A Review

Clyde B. McCo y, PhD Economic Evaluation of Breast Cancer Screening Steven G. Ullm a nn, PhD A Re vie w Da vid W. Bro wn, MSc Micha e l T. Fre nch, PhD Ma urice E. Schweitzer, PhD Kerry Anne McGea ry, PhD PURPOSE : The authors provide a review of the ec onomic evaluation literature of breast c anc er sc reening and identify important trends and gaps in the literature. OVERVIEW: Healthc are resourc es are limited and ec onomic evalua- tion plays a c ritic al role in resourc e alloc ation, healthc are polic y, and c linic al dec isions. Many ec onomic evaluations of medic al prac tic e, however, are unreliable and do not use appropriate analytic tec hniques. Three important trends were observed. First, two ec onomic evaluation methods are dominant. Sec ond, a wide range of c ost estimates exists ac ross studies. Third, a lac k of standardization exists ac ross studies with regard to basic ec onomic evaluation princ iples. These findings should be c onsidered when c onduc ting future researc h, analyzing ec onomic evaluations of breast c anc er sc reening, and developing c linic al guidelines. CLINICAL IMPLICATIONS: Conc erns about c ost c ontainment in health- c are make it nec essary for physic ians and c linic al administrators to take an ac tive role in resourc e alloc ation dec isions at the c linic al level. For instanc e, the rec ent debate on the proper age to begin annual mammography sc reening involves both resourc e alloc ation and c linic al issues. Thus, it is important for physic ians and c linic al administrators to be familiar with the ec onomic evaluation literature of breast c anc er sc reening, ec onomic evaluation methodology, and the assoc iated shortc omings of published estimates. KEY TERMS: B Breast c anc er; Ec onomic evaluation; Literature review reast cancer, the second leading cause of cancer death in women, is a significant healthcare issue and a research priority. A woman’s risk of being diagnosed with breast cancer by age 50 is 1 in 50. By age 60, the risk is 1 in 24, and by age 70 the risk of being diagnosed with the 28 disease increases to 1 in 14 (Table 1). 1 The SEER Cancer Statistics Review estimated that in 1997, more than 180,000 new cases of breast cancer occurred in the United States, accompanied by an estimated 44,000 deaths. 2 Currently, the most effective method for preventing premature mortality due to breast cancer is through the increased use of screening programs. Screening programs aim to detect breast cancer in the early stages of the disease before it progresses to later stages when treatment is less efficacious. Prior research and recent statistics demonstrate that detection of cancer when the tumor is small and localized improves the chances of survival (Table 2). 3,4 In addition to preventing premature mortality, early detection of cancer can enhance the patient’s quality of life and can lower treatment costs by taking advantage of less invasive and less expensive treatment options. As with other preventive healthcare services, the direct and indirect costs of providing screening can be expensive. For example, in 1998 the annual economic cost of screening for a mobile mammography program has been estimated at more than $381,000 for a low-volume operation (3600 women screened per year) and more than $789,000 for a high-volume service (10,000 women screened per David W. Brown, MSc, Research Associate, Health Services Research Center, University of Miami School of Medicine, Miami, Florida. Michael T. French, PhD, Research Associate Professor, Health Services Research Center, University of Miami School of Medicine, Miami, Florida. Maurice E. Schweitzer, PhD, Assistant Professor, University of Miami, Coral Gables, Florida. Kerry Anne McGeary, PhD, Research Assistant Professor, University of Miami, Coral Gables, Florida. Clyde B. McCoy, PhD, Professor, University of Miami, Coral Gables, Florida. Steven G. Ullmann, PhD, Professor and Vice Provost, University of Miami, Coral Gables, Florida. Financial support was provided through a grant from the National Cancer Institute (NCI), Number 1 R01CA/HS61252, Principal Investigator, Clyde B. McCoy, PhD. Address for correspondence: Dr. Michael T. French, Health Services Research Center, University of Miami School of Medicine, 1400 NW 10th Avenue (D-93), Suite 1105, Miami, FL 33136. CANCER PRACTICE Jan u ary/Febru ary 1 9 9 9 , Vol. 7 , No. 1 © American Cancer Society 1065-4704/99/$10.50/28 28–33 29 Economic Evaluation / Brown et al Table 1 . A Wom an ’s Lifetim e Risk of Bein g Diagn osed with Breast Can cer, by Age Age ( yr) Risk 30 1 in 2 5 2 5 40 1 in 2 1 7 50 1 in 5 0 60 1 in 2 4 70 1 in 1 4 80 1 in 1 0 Sourc e: National Canc er Institute. 1 year). 5 (These and all subsequent cost estimates are reported in 1997 dollars.) Recent estimates for a fixed-site mammography program are not available. However, bec ause a fixed-site program must rent or lease building space, it is reasonable to assume that the annual costs of screening in a fixed-site program would exceed those of the mobile program. Healthcare resources are limited, however, and policymakers are faced with difficult resource allocation decisions. This is particularly true with regard to breast cancer, for which the estimated annual direct expenditures on treatment alone were $6.6 billion in 1990 (approximately $9.7 billion in 1997 dollars, cetaris paribus). 