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Originally published as JCO Early Release 10.1200/JCO.2008.19.4928 on December 15 2008 © 2009 American Society of Clinical Oncology.
Hanging in the Balance: Making Decisions About the Benefits and Harms of Breast Cancer Screening Among the Oldest Old Without a Safety Net of Scientific EvidenceLombardi Comprehensive Cancer Center, Cancer Control Program, Georgetown University Medical Center, Washington, DC
Section of Geriatrics, Boston University Medical Center, Boston, MA The number of women in the United States today who are living into old age is steadily climbing as a result of aging of the "baby boom" generation, increases in life expectancy, decreases in rates of cardiovascular disease, improvements in medical care, and trends toward adoption of healthier, more active lifestyles.1,2 This so-called graying of America is coupled with cancer incidence rates that increase steadily with advancing age, peaking at approximately age 80 years.3 As a result of these parallel demographic and epidemiologic forces, over the coming years, more and more women are likely to survive to be at risk of developing cancer in their 80s. In fact, one third of all cancers in women and 23.5% of invasive breast cancers occur among women 80 years of age and older.3 This at-risk older population is very heterogeneous, with 25% of women who live to age 80 years being fairly robust and having a life expectancy of approximately 13 years, whereas 50% have a life expectancy of 8.6 years; the remaining 25% are frailer and will only live 4.6 years.4 The recent article by Badgwell et al5 on breast cancer screening among women 80 years and older and the controversy that has followed from its publication and media dissemination6–8 highlights several of the dilemmas facing clinicians, patients, and professional groups as they struggle to make rational, evidence-based decisions about optimal care for this diverse and growing older population. First and foremost of these difficulties is that women 80 years and older basically have not been included in mammography clinical trials—the gold standard of evidence about medical interventions. In the absence of clinical trial data, observational data are often used to provide evidence about the effectiveness of medical interventions in broader populations.9,10 Badgwell et al5 used the Surveillance, Epidemiology, and End Results–Medicare database to examine women 80 years and older with newly diagnosed breast cancer by past mammography use to provide indirect evidence regarding the value of screening in this age group. They found that women with more recent screening were diagnosed with smaller size tumors and had better 5-year breast cancer and all-cause survival than women with less screening.5 However, as pointed out by the authors themselves and their critics, these results may indicate screening benefits, or they may simply represent lead time, length biases, and selection factors. As noted by Berry et al6 in a letter about the article appearing in this issue of the Journal of Clinical Oncology, lead time biases result in an earlier diagnosis without any associated mortality benefit (ie, the woman is diagnosed earlier in the disease process, but that diagnosis and the treatment that follow do not alter the time that the woman was destined to die).11,12 In another observational study among older women that attempted to correct for lead time, screening seemed to reduce mortality for women younger than age 84 years but not among those older than 85 years.13 However, the lead time used, 1.25 years, may be an underestimate of the true lead time among older women,14 so this conclusion may also be overly optimistic.15 Other studies that attempt to correct for observational biases have not included women older than 74 years or have not separated results for women 80 years and older.15,16 Length bias (screen detection of the slowest growing tumors) results in screen detection of tumors with the most favorable prognosis, leading to overestimates of benefits.11 Thus length bias can be largely explained by the biologic characteristics of a tumor that govern its growth rate. For instance, in one large case series recently reported by Dong et al,17 biomarkers of tumor growth and aggressiveness were significantly related to mode of detection, with screen-detected tumors being more likely to have favorable prognosis markers than clinically detected tumors. Older women (age > 60 years) were also more likely to have screen versus symptomatic detection, although the numbers and distribution of women in the 60+ years age group was not presented. Of note, although mode of detection was an independent predictor of recurrence-free survival, it was not a significant predictor of breast cancer mortality. The authors concluded that it is impossible to separate length bias from any possible benefits of screening.17 The most extreme example of length bias is the situation in which a woman is diagnosed and treated for a screened detected breast cancer, but without screening, this slow-growing cancer would not have become clinically apparent before she died of, say, congestive heart failure a year later. This latter situation is sometimes referred to as overdiagnosis. Recently screened women in the study by Badgwell et al5 also had higher 5-year all-cause survival than those with less screening. This result suggests (as acknowledged by the authors) that there was a selection of the healthiest women to screening and that this selection bias may have overestimated screening benefits. These three types of biases, all of which make screening seem more beneficial than it may actually be, are the reasons that most researchers suggest that mortality reduction (and not 5-year survival) is the most appropriate metric for drawing conclusions about the effectiveness of screening.18 Thus, at this time, we are left with the fact that there is no evidence that screening women 80 and older with mammography results in reductions in mortality. Given the uncertainty about the effectiveness of screening mammography in this age group, groups setting practice guidelines and clinicians and their patients' must weigh the harms and costs associated with screening against potential benefits. The potential harms of screening include labeling a woman earlier in the disease course as having cancer and subjecting her to treatment and psychological distress, when that cancer was never destined to cause mortality. For instance, in a review of community-living nursing home–eligible older women undergoing state-mandated mammography, Walter et al19 found that 42% reported pain or psychological distress associated with that screening and 17% experienced burden or harm, defined by the authors as having evaluations for false-positive mammograms, refusing further work-up of an abnormal mammogram or having clinically insignificant cancers identified and treated (ie, cancers among women who died in < 2 years after screening). However, Badgwell et al argue that some of these types of harms may be offset by the detection of smaller tumors, because these require less extensive treatment than if they were detected at larger sizes and more advanced stages.5 Although this is true, they fail to balance this against the potential harm of labeling a woman as a patient with breast cancer when her cancer never would have actually clinically surfaced (so-called overdiagnosis). In this situation, the woman will needlessly undergo the stress and inconvenience of even minimal treatment. Data from mathematical models suggest that among women screened annually from age 40 to 84 years, as many as one quarter of screen-detected invasive cases among women 80 to 84 years of age represent such overdiagnosis (Lee SJ and Zelen M, personal communication, May, 2008). This is only the tip of the iceberg, because this estimate does not include cases of ductal carcinoma in situ, many of which would probably never progress to invasive disease.20,21 In recognition of this issue, Badgwell et al correctly excluded cases of ductal carcinoma in situ from analysis. Over one quarter of breast cancer deaths occur in women older than 80 years of age, and we do not know how much of this might be reduced via targeted screening and how much by the provision of standard treatments.22 Unfortunately, for older women and their clinicians, despite the more favorable tumor characteristics on average seen in older women, as noted by Berry et al,6 it is not possible to know prospectively which tumors are destined to progress or metastasize within the women's remaining life. To do so requires accurate prognostication about the cancer itself and a woman's overall future life expectancy. New technologies such as the Oncotype Dx (Genomic Health, Redwood City, CA) gene profile test23 may provide some specific guidance regarding the probability that a given tumor detected in an 80-year-old