Mammography screening is an important regular primary health care service aimed at detecting cancer with a favorable prognosis that cannot be detected by clinical breast examination. Although breast cancer incidence and mortality rates increase dramatically with age (National Cancer Institute, 1999), advanced age is associated with a decreased likelihood of receiving a mammogram (Blustein & Weiss, 1998). The introduction of Medicare coverage for biennial screening mammography between 1991 and 1997 has not affected this trend (Parker, Gebretsadik, Sabogal, Newman, & Lawson, 1998) because of the considerable scientific uncertainty and ambivalence surrounding breast cancer screening in older women. For many clinicians, it is unclear how age older than 75 and the presence of cognitive impairment should influence decisions about whether or not to recommend mammography. Unfortunately, meta-analysis cannot be used to decide what screening should be performed for women older than age 75 because clinical trials have not included substantial numbers of women in this age range. Decision analysis is a quantitative approach that can be used to assess the relative value of different decision options (Friedland et al., 1998). Based on a synthesis of the literature and the best available data, decision analysis was used to model and compare outcomes of mammography screening in a hypothetical cohort of women age 75 and older with and without cognitive impairment.
BREAST CANCER IN OLDER WOMEN
The incidence of breast cancer increases with age. Surveillance, Epidemiology, and End Results (SEER) data covering the period from 1973 to 1995 has indicated that for women in the age 25 to 29 cohort the incidence of breast cancer is 7.7 cases per 100,000 population (National Cancer Institute, 1999). The incidence rises sharply to 408.5 cases per 100,000 in the age 65 to 69 cohort and to 480.8 cases per 100,000 population for the age 75 to 79 cohort (National Cancer Institute, 1999). More than 50% of the 175,000 newly diagnosed cases of breast cancer annually occur in women age 65 and older (Costanza, 1994). Women age 65 and older represent 14% of the total female population, but they account for 43% of invasive breast cancer (Costanza et al., 1992). Mortality rates for breast cancer increase with age, with as many as 198 women per 100,000 population per year older than age 85 dying of breast cancer (National Cancer Institute, 1999).
Breast cancer in older women is thought to be a more indolent disease than in younger women. Risk factors for early disease recurrence and short survival are not as great among elderly individuals. Tumors in older women tend to have a lower proliferative rate and more well-differentiated histologic grades. Furthermore, the higher hormone-receptor content of postmenopausal tumors has been correlated with greater tumor response to hormonal therapy (Clark, 1992). The biology of breast cancer in older women suggests these women should have better survival rates than younger women.
Yet mortality is higher. Among women age 67 to 84 diagnosed with breast cancer, 32% have late-stage disease (McCarthy et al., 1998). The older than age 85 group has the highest likelihood of being diagnosed with metastatic disease (McCarthy et al., 1998), and there has been no apparent decline in mortality among women in this age group as there has been for younger women in the United States (Chevarley & White, 1997). Higher mortality may be a result of early detection because lack of previous mammography use has been associated strongly with cancer stage at diagnosis in women age 65 and older (McCarthy et al., 1998).
SCREENING EFFECTIVENESS FOR OLDER WOMEN
Among women age 50 to 69, reductions in breast cancer mortality of 30% to 40% have been achieved with screening programs including regular mammograms (Kerlikowske, Grady, Rubin, Sandrock, & Ernster, 1995). Similar reductions in breast cancer mortality were obtained among women age 65 to 74 in a nonrandomized clinical trial of mammography (van Dijck et al., 1997). The Breast Cancer Detection Demonstration Project (Byrne, Smart, Chu, & Hartman, 1994) has demonstrated that for all age groups studied, survival improves if breast cancer is diagnosed early without positive nodes at a small size and lower stage. The survival advantage attributable to mammography increases dramatically with age, from 36% in women age 50 to 59, to 43.5% in women age 67 and older (McCarthy et al, 1998). More important, early detection may improve quality of life (QOL) because fewer women will be diagnosed with metastatic disease (Costanza et al., 1992), which is very painful and does not necessarily result in a rapid death (McCool, 1994).
