Helen M Johnson1, William Irish1, Mahvish Muzaffar2, Nasreen A Vohra1, Jan H Wong3. 1. Division of Surgical Oncology, Department of Surgery, East Carolina University Brody School of Medicine, 600 Moye Blvd, Greenville, NC, 27834, USA. 2. Department of Medicine, Division of Hematology/Oncology, East Carolina University Brody School of Medicine, Greenville, NC, USA. 3. Division of Surgical Oncology, Department of Surgery, East Carolina University Brody School of Medicine, 600 Moye Blvd, Greenville, NC, 27834, USA. wongj@ecu.edu.
Abstract
PURPOSE: The relationship between age at diagnosis and breast cancer-specific mortality (BCSM) is unclear. The aim of this study was to examine the nature of this relationship using rigorous statistical methodology. METHODS: A historical cohort study of adult women with invasive breast cancer in the SEER database from 2000 to 2015 was conducted. Multivariable Cox's cause-specific hazards model was used to evaluate the association of age at diagnosis with risk of BCSM. Functional relationship of age was assessed using cumulative sums of Martingale residuals and the Kolmogorov-type supremum test. RESULTS: A total of 206,332 women were eligible for study. Mean age at diagnosis was 59.7 ± 13.8 years. Median follow-up was 80 months. During the study period, 21,771 women (10.6%) died from breast cancer and 18,566 (9.0%) died from other causes. Cumulative incidence of BCSM at 120 months post-diagnosis was 14.4% (95% CI 14.2-14.6%). Age was found to be quadratically related to the risk of BCSM (p < 0.001), with a nadir at 45 years of age. The final Cox model suggests that a 30-year-old woman has approximately the same adjusted BCSM risk (HR 1.187, 95% CI 1.187-1.188) as a 60-year-old woman (HR 1.174, 95% CI 1.174-1.175). CONCLUSIONS: Women diagnosed with breast cancer at the extremes of age suffer disproportionate rates of cancer-specific mortality. The relationship between age at diagnosis and adjusted risk of BCSM is complex, consistent with a quadratic function. With the growing appreciation for breast cancer as a heterogeneous disease, it is essential to accurately address age as a prognostic risk factor in predictive models.
PURPOSE: The relationship between age at diagnosis and breast cancer-specific mortality (BCSM) is unclear. The aim of this study was to examine the nature of this relationship using rigorous statistical methodology. METHODS: A historical cohort study of adult women with invasive breast cancer in the SEER database from 2000 to 2015 was conducted. Multivariable Cox's cause-specific hazards model was used to evaluate the association of age at diagnosis with risk of BCSM. Functional relationship of age was assessed using cumulative sums of Martingale residuals and the Kolmogorov-type supremum test. RESULTS: A total of 206,332 women were eligible for study. Mean age at diagnosis was 59.7 ± 13.8 years. Median follow-up was 80 months. During the study period, 21,771 women (10.6%) died from breast cancer and 18,566 (9.0%) died from other causes. Cumulative incidence of BCSM at 120 months post-diagnosis was 14.4% (95% CI 14.2-14.6%). Age was found to be quadratically related to the risk of BCSM (p < 0.001), with a nadir at 45 years of age. The final Cox model suggests that a 30-year-old woman has approximately the same adjusted BCSM risk (HR 1.187, 95% CI 1.187-1.188) as a 60-year-old woman (HR 1.174, 95% CI 1.174-1.175). CONCLUSIONS:Women diagnosed with breast cancer at the extremes of age suffer disproportionate rates of cancer-specific mortality. The relationship between age at diagnosis and adjusted risk of BCSM is complex, consistent with a quadratic function. With the growing appreciation for breast cancer as a heterogeneous disease, it is essential to accurately address age as a prognostic risk factor in predictive models.
Entities:
Keywords:
Age distribution; Age groups; Breast cancer; Differential mortality; Mortality; Statistical model