woman will recur, but this predictive test was developed using samples from clinical trials that included very few patients 80 years and older. With respect to estimating future life expectancy or risk of mortality, the histograms reported by Walter and Covinsky19 and prognostic indices such as developed by Lee et al24 that take into account age, comorbidities, and functional status are examples of emerging strategies to assist practicing physicians and their patients. Multiple morbidities are common in women 80 years and older,25 but functional limitations seem to be more important predictors of mortality than numbers of chronic conditions and an individual's age, especially from age 80 years onwards.26 Among the subset of women 80 years and older destined to live long enough to potentially benefit from early detection and treatment, we know little about the late effects of cancer therapy on older women (such as cardiac disease or cognitive impairment).27–30 Another portion of the "balance sheet" that is more difficult to consider in decisions about whether to continue screening beyond age 79 years are the costs associated with it.31,32 Screening beyond age 69 years can be fairly expensive per year of life saved, but targeting biennial screening to high-risk older women or to older women in the highest quartile of life expectancy for their ages (approximately 7 years) might be considered a reasonable expenditure in terms of current spending.31,32 However, it should be noted that decrements in quality of life associated with being labeled as a patient with breast cancer earlier in the disease course (ie, in the lead time) considerably decrease the cost-effectiveness of screening in the older age groups.32 These results underscore the point that individual preferences and life expectancy are critical components of decision making, at least from the perspective of groups setting guidelines. In practice it is difficult to estimate individual future life expectancy. Even if physicians can provide their oldest patients with accurate estimates of life expectancy, there are some data to suggest that older adults may overestimate their own life expectancy and the benefits of continued cancer screening, leading them to choose continued screening even when risks may outweigh benefits.33 Likewise, some physicians express intentions to continue to screen frail older women.34 Communication between older patients and their providers about screening cessation does influence screening behavior. For example, among women 80 years and older in generally good health, Schonberg et al7 found that physician recommendation was the most important factor cited in decisions about whether to stop or continue screening. However, others have found that not all patients want to have discussions about their life expectancy when making cancer screening decisions, so that consideration of patient preferences remains key in the decision making and communication process.35 In a recent trial in Australia targeting 70-year-old women, a decision aid was used to assist in informed decision making about stopping or continuing screening. The trial demonstrated statistically significant short-term increases in knowledge and perceptions of having an informed choice; however, there was no difference between the intervention and control group in actual use of screening within the period of the trial.36 It will be interesting to test whether such approaches will lead to longer-term differences in choices about continuing screening among older women and whether decision aids can be incorporated into geriatric primary care.
Unfortunately, even when considering older women with a long life expectancy and higher probability of benefiting from mammography (for example, With continued gains in life expectancy and increases in cancer incidence with age, clinicians will be caring for an ever increasing number of older individuals, including the "oldest old." Without a major shift in emphasis in clinical trials and new investments in understanding the impact of technology and downstream therapy on older populations, we will continue to practice in the context of limited trial evidence. We recommend investment in clinical trials specifically to assess cancer screening and treatment for older individuals. These studies will be expensive and challenging to conduct. They will need to be multisite and with long enough follow-up to assess the impact of screening and treatment