6 As the constraints on healthcare resources increase, decisions on how to allocate available resources must be made. Economic evaluation research, which measures and assigns value to costs and outcomes, aids in this process. 7 The extent to which results from this research are reliable depends on the data available, the ec onomic evaluation method used, and how rigorously the method is applied. Prior research has demonstrated that most cost-effectiveness and cost-benefit analyses in the medical literature do not adhere to basic economic evaluation principles. This has contributed to a wide range of results found across breast cancer screening studies. 8,9 Such disparities hinder an already difficult decision-making process. Noting these disparities, this report reviews the existing literature on the economic evaluation of breast cancer screening programs and identifies important trends and gaps that may influence subsequent analyses and policy decisions based on published results. Six economic evaluation methods, existing literature, shortcomings of current economic evaluation research and opportunities for future evaluation of breast cancer screening programs, and the impact of current findings and shortcomings on clinical decision making are discussed. Economic Evaluation Methods There are six types of economic evaluations: cost analysis; cost-minimization analysis; cost-effectiveness analysis; cost-utility analysis; cost-offset analysis; and cost-benefit analysis. Of these, c ost analyses and c ost-effec tiveness analyses dominate the breast cancer screening literature. Cost analysis is a partial evaluation method, the goal of which is to identify costs associated with a disease, illness, or intervention. Cost analysis is limited, however, because it does not estimate, assign value to, and compare outcomes (tumors detec ted) assoc iated with the identified c osts (screening costs). Cost minimization, the easiest of the full economic evaluation methods to conduct, is used to select the lowest cost intervention from two or more comparable strategies. The primary limitation of cost minimization is the requirement that all strategies achieve common and equal outcomes, such as mammograms completed or tumors detected. Cost-effectiveness analysis evaluates the incremental cost and outcome of two or more possible interventions through a calculated cost-effectiveness ratio. However, the cost-effectiveness ratio can only be used when comparing interventions that have homogenous outcomes (cost per life-year saved due to screening or cost per cancer detected by mammography) and thus is limited to comparison within diseases and within treatments. In reality, however, outcomes across individuals are rarely homogenous. Individuals rec eive different treatments, respond differently to screening or to treatment, and will often view their quality of life differently. To account for such differences, costutility analysis extends cost-effectiveness analysis by allowing the researcher to make outcome comparisons between distinct treatment protocols and diseases through the use of measures such as quality-adjusted life-years. Table 2 . Five-Year Relative Su rvival Rates for Wom en Diagn osed with Breast Can cer Between 1 9 8 6 an d 1 9 9 3 Localized* Region al† Distan t‡ Un staged§ Women of all rac es 9 6 .8 % 7 5 .9 % 2 0 .6 % 5 4 .9 % White women 9 7 .4 % 7 7 .4 % 2 1 .2 % 5 6 .4 % Afric an Americ an women 8 9 .6 % 6 1 .2 % 1 6 .8 % 4 7 .1 % * Loc alized: invasive neoplasm c onfined entirely to the organ of origin. † Regional: neoplasm that has extended beyond the limits of the organ of origin direc tly into the surrounding organs or tissues, into regional lymph nodes, or both direc t extension and regional lymph node involvement. ‡ Distant: neoplasm that has spread to parts of the body remote from the primary tumor either by direc t extension or by disc ontinuous metastasis. § Unstaged: information not suffic ient to assign a stage. Sourc e: SEER Canc er Statistic s Review. 2 30 CANCER PRACTICE Jan u ary/Febru ary 1 9 9 9 , Vol. 7 , No. 1 Cost-offset analysis is a partial cost-benefit analysis in which program costs are estimated and compared with the avoided healthc are c osts derived from a treatment or screening program. This method avoids the challenge of a full account of benefits such as avoided morbidity and mortality costs. Cost-benefit analysis, the most comprehensive economic evaluation method, assigns a dollar value to all costs and outcomes, tangible and intangible. The valuation of all costs and outcomes, especially pain and suffering, is an inherently difficult task, and, thus, the availability of data is often a limitation to cost-benefit analysis. For decisionmaking purposes, cost-benefit analysis is clearly the most desirable evaluation method because it provides a single metric (dollars) for all costs and benefits of an intervention. For an in-depth discussion of the six economic evaluation methods introduced here, the authors refer the reader to reports by Drummond et al, 7 Gold et al, 10 Tolley et al, 11 and Johannesson. 