Amanda L Kong1,2, Ann B Nattinger3,4, Emily McGinley3, Liliana E Pezzin3,4. 1. Division of Surgical Oncology, Department of Surgery, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA. akong@mcw.edu. 2. Center for Patient Care and Outcomes Research, Medical College of Wisconsin, Milwaukee, WI, USA. akong@mcw.edu. 3. Center for Patient Care and Outcomes Research, Medical College of Wisconsin, Milwaukee, WI, USA. 4. Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA.
Abstract
PURPOSE: To examine the relationship between patient and tumor characteristics, patterns of breast cancer care, and 5-year survival among a population-based cohort of elderly women with incident breast cancer, with a special focus on identifying sources of socioeconomic (SES) disparities in outcomes. METHODS: We identified women with newly diagnosed breast cancer in 2006-2009 from the Surveillance and Epidemiology End Result study linked with Medicare claims. A Classification and Regression Tree (CART) model was applied to 13 individual indicators of neoadjuvant and adjuvant breast cancer treatment, tumor characteristics, and patient sociodemographic variables to identify patterns with the greatest discriminant value in predicting 5-year survival. We subsequently examined the extent to which these patterns varied by the patient's SES. RESULTS: Survival probabilities associated with the 18 unique CART-identified patterns ranged from 22 to 87%. The number of positive axillary nodes was the best single discriminator between high and lower survival outcomes. The most common discriminant factor among patterns with poor (< 25%) survival was the absence of radiation treatment, followed by the presence of comorbidities, tumor size > 2 cm, and no breast surgery. Relative to high SES women, poor women were nearly four times (12.3% vs. 3.2%, p < 0.001) as likely to be classified in the pattern associated with worse survival, and less likely (31.7% vs. 52.9%, p = 0.04) to receive the pattern associated with the greatest survival. CONCLUSIONS: Greater adoption of effective patterns of care could improve survival of elderly women with incident breast cancer overall, and reduce SES disparities therein.
PURPOSE: To examine the relationship between patient and tumor characteristics, patterns of breast cancer care, and 5-year survival among a population-based cohort of elderly women with incident breast cancer, with a special focus on identifying sources of socioeconomic (SES) disparities in outcomes. METHODS: We identified women with newly diagnosed breast cancer in 2006-2009 from the Surveillance and Epidemiology End Result study linked with Medicare claims. A Classification and Regression Tree (CART) model was applied to 13 individual indicators of neoadjuvant and adjuvant breast cancer treatment, tumor characteristics, and patient sociodemographic variables to identify patterns with the greatest discriminant value in predicting 5-year survival. We subsequently examined the extent to which these patterns varied by the patient's SES. RESULTS: Survival probabilities associated with the 18 unique CART-identified patterns ranged from 22 to 87%. The number of positive axillary nodes was the best single discriminator between high and lower survival outcomes. The most common discriminant factor among patterns with poor (< 25%) survival was the absence of radiation treatment, followed by the presence of comorbidities, tumor size > 2 cm, and no breast surgery. Relative to high SESwomen, poor women were nearly four times (12.3% vs. 3.2%, p < 0.001) as likely to be classified in the pattern associated with worse survival, and less likely (31.7% vs. 52.9%, p = 0.04) to receive the pattern associated with the greatest survival. CONCLUSIONS: Greater adoption of effective patterns of care could improve survival of elderly women with incident breast cancer overall, and reduce SES disparities therein.
Authors: Julia Frebault; Carmen Bergom; Chandler S Cortina; Monica E Shukla; Yiwen Zhang; Chiang-Ching Huang; Amanda L Kong Journal: Clin Breast Cancer Date: 2021-07-16 Impact factor: 3.225