five years already survived was -1.1% for local disease, 3.2% regional disease, and 91.4% for distant disease; -0.9% for Grade I, -0.7% for Grade II, 11.4% for Grade III, and 14.2% for Grace IV; 3.9% for Whites, 13.4% for Blacks, 8.8% for American Indians/Alaska Natives, and 3.5% for Asians; and 2.8% for married and 6.8% for singles. Age and ethnicity had little influence on conditional relative survival. The association between 5-year relative survival and time already survived within stage groups remains similar after adjusting for age, race, ethnicity, marital status, and tumour grade.Biography
Ray Merrill is a Professor in the Department of Health Science at Brigham Young University. He joined the faculty in 1998, following employment as a Mathematical Statistician in the Applied Research Branch at the National Cancer Institute. His research interests include chronic disease epidemiology, social determinants of health and program planning and evaluation.