12 Review of the Literature Thirty-three articles related to the economic evaluation of breast cancer were identified using MEDLINE and the bibliographies of artic les loc ated through MEDLINE as sources of literature. The list included 22 empirical studies5,13–34 and 11 papers or texts discussing economic evaluation methodology and its application to breast cancer screening. 7,8–12,35–40 Because the authors were primarily interested in economic evaluation methods and the application of those methods, the focus of the literature review was on empirical studies and those studies that discuss economic evaluation directly. The empiric al studies inc lude artic les from 1 9 7 9 through 1997 that evaluate both breast cancer treatment and breast cancer screening programs. Empirical breast cancer treatment articles are included based on the notion that early detection of breast cancer lowers total treatment costs relative to the treatment costs at later stages of detection. Thus, articles investigating breast cancer treatment were selected only if there were identifiable implications for screening programs. Although the detection of breast cancer is an intermediate outcome of screening, the authors have also included measures of the treatment cost per detection along with other cost-effectiveness measures. ent estimates across economic evaluations of breast cancer screening. This finding is consistent with prior research, which found estimates of the screening cost per life-year saved to range from $3,400 to $83,830. 9 The wide variation in cost estimates can be attributed to the age distribution of the target population and the prevalenc e of first-time screening. Table 3 reports estimates of the cost per mammogram obtained from the c ost analysis papers, while Table 4 presents estimates from other selected economic evaluation studies. Estimates in both tables have been adjusted to 1997 US dollars using the Medical Care Services Consumer Price Index. 41 Third, consistent with the findings of Udvarheli et al, 8 the authors observe that the majority of the economic evaluations do not adhere to basic economic evaluation principles. For example, only 5 of the 23 empirical papers adjusted estimates for the differential timing of costs and benefits, while 13 did not report the year in which costs and outcomes were estimated. Also, nine economic evaluations used medical care charge data rather than actual costs due to data limitations. On four occasions it was not possible to determine whether costs or charges were being represented in the final estimates because either no statement was made or costs and charges were combined among the estimates. Charges are not equal to costs but are reflective of prices for medical services set by hospitals and other providers. Estimates based on charge data typically overestimate the actual cost of a service. (For a detailed description of the differences between costs and charges and the implications for economic evaluation and policy, see the report by Finkler. 42 ) Of the nine economic evaluations using charge data, only two mention that costs and charges are not equivalent. Finally, while every economic evaluation should include a well-defined description of the costs and outcomes included in the analysis, this review revealed 15 studies that failed to meet this guideline. Only five studies indicated that a measure of indirect costs was included. A detailed identification of the full costs (ie, direct, indirect, tangible, and intangible) is necessary for subsequent analysis and interpretation of the results. On those occasions when costs were presented, the discussion was often general and in- Table 3 . Selected Cost An alysis Stu dies Results The review of the empirical economic evaluations of breast cancer screening revealed three significant findings. First, the ec onomic evaluation method implemented is nearly uniform across studies. Of the 23 empirical studies reviewed, five are cost-analysis studies, and the remaining 18 are c ost-effec tiveness analyses. Four studies identify themselves as cost-benefit analyses, but they fall short of meeting the necessary requirements to be classified as such and are more correctly classified as cost-effective analyses. One of the 18 cost-effectiveness analysis studies also provides an application of cost-utility analysis. Second, the authors report the significant estimates observed in the empirical papers to highlight the many differ- Fin din gs Stu dy Co st pe r m a m m o gra m ( wo m e n scre e ne d) * 10† 14 Sic kles et al ‡ $137 15 Bird § Coursen 23 ‡ 5 Sc hweitzer et al ‡ 15† $98 20† 30† 40† 50† $78 $59 $49 $43 — — — $58 $47 $44 — — — $74 — — $126 $104 $93 $83 $79 $75 * All estimates have been adjusted for inflationary effec ts to 1 9 9 7 US dollars using the Medic al Care Servic es Consumer Pric e Index. † Mammograms per day. ‡ Mobile mammography unit. § Fixed-site mammography servic e. 41 Economic Evaluation / Brown et al 31 Table 4 . Selected Econ om ic Evalu ation Stu dies* Stu dy Fin din gs Butler et al 2 8 ,2 9 † Results show treatment c ost per detec tion equal $ 5 2 2 6 at stage 0 ( in situ) , $ 5 8 6 9 at stage I, $ 1 2 ,4 8 6 at stage II, $ 1 6 ,5 5 2 at stage III, and $ 1 9 ,5 3 1 at stage IV. Legoretta et al 32 Results show treatment c ost per detec tion equal $ 2 2 ,2 7 2 at stage 0 ( in situ) , $ 2 7 ,3 3 9 at stage I, $ 3 3 ,9 3 8 at stage II, $ 7 1 ,8 8 3 at stage III, and $ 5 8 ,3 3 1 at stage IV. Janjan et al 27 Treatment c ost for patients diagnosed at stage I is $ 3 3 ,4 1 9 and at a loc ally advanc ed stage is $ 8 9 ,8 3 7 . 