Targeting of Mammography Screening According to Life Expectancy in Women Aged 75 and Older

Abstract

OBJECTIVES To examine receipt of mammography screening by life expectancy (LE) among women ≥75 years. DESIGN/SETTING/PARTICIPANTS Cross-sectional survey of community dwelling US women ≥75 years that participated in the 2008 or 2010 National Health Interview Survey. MEASUREMENTS Using an index we previously developed and validated, we categorized women according to life expectancy (>9-years, 5–9 years, <5-years). We examined receipt of mammography screening in the past 2 years by life expectancy adjusting for sociodemographics, access to care, preventive orientation (e.g., receipt of flu vaccination), and receipt of a clinician recommendation for screening. RESULTS Of 2,266 respondents, 27.1% had >9-years LE, 53.4% had 5–9 years LE, and 19.5% had <5-years LE. Overall, 55.7% reported receiving mammography screening in the past 2 years. Life expectancy was strongly associated with receipt of screening (p<0.001); yet, 36.1% of women with <5-years LE were screened while 29.2% of women with >9-years LE were not screened. A clinician recommendation for screening was the strongest predictor of screening independent of life expectancy. Higher educational attainment, age, receipt of flu vaccination, and history of benign breast biopsy, were also independently associated with being screened. CONCLUSION Despite uncertainty of benefit, many women >75 years are screened with mammography. Life expectancy is strongly associated with receipt of screening which may reflect clinicians and patients appropriately considering LE in screening decisions. However, 36% of women with short LEs are still screened suggesting new interventions are needed to further improve targeting of screening by LE. Patient decision aids and guidelines encouraging clinicians to consider patient LE in screening decisions may improve care.

Receipt of Cancer Screening Is a Predictor of Life Expectancy

“…5 Other published methods include information on functional and emotional status, but these methods cannot be used with administrative data. 6,8 …”

“…[2][3][4] One example of over-testing is the case of a patient with limited life expectancy receiving a screening test for cancer. [5][6][7][8][9][10][11] There is a lag between when a cancer is diagnosed by screening and when it would be diagnosed through symptoms, and a further lag before screening lowers the risk of death from the cancer. 12 Thus, patients with limited life expectancy who undergo cancer screening are at risk of diagnosis and treatment of a cancer that would not otherwise have affected their health.…”

Capsule Commentary on Goodwin et al., Receipt of Cancer Screening is a Predictor of Life Expectancy

“…Of note, excluding beneficiaries diagnosed with cancer as a result of these tests did not affect the overall findings. However, since claims data do not capture beneficiaries' function, cognition, disease severity, or social support, and these factors affect receipt of cancer screening 4 , the prolonged survival associated with receipt of cancer screening among older adults is likely explained by these factors and probably reflects that providers are screening based on their judgement about patient's life expectancy.…”

An Individualized Approach to Cancer Screening Decisions in Older Adults: A Multilevel Framework

“…2,3 Recent guidelines encourage an individualized decisionmaking approach among older adults, where the risks and benefits of screening tests are weighed and the quantity and quality of life are considered. 1,3,4 These considerations are foundational to informing patient screening choices. 5,6 In clinical practice, implementation of preference-sensitive cancer screening depends on factors at the patient, clinician, and healthcare organization levels.…”

“…Health status among individuals in this age group varies widely, ranging from robust to frail. 1 As this variance increases with age, cancer screening decisions become increasingly complex. 2,3 Recent guidelines encourage an individualized decisionmaking approach among older adults, where the risks and benefits of screening tests are weighed and the quantity and quality of life are considered.…”