Studies which have examined the preferences and values women attribute to living with various stages of breast cancer indicate QOL is rated as poor under these circumstances. Gerard, Dobson, and Hall (1993) used the time trade-off method of quality adjusted life years (QALYs) to elicit the preferences of a convenience sample of 104 women, 60 of whom had breast cancer. Six breast cancer scenarios were presented to the women, and subjects were asked to evaluate the scenario as a percentage of good health. All of the scenarios were considered worse than good health. The best of the breast cancer scenarios was valued at 80% of good health. It included a description of good physical health (i.e., occasional discomfort around chest wall, some stiffness in shoulder, and extra care with appearance) and good mental health (i.e., not anxious about cancer diagnosis, cancer returning, or early death; sexual relations and social contacts as before). The worst breast cancer scenario was valued at 26% of good health. It included poor physical health (i.e., considerable discomfort around chest wall, stiffness in shoulder, extra care needed with appearance) and poor mental health (i.e., unduly anxious about cancer diagnosis, cancer returning and early death; sexual relations and social contacts badly affected). Although assessing patient's utilities is controversial (Mulley, 1989) and no consensus exists on the best methods to assess health outcomes (La Puma & Lawlor, 1990; Nelson & Berwick, 1989), most clinicians would agree the patient is the best source of information about their QOL with disease (Aaronson, 1990).
Screening options for breast cancer include breast self-examination (BSE), clinical breast examination (CBE), and mammography. WaId, Hacksaw, and Chamberlain (1994) assert there is no satisfactory evidence that BSE is of value. Mammography is the best method for detection of tumors, particularly small ones. According to Meden, Neues, Roben-Kampken, and Kuhn (1995), mammography is capable of detecting 94.5% of breast carcinomas. A meta-analysis conducted by Kerlikowske et al. (1995) determined the overall summary relative risk ratio for breast cancer mortality for women older than age 50 undergoing mammography compared with controls was .74 (95% confidence interval = .66 to .83). Shapiro (1994) concluded from a meta-analysis of eight trials the overall relative risk of screened women versus controls was .76 (95% confidence interval = .66 to .87).
Primary data on screening efficacy of mammography for women older than age 75 do not exist. Of the studies included in the abovedescribed meta-analyses, only two randomized control trials and one case-control study have included data on women age 70 to 74. Data collected in the Swedish two-county program were used to compare the relative risk (RR) ratio of death from breast cancer for women in an active screening program and women in a passive screening program (Tabar et al., 1995). For women age 50 to 74, the crude RR in Kopparberg county was .58 (95% confidence interval = .43 to .78) and the crude RR in Ostergotland county was .73 (95% confidence interval = .56 to .97). In the Nijmegen case-control study in the Netherlands (van Dijck, Holland, Verbeek, Hendricks, & Mravunac, 1994), among women age 65 to 74 the RR was .34 (95% confidence interval = .12 to .97). Thus, although bias in the case-control study partially may have accounted for some of the dramatic benefit of screening for the older than age 65 population, there still appears to be some continued benefit of screening for the age 70 to 74 population.
Although the American Cancer Society (ACS) and the National Cancer Institute (NCI) recommend mammography be performed annually for women age 50 and older and have set no upper age limit for screening (Kiinkman, Zazove, Mehr, & Ruff in, 1992), fewer than half of the physicians surveyed agreed with this guideline (Marwill, Freund, & Barry, 1996). In addition to advanced age (older than age 75), having mild dementia, residing in a nursing home, and having impaired functional status substantially reduces the likelihood of mammography screening (Blustein & Weiss, 1998; Marwill et al, 1996). In the 1990 National Health Interview Survey (NHIS), 65.2% of women age 55 to 64 have had mammography screening, but only 49% of women age 75 to 84 and 30% of women age 85 and older reported ever having mammograms (Ruchlin, 1997). This reduced usage rate seems inconsistent with what is known about the sensitivity and specificity of mammography for women older than age 75. Sensitivity for older women is much higher than for younger women. For women in the age 40 to 49 category, sensitivity is only 60%. For women in the age 70 to 74 category, sensitivity is more than 95% (Tabar et al., 1992). This means the test does a much better job of identifying true cases of breast cancer in older women. To model the potential benefits of biennial mammography for women older than age 75, a decision analysis model was constructed to compare the effects of screening healthy and cognitively impaired older women for breast cancer versus performing no screening at all.
VALUES USED IN THE DECISION TREE
Decision analysis begins by systematically separating a problem into its component parts and creating a decision tree to represent the components and decision options. The medical literature or expert opinion is used as a source to estimate probabilities and define the range of uncertainties around these probabilities. The values for each outcome are measured or implied, such as survival or quality-adjusted survival (Friedland et al., 1998). For this project, hypothetical cohorts of women in three age categories were examined: age 75 to 79, age 80 to 84, and age 85 and older. Two models were tested for each age group: one that assumed no prior screening, and one that assumed the woman was continuing a program of regular screening. Two possible outcomes were evaluated in each of the scenarios: one that used QALYs and another that compared the costs of the screening program and the management of disease recurrence. A QALY is determined by adjusting the length of time in a health outcome according to a utility score on a scale of 0 to 100 reflecting the quality or value of that health state. To account for the comorbidity associated with cognitive impairment (decreased life expectancy), separate analyses were conducted with cognitively impaired women in the three age categories for no prior screening and continued screening using QALYS and costs.
The decision tree in the Figure was used to compare the efficacy of breast cancer screening every 2 years with no screening for healthy and cognitively impaired women. The decision being modeled is on the left (screen versus no screen) and the outcomes are on the right (QALYs). The decision tree is composed of decision nodes, chance nodes, and health outcomes. A decision node, represented on the tree by a square, is a point where the clinician must choose an action or strategy. Chance nodes, which appear as circles on the tree, represent the probability of events such as disease recurrence. All branches of the tree end in a terminal state representing one of the final possible outcomes. For both healthy and cognitively impaired women, trees were constructed that assumed no previous screening and biennial screening. It was assumed that all women would be treated in accordance with the stage of cancer at diagnosis. It also was assumed that those women with a false negative test would have their cancer progress and eventually would be diagnosed and treated before the next mammogram (interval diagnosis). Unscreened women either would have cancer and receive a late diagnosis or would not have cancer and suffer no ill effects.
VALUES USED IN THE DECISION TREE
Values Assigned at Probability Nodes
The probability and utility values assigned to nodes in the model are presented in Table 1. The values for age-specific life expectancy and disease mortality as well as breast cancer stage distribution were taken from Mandelblatt et al. 's (1992) decision-analysis model. Incidence rates and life expectancy values are critical components used in calculating QALYs. The prior probability of disease used for the analysis was calculated using the prevalence of disease in older women first entering the program and using annual incidence data to simulate results after the screening program was applied (Pauker, 1992). Values for life expectancy were calculated using data from Katzman's (1976) work, which indicates life expectancy is 5 years less than average for people with Alzheimer's disease.
Screening Test Parameters
The sensitivity and specificity of mammography were assumed to be .95 and .95, respectively. The biopsy was assumed to be the best available test for breast cancer diagnosis and, therefore, was considered to have a sensitivity and specificity of 100%. Because Medicare only reimbursed for biennial screening until recently, a screening interval of every 2 years was evaluated. The model also assumed no biopsy-related mortality or perioperative death with treatment because in Mandelblatt et al.'s (1992) decision analysis, operative mortality had no impact on the screening decision.
COSTS OF /MAMMOGRAPHY AND RECURRENCE
Stage Distribution of Breast Cancer
Using data on women older than age 50 from the Breast Cancer Detection Demonstration Project (BCDDP) (Baker, 1982) and data from women age 65 to 74 in the Swedish trials (Tabar et al., 1985), Mandelblatt et al. (1992) estimated the proportions of screened and diagnosed women in each stage of cancer were: localized = 73%; regional = 25%; and distant = 2%. Localized disease is defined as Stage 1 disease, and regional disease is defined as Stage 2 and 3 disease. The primary difference between localized and regional disease is the presence or absence of metastasis in the axilla at the time of diagnosis (Mueller, 1994). Distant disease is defined as disseminated Stage 4 breast cancer. Based on data from the BCDDP, women diagnosed during the interval between screenings were assumed to have the following stage distribution of breast cancer following a false negative mammogram result: 70% localized, 30% regional, and 0% distant. Stage distribution for breast cancer among older unscreened women was estimated using SEER data. These proportions (localized = 51%, regional - 37%, and distant = 12%) are similar to those observed among controls in the Swedish study (Tabar et al., 1985). Cognitively impaired women were assumed to have rates equal to healthy women for early, interval, and late diagnosis.
Measures of utility were life expectancy using the declining exponential approximation of life expectancy (DEALE) model, as described by Beck, Pauker, Gottlieb, Klein, and Kassirer (1982), and QOL years using the preferences for various breast cancer scenarios described by Gerard, Dobson, and Hall (1993). These utility assessments are similar to the lower end utilities of health states used to adjust for QOL in the sensitivity analysis of Mandelblatt et al. (1992). The short-term adverse effects of screening for women without cancer and women with false positive screening results (Lerman et al., 1991) was not included in the QOL adjustments.