22 Gerard et al † The total c ost per c anc er detec ted during year 1 of the sc reening c yc le was $ 1 8 ,7 3 0 , and during years 2 and 3 the total c ost per c anc er detec ted was $ 1 1 ,6 6 3 ( based on a detec tion rate of 8 /1 0 0 0 ) . Fireman et al 34 Attributable long-term c ost was $ 4 7 ,9 3 4 for patient diagnosed at loc al stage, $ 6 1 ,3 4 9 at regional stage, and $ 4 9 ,2 4 7 at distant stage. The attributable long-term c ost was $ 4 9 ,7 9 1 for all stages. Sc hweitzer et al 5 The sc reening c ost per detec tion is $ 1 4 ,7 3 8 based on 1 0 mammograms per day, and $ 1 2 ,2 1 4 ; $ 1 0 ,9 5 3 ; $ 9 6 9 0 ; $ 9 2 4 9 ; and $ 8 8 3 2 based on 1 5 , 2 0 , 3 0 , 4 0 , and 5 0 mammograms per day, respec tively ( based on a detec tion rate of 8 .5 4 /1 0 0 0 ) . Eddy et al 19 The disc ounted marginal c ost per year of life expec tanc y for adding a mammogram to annual breast physic al examination is $ 1 5 0 ,9 6 0 ( 5 % disc ount rate) . Zavertnik et al 26 Sc reening saves $ 2 1 in treatment c ost per mammogram performed. Sc reening saves $ 4 2 2 2 in treatment c ost per c anc er patient diagnosed and treated. Mandelblatt et al 33 The c ost per life-year gained for the establishment of a free-standing breast c anc er sc reening program in the emergenc y room of a public hospital is $ 4 0 6 ,0 6 7 . The c ost per life-year gained for the addition of breast c anc er sc reening servic e to an existing emergenc y room c anc er sc reening program is $ 2 6 ,7 6 4 . * All estimates have been adjusted for inflationary effec ts to 1 9 9 7 US dollars using the Medic al Care Servic es Consumer Pric e Index. 41 † Cost information was originally provided in 1 9 8 8 Australian dollars. These estimates were c onverted to 1 9 8 8 US dollars using the 1 9 8 8 exc hange rate of AU$ 1 = US$ 0 .7 8 4 1 . Estimates were then adjusted to 1 9 9 7 dollars. complete, leaving the reader to speculate about the cost components. Discussion To make informed resource allocation decisions, policy-makers, administrators, and practitioners need accurate, current, and reliable estimates of the costs and outcomes of breast cancer screening. It is evident from this review that economic evaluation research may not be meeting these needs for at least two reasons: 1) current economic evaluation research lacks standardization, making comparisons across studies difficult; and 2) the information provided is limited by the economic evaluation methods that are used. The authors reviewed 23 empirical studies presenting a variety of results based on diverse data sets across a wide range of conditions. While the range of estimates itself is not necessarily problematic, the inability to compare estimates across studies systematically does present a problem. Polic y-makers, who use published results as a primary source of information, are confronted with a similar task of sorting through the wide range of empirical results and through the myriad of assumptions and details specific to each research study. Ideally, every economic evaluation would follow a standard set of criteria that facilitates the interpretation and comparison of estimates, regardless of the economic evaluation method used. Because economic evaluation research is not standardized, methodological choices can bias estimates. These choices may then go undetected because methodological or analytical information is not reported. 43 To resolve the problem of standardization, Russell et al44 recommend that studies include a reference case, defined by a standard set of methods and assumptions. The reference case defines the costs and outcomes that are included, as well as the manner in which they are assigned value, and provides a standard form for reporting the results. 10,44 By providing a standard, the reference case facilitates subsequent analyses and comparisons across studies. The literature also is limited by its focus on two evaluation methods, namely, cost analysis and cost-effectiveness analysis. Interest in the cost-effectiveness of screening is widespread. However, cost-effectiveness analyses can be limiting, and decisions should not always be based on costeffectiveness analysis alone. Cost-effectiveness measures only allow comparison between programs that produce similar outcomes, and significant issues, such as equity and quality of life, are not incorporated. In addition, cost-effectiveness analysis, as well as cost analysis, cost-minimization analysis, and cost-utility analysis, does not assign a value to outcomes. Despite the debate associated with the reliability of assigning dollar values to health outcomes, such values are necessary to understand the economic benefits of screening and to make objective resource allocation decisions across programs with different outcomes. To this point, breