Effect of Age on Breast Cancer Patient Prognoses: A Population-Based Study Using the SEER 18 Database

• Published in: PloS one Vol. 11; no. 10; p. e0165409
• Main Authors: Chen, Hai-Long, Zhou, Mei-Qi, Tian, Wei, Meng, Ke-Xin, He, Hai-Fei
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 31.10.2016; Public Library of Science (PLoS)
• Subjects: Adult; Age; Age Factors; Age groups; Aged; Aged, 80 and over; Analysis; Biology and Life Sciences; Breast cancer; Breast Neoplasms - diagnosis; Breast Neoplasms - epidemiology; Cancer; Cancer metastasis; Cancer patients; Cancer research; Databases, Factual; Demography; Diagnosis; Epidemiology; Female; Geriatrics; Health aspects; Health risk assessment; Health risks; Histology; Hospitals; Humans; Identification methods; Kaplan-Meier Estimate; Medical diagnosis; Medical prognosis; Medical research; Medicine and Health Sciences; Metastases; Middle Aged; Multivariate Analysis; Neoplasm Staging; Older people; Oncology; Patients; People and Places; Population; Population studies; Population-based studies; Prognosis; Proportional Hazards Models; Regression analysis; Regression models; Risk factors; SEER Program; Studies; Surgery; Survival; Survival analysis; Women's health; Womens health; United States > US; China
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0165409

Age is an important risk factor for breast cancer, but data regarding whether patient age at diagnosis is related to breast cancer survival are conflicting. This population-based study evaluated the effect of age on breast cancer prognosis and identified outcome-related factors. We searched the Surveillance, Epidemiology, and End Results (SEER) database and enrolled female primary non-metastatic cases. Patients were subdivided into seven groups, and analyses of the associations between age and overall survival (OS) and breast cancer-specific survival (BCSS) were carried out using the Kaplan-Meier method and Cox regression model, respectively. We also assessed differences in survival among three specific age groups, using the ages of 30 and 50 years as cut-offs. Stratified analyses regarding race, histology, grade, stage and hormone receptor status were also carried out. A total of 133,057 female patients diagnosed with breast cancer from 2004 to 2008 were included in the current study (6.4% <40 years), Women aged 40 to 49 years and 60 to 69 years exhibited significantly better OS and BCSS, respectively (log-rank, p<0.001), than their counterparts in other groups. Middle-aged women exhibited distinctly better OS (log-rank, p<0.001) and BCSS (log-rank, p<0.001) than their counterparts in the other two age groups. Following adjustments for potential confounding factors, middle-age at breast cancer diagnosis was shown to be an independent predictor of favourable outcomes in terms of OS, but not BCSS (for OS, HR, 0.92; 95%CI, 0.87-0.98; p = 0.007; for BCSS, HR, 0.94; 95%CI, 0.80-1.01; p = 0.075, using the young group as reference). Stratified analysis showed that middle-age was significantly associated with increased survival, except among patients with stage III disease, and that elderly women faced worse prognoses than younger patients. Our results indicate that younger breast cancer patients exhibit more aggressive disease than older patients. Middle-aged patients exhibit better OS and BCSS than young and elderly patients but exhibit BCSS rates similar to those of young patients after adjustments for confounders. Stratified analysis demonstrated that middle-aged patients exhibited better survival than young patients, with the exception of patients with stage III disease. An age of 60 years or more was a significant independent predictor of a poor prognosis.