This is the first study to explicitly consider a proxy for women's physiologic age as well as age-specific disease natural history in making breast cancer screening decisions for older women. At a threshold of cost-effectiveness of $80,000, our results suggest that it is cost-effective to conduct biennial screening until age 79. If a threshold of $60,000 is considered cost-effective, then screening to age 79 is only cost-effective if limited to women with life expectancies in the top quartile for their ages. These conclusions are based on the assumption that all older women with breast cancer have survival comparable to that seen in clinical trials. If treatment patterns are not ideal and survival is lower, as is the case at present, then screening has greater benefits, and it might be appropriate to continue screening without an upper age limit.
The result that screening benefits are greatest in women with the longest life expectancy is intuitively obvious. However, clinicians often underestimate older women's life expectancy,70
and there is considerable heterogeneity in health and functioning.22
Using a threshold for cost-effectiveness of $80,000 per LYS, a figure many would consider reasonable by current standards for screening,6,71
it is cost-effective to screen women with a life expectancy of 9.5 years. This value can be expected for 75% of 79-year-olds, about 50% of 80-year-olds, and 25% of 85-year-olds.22
Therefore, one practical implication of our analysis is that simple methods to determine life expectancy in clinical settings could aid screening decisions for older women.27,28
Our results imply that prevailing treatment patterns (and the resultant survival) play a central role in screening decisions. However, optimal treatment of older women remains controversial, largely as a result of a paucity of primary data in this age group, with only 1% to 2% of older women treated in clinical trials,67
and only 30% to 40% receiving some chemotherapy.72,73
If such patterns continue, then our model suggests that screening may be beneficial beyond age 79, especially for the healthiest women.
If we could accurately triage women according to risk of developing breast cancer, then it is also reasonable to screen to age 79, and perhaps for life among high-risk women. This finding confirms results of an earlier model that showed that screening older high-risk women (based on bone mineral density, a proxy for estrogen exposure) was cost-effective until age 79, costing $66,773 per life year saved, compared to stopping at age 69. That result is very similar to our result of $62,843 per year of life saved for screening high-risk women (based on family history) to age 79 (vs stopping at age 70).
We found that from a societal perspective, screening is too expensive relative to its benefits to be offered on an annual basis to average-risk and average-health women after age 70. However, optimal intervals depend on disease biology, particularly the time from stages that are detectable preclinically to stages that present clinically with symptoms. For instance, if tumors grow more slowly in older women, with a preclinical detectable period of 6.2 years,74
then screening intervals might logically be extended from every 2 to every 3 to 5 years.
The benefits of screening older women have been noted in other studies75,76
and recent reviews of cost-effectiveness analyses have concluded that biennial screening after age 65 is generally cost-effective,77
especially in the absence of major comorbidity limiting life expectancy.78
This is very similar to our finding that cost-effectiveness is most favorable for women in the top 25% of life expectancy for their age group.
When caring for asymptomatic populations, it is important to consider the harms as well as the benefits of screening. If screening is extended from age 70 to 79, or for a lifetime, then women have an increased risk of having a false positive result.8
One way to decrease the number of false positive exams is to extend the screening interval among older women. This would decrease costs, and, if tumors are slow growing, still maintain benefits. Women who are screen detected live with cancer and treatment consequences for a longer period of time than if clinically diagnosed. If women value life as a breast cancer survivor less than life in their general health, then the cost per QALY increases and screening could result in a small loss of quality-adjusted years. If women are relieved to have their disease detected earlier through screening, even if they live longer with the knowledge of cancer, then screening will still be beneficial. Thus, women's values must be carefully weighed in all screening decisions.
Our analysis has several important strengths, including use of current standards for cost-effectiveness analyses,24
developing a paradigm for basing decisions on physiological as opposed to chronological age, estimation of age-specific tumor biology, a robust model, and assessment of the impact of uncertain parameters.
Despite these strengths, there are several issues that should be considered when interpreting our results. First, we used life expectancy corresponding to quartiles of health and age to measure the probability of death as a proxy for physiological age. Clearly, data that link direct measurement of physiological reserve to clinical assessments of health status and life expectancy would be invaluable in individual decision making. In the interim, using life expectancy based on individual health conditions or self-reported health, rather than average U.S. age-specific life expectancies, may be a better indicator than age per se for use in clinical practice.
Second, while our model goes beyond many prior models of screening, our estimates of age-specific tumor natural history are fairly crude and limited by the relative paucity of data for this age group. Also, within any age group, breast cancer is a heterogeneous disease with variability in aggressiveness and probability of disease progression.
Next, our results must also be considered in the context of the current controversies about the effectiveness of mammography.9,79
Our model does not make a direct assumption about the impact of mammography on breast cancer mortality. Rather, we rely on observed stage distributions among screened and unscreened older populations to calculate screening benefits. Also, within each stage, we assumed similar survival for mammographically detected and non-screen-detected cancers. This assumption biases results against screening benefits.
Fourth, we restricted the screening intervals evaluated to those currently under consideration or in use in the United States. If it becomes generally acceptable to extend screening intervals to every 3 to 5 years after a certain age, then our model could be used to estimate the potential costs savings relative to any losses in benefits.
In addition, we used Medicare reimbursements as the single best source of costs for all analyses, while our base survival estimates were derived from clinical trials. Costs in clinical trials may be higher or lower than average, depending on intensity and efficiency of care. At present, we are not aware of any data that compare treatment costs for older women off and on clinical trials. Our model also does not capture the effects of distress associated with a false positive screen,80,81
but given the transient nature of this adverse event, it is not likely to alter our conclusions. Finally, our results may only be generalizable to U.S. screening policies.
Breast cancer is largely a disease of old age. Older women are a rapidly growing segment of the U.S. population and will be very heterogeneous in their health and functioning. We recommend that policymakers and clinicians explicitly consider life expectancy, or “physiological age,” how aggressively older women with cancer will be treated, and women's preferences in making screening decisions affecting older women.