on quality of life and include large enough populations to determine the subgroups most and least likely to benefit from interventions. Results of such studies would determine for whom screening can stop and when strategies such as watchful waiting used among older men with prostate cancer are appropriate for patients with breast cancer. Aside from the acknowledged methodological caveats and the potentially misleading press surrounding the article by Badgwell et al,5 the study's investigators and the Journal of Clinical Oncology are to be commended for raising difficult questions in gero-oncology, especially when the answers are imperfect. The intensity about the controversy that followed this publication reflects the fact that we are ill-prepared from a scientific knowledge perspective to provide health care rationally, ethically, equitably, and humanely to the "booming" older population. AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST The author(s) indicated no potential conflicts of interest. AUTHOR CONTRIBUTIONS Manuscript writing: Jeanne Mandelblatt, Rebecca A. Silliman Final approval of manuscript: Jeanne Mandelblatt, Rebecca A. Silliman Acknowledgment J.S.M. is supported by National Cancer Institutes Grants No. CA124924, CA127617, CA096940, and CA088283 and R.S. by Grants No. CA92395 and CA106979. The opinions expressed in this editorial solely reflect those of the authors and not any of the sponsoring agencies. REFERENCES 1. United States Department of Health and Human Services. Life expectancy at birth, at 65 years of age, and at 75 years of age, by race and sex: United States, selected years 1900-2005. Bethesda, MD: United States Department of Health and Human Services, 2008. 2. Arias E: United States life tables, 2003. Natl Vital Stat Rep 54:1–40, 2006.[Medline] 3. Ries L, Melbert D, Krapcho M, et al. SEER Cancer Statistics Review, 1975-2005, National Cancer Institute. Bethesda, MD http://seer.cancer.gov/csr/1975_2005/, based on November 2007 SEER data submission, posted to the SEER web site. http://seer.cancer.gov/csr/1975_2005/results_single/sect_02_table.04.pdf and http://seer.cancer.gov/csr/1975_2005/results_single/sect_04_table.08.pdf. 4. Walter LC, Covinsky KE: Cancer screening in elderly patients: A framework for individualized decision making. JAMA 285:2750–2756, 2001. 5. Badgwell BD, Giordano SH, Duan ZZ, et al: Mammography before diagnosis among women age 80 years and older with breast cancer. J Clin Oncol 26:2482–2488, 2008. 6. Berry D, Baines C, Baum M, Dickersin K, Fletcher SW, Gotzsche PC, et al: Flawed inferences about screenng mammography's benefit based on observational data. J Clin Oncol 27:639; 2009.[CrossRef][Medline] 7. Schonberg MA, McCarthy EP: Mammography screening among women aged 80 and older: Consider the risks. J Clin Oncol 27:640–641, 2009.[CrossRef][Medline] 8. Rabin R. Screening for breast cancer in elderly fuels a new debate. The New York Times. 2008 7 8. http://www.nytimes.com/2008/07/08/health/ 08canc.html?bl&ex=1216094400&en=9c44f4f08ee8c5af&ei=5087%0A. 9. Hillner BE, Mandelblatt J: Caring for older women with breast cancer: Can observational research fill the clinical trial gap? J Natl Cancer Inst 98:660–661, 2006. 10. Mandelblatt JS, Fryback DG, Weinstein MC, et al: Assessing the effectiveness of health interventions for cost-effectiveness analysis: Panel on Cost-Effectiveness in Health and Medicine. J Gen Intern Med 12:551–558, 1997.[CrossRef][Medline] 11. Morrison AS: The effects of early treatment, lead time and length bias on the mortality experienced by cases detected by screening. Int J Epidemiol 11:261–267, 1982. 12. Shwartz M: Estimates of lead time and length bias in a breast cancer screening program. Cancer 46:844–851, 1980.[CrossRef][Medline] 13. McCarthy EP, Burns RB, Freund KM, et al: Mammography use, breast cancer stage at diagnosis, and survival among older women. J Am Geriatr Soc 48:1226–1233, 2000.[Medline] 14. Lee S, Zelen M: A stochastic model for predicting the mortality of breast cancer. J Natl Cancer Inst Monogr, 79–86, 2006. 15. Mahnken JD, Chan W, Freeman DH, et al: Reducing the effects of lead-time bias, length bias and over-detection in evaluating screening mammography: A censored bivariate data approach. Stat Methods Med Res [epub ahead of print on April 29, 2008]. 16. Lawrence G, Wallis M, Allgood P, et al: Population estimates of survival in women with screen-detected and symptomatic breast cancer taking account of lead time and length bias. Breast Cancer Res Treat 2008 [epub ahead of print]. 17. Dong W, Berry DA, Bevers TB, et al: Prognostic role of detection method and its relationship with tumor biomarkers in breast cancer: The University of Texas M.D. Anderson Cancer Center experience. Cancer Epidemiol Biomarkers Prev 17:1096–1103, 2008. 18. Measurement of progress against cancer: Extramural Committee to Assess Measures of Progress Against Cancer. J Natl Cancer Inst 82:825–835, 1990. 19. Walter LC, Eng C, Covinsky KE: Screening mammography for frail older women: What are the burdens? J Gen Intern Med 16:779–784, 2001.[CrossRef][Medline] 20. Kerlikowske K, Molinaro A, Cha I, et al: Characteristics associated with recurrence among women with ductal carcinoma in situ treated by lumpectomy. J Natl Cancer Inst 95:1692–1702, 2003. 21. Ernster VL, Barclay J, Kerlikowske K, et al: Mortality among women with ductal carcinoma in situ of the breast in the population-based surveillance, epidemiology and end results program. Arch Intern Med 160:953–958, 2000. 22. Yood MU, Owusu C, Buist DS, et al: Mortality impact of less-than-standard therapy in older breast cancer patients. J Am Coll Surg 206:66–75, 2008.[CrossRef][Medline] 23. Paik S, Shak S, Tang G, et al: A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351:2817–2826, 2004. 24. Lee SJ, Lindquist K, Segal MR, et al: Development and validation of a prognostic index for 4-year mortality in older adults. JAMA 295:801–808, 2006. 25. Marengoni A, Winblad B, Karp A, et al: Prevalence of chronic diseases and multimorbidity among the elderly population in Sweden. Am J Public Health 98:1198–1200, 2008. 26. Lee SJ, Go AS, Lindquist K, et al: Chronic conditions and mortality among the oldest old. Am J Public Health 98:1209–1214, 2008. 27. Doyle JJ, Neugut AI, Jacobson JS, et al: Chemotherapy and cardiotoxicity in older breast cancer patients: A population-based study. J Clin Oncol 23:8597–8605, 2005. 28. Giordano SH, Kuo YF, Freeman JL, et al: Risk of cardiac death after adjuvant radiotherapy for breast cancer. J Natl Cancer Inst 97:419–424, 2005. 29. Patt DA, Goodwin JS, Kuo YF, et al: Cardiac morbidity of adjuvant radiotherapy for breast cancer. J Clin Oncol 23:7475–7482, 2005. 30. Hurria A, Rosen C, Hudis C, et al: Cognitive function of older patients receiving adjuvant chemotherapy for breast cancer: A pilot prospective longitudinal study. J Am Geriatr Soc 54:925–931, 2006.[CrossRef][Medline] 31. Kerlikowske K, Salzmann P, Phillips KA, et al: Continuing screening mammography in women aged 70 to 79 years: Impact on life expectancy and cost-effectiveness. JAMA 282:2156–2163, 1999. 32. Mandelblatt JS, Schechter CB, Yabroff KR, et al: Toward optimal screening strategies for older women: Costs, benefits, and harms of breast cancer screening by age, biology, and health status. J Gen Intern Med 20:487–496, 2005.[CrossRef][Medline] 33. Lewis CL, Kistler CE, Amick HR, et al: Older adults' attitudes about continuing cancer screening later in life: A pilot study interviewing residents of two continuing care communities. BMC Geriatr 6:10; 2006.[CrossRef][Medline] 34. Heflin MT, Pollak KI, Kuchibhatla MN, et al: The impact of health status on physicians' intentions to offer cancer screening to older women. J Gerontol A Biol Sci Med Sci 61:844–850, 2006.[Medline] 35. Kistler CE, Lewis CL, Amick HR, et al: Older adults' beliefs about physician-estimated life expectancy: A cross-sectional survey. BMC Fam Pract 7:9; 2006.[CrossRef][Medline] 36. Mathieu E, Barratt A, Davey HM, et al: Informed choice in mammography screening: A randomized trial of a decision aid for 70-year-old women. Arch Intern Med 167:2039–2046, 2007. 37. Williams BA, Lindquist K, Sudore RL, et al: Screening mammography in older women: Effect of wealth and prognosis. Arch Intern Med 168:514–520, 2008. 38. Bynum JP, Braunstein JB, Sharkey P, et al: The influence of health status, age, and race on screening mammography in elderly women. Arch Intern Med 165:2083–2088, 2005.
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Copyright © 2009 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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10% probability of death within the next 5 years), poor older women (characterized by net worth) are less likely to receive screening than wealthy older women. In fact, 48% of wealthy older women with a 
50% probably of death in 5 years were still receiving screening when they were unlikely to benefit.