Costs of Screening
Costs associated with the various scenarios included the screening program costs plus the costs of managing metastatic disease following recurrence (Table 2). Costs were based on a retrospective cost analysis of individuals at an academic medical center for physician, laboratory, office, and hospital services (Hillner & Smith, 1991) and on published estimates of the costs of treating disease recurrence from Medicare data (Baker, Kessler, & Smucker, 1989). Indirect costs were not included. Costs of treatment assumed outpatient care for nonfatal first recurrences and 7 days of hospitalization for nonfatal second or third recurrences. Costs for terminal care were greater if death occurred in the first year. A discount rate of 5% was used to reflect that the present value of costs and wellness is greater than the value of either in the future. Although the data used to estimate treatment costs are relatively old, literature review indicates the figures are similar to more recently published estimates (Hayman, Hillner, Harris, & Weeks, 1998). The costs for all screening scenarios among the hypothetical cohorts were compared.
SAVINGS IN LIFE EXPECTANCY FOR QUALITY-OF-LIFE-ADJUSTED MODELS
Breast Cancer Recurrence
In addition to enhancing survival, a substantial portion of the benefit of detecting preclinical breast cancer is decreasing the probability of late recurrence (Pauker, 1992). Women's preferences for treatment are influenced by fear of recurrence and the desire to avoid a second surgery in the future (Long, 1993). According to interviewed oncologists and oncology nurses, recurrence is associated with poor QOL (Hillner & Smith, 1991). Therefore, recurrence rates were selected as a proxy for the likelihood of experiencing a good or bad outcome after treatment. Recurrence rates reported after adequate treatment for early localized disease range from 7% to 10% (Balch, Singletary, & Bland, 1993). The likelihood of complete remission drops from 90% in early localized disease to 10% to 20% for Stage 3 disease, and only 10% of patients with distant disease have a complete remission (Hortobagyi, 1994).
One-way sensitivity analyses were performed to test the effects of varying the ranges of variables with potentially problematic estimates. This process challenges the conclusions of the decision analysis by systematically varying the values of the probabilities, utilities, and cost estimates used in the decision tree. Estimates were varied around a range corresponding to a reasonable area of uncertainty for prior probability of disease, QOL, costs of recurrence, sensitivity, and specificity.
The results of the multiple decision analyses demonstrated that screening every 2 years results in increased QALYs for all age categories of women (Table 3). The most pronounced increase in QALYs was among women who were not screened previously. For women who had been screened at least once, the increase in QALYs with ongoing screening was minimal for all age groups. When costs of screening and treatment of recurrence were used as outcomes, two different patterns emerged. Mammography screening resulted in decreased combined recurrence and screening costs for women who were never screened. The combined costs of screening and managing recurrence were less in the nonscreened population than for women who had started a regular screening regimen. In other words, the advantage gained by early detection in reducing costs of managing recurrent disease was lost when screening was repeated over time.
Effect of Cognitive Impairment
The presence of cognitive impairment did not alter the finding that screening increased QALYs, despite the far lower life expectancy of women with cognitive impairment. Because cost outcomes were not tied to life expectancy, the benefits for women who were never screened and biennially screened women were the same as for the healthy population. These results would have been altered dramatically had the utilities assigned to good and poor physical states been altered to account for the perception among many primary care providers that living with dementia in a nursing home is synonymous with a lower QOL (Marwill et al., 1996). In a multi-center study examining QOL among dementia patients, a high QOL, defined by frequent activity and positive affect, was reported for a quarter of the sample (Albert et al., 1996). If a negative view of the QOL of dementia patients had been used as the utility value incorporated into the analysis, an increase in life years would have been viewed as negative and undesirable. It was assumed that utility estimates for healthy women living with breast cancer used were a more useful predictor of the outcomes of preventing breast cancer among cognitively impaired women.
The decision analysis was most sensitive to the prior probability of cancer and adjustments for the QOL ratings. Variations in recurrence costs, sensitivity, and specificity of the test had no effect on the results. To assess whether targeting screening by risk factors would yield different benefits, the range of prior probabilities was varied from .001 to .33. The most optimal choice remained screening for all of the age categories examined. In general, the preference for screening rather than not screening remained robust in a wide range of circumstances. Only when the QOL with breast cancer approached a utility rating of less than .1 did the optimal decision switch from screening to not screening. Varying costs of recurrence from $15,478 to $23,902 did not cause the cost outcome preference to switch to no screening in the no prior screening group, nor did it change the preference to screen in the regularly screened group. Using the reported variations in sensitivity and specificity also did not change the decision to screen to increase QALYs.
The decision analysis showed breast cancer screening results in increased QALYs for all ages screened. The results were most dramatic among older women who had never been screened before. Older women still benefited by regular screening after a program had been established, but the gains were not as dramatic. Cognitively impaired women benefited from screening, although not as much as their healthy counterparts. These results were robust in the face of wide variations in test sensitivity and specificity. The decision analysis indicates all older women who have never had mammography should be offered screening. This will not only result in increased QALYs for women but also should save health care dollars by avoiding more expensive recurrence costs in the future for the large numbers of older women who have never been screened. Cognitively impaired elderly women also will benefit from screening and should not be excluded from such programs based solely on their functional limitations.
Some caveats apply to the costeffectiveness portion of this analysis. Treatment costs were estimated with limited data sources that are several years old, and therefore, they may underestimate costs. Although sensitivity analysis was used to test the model assumptions with a range of values, this may not be correct for this limitation. In addition, costeffectiveness analysis assumes a societal utilitarian perspective with the objective of maximizing net health benefit for members of a population within a limited level of resources. This societal perspective is in stark contrast to the perspective of the clinician, whose goal is to maximize a patient's health status.
GERONTOLOGICAL NURSING IMPLICATIONS
The goal of preventive care in older adults is not only to decrease premature morbidity and mortality but also to maintain function and QOL. Nurses who work in primary care clinics, community agencies such as senior centers or retirement communities., and in long-term care settings can provide older women and their families educational materials about the increased risk of cancer associated with aging and the benefits of mammography screening. Early detection messages may be particularly important for older women because as women age, their chances of getting breast cancer increase. Educational interventions should be designed to overcome the barriers to screening (see the Sidebar on page 21) that have been noted in the literature (Caranasos, 1997; Marwill et al., 1996). Nurses should emphasize to patients the importance of routine screening for the early detection of breast cancer. Once is not enough. Nurses should highlight that early detection of breast cancer can increase women's options for treatment and increase survival rates.
Resources for providing information for patients include the NCI's Cancer Information Service (CIS) at (800) 4-CANCER. The Food and Drug Administration's mammography facility locator service can be accessed by calling CIS. Women should be provided information on Medicare's coverage of mammograms. Information is available through the Medicare Hotline at (800) MEDICARE.
Nurses can anticipate the following questions about mammography from older women who have never been screened:
* What is mammography? Explain that a mammogram is a special x-ray of the breast. It is a radiological procedure available to detect small cancers long before they can be felt. As the x-rays pass through the breast tissue, an actual picture of the tissue inside is obtained. This image allows the radiologist to determine whether or not cancer is present. If the woman is not having any breast problems, she will be scheduled for a screening mammogram. If she is having problems, then she should be scheduled for a diagnostic mammogram.
* Is a mammogram painful? Explain that during a mammogram, the breast is positioned on the x-ray machine and is placed between two pieces of plastic. This flattens the breast and exposes as much of the tissue as possible. The breasts will be compressed a few seconds for each x-ray. Although this will be slightly uncomfortable, it is necessary to assure an accurate examination.
* Who will perform the examination? A registered radiologic technologist performs the examination.
* How long will the examination take? Generally the examination will take 20 to 30 minutes. Explain that she should not be concerned if the radiologist requests additional views. Occasionally this is necessary for technical reasons or to view a particular area better. Sometimes an ultrasound (sonography) examination may be ordered in conjunction with a mammogram.
* Is the radiation harmful? The procedure uses an extremely low xray dose.
* How should I prepare? If the patient has had a mammogram before, she should arrange, if possible, to bring the films to her appointment for the radiologist. Because the woman must undress from the waist up for the examination, she may wish to wear a two-piece outfit. She should not apply any deodorant, powder, or cream the day of her examination because this can interfere with the mammogram by appearing on the x-ray film as calcium spots.
* How do I get the results? The patient should request to have the results telephoned, faxed, or mailed to her physician so she will get the results promptly.
If necessary, nurses should advocate for the appropriate screening of older women who may not be offered this service consistently in their usual primary care setting. As patient advocates, nurses should be leading efforts to develop breast cancer and mammography outreach and education for minority and underserved groups that address barriers to getting mammograms. Nurses are the ideal health care professionals to provide access to the latest information on risks for breast cancer, screening, diagnosis, treatment, and follow-up care. Early detection and treatment of breast cancer in older women is possible, and nurses can provide the critical knowledge to make this happen.
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VALUES USED IN THE DECISION TREE
VALUES USED IN THE DECISION TREE
COSTS OF /MAMMOGRAPHY AND RECURRENCE
SAVINGS IN LIFE EXPECTANCY FOR QUALITY-OF-LIFE-ADJUSTED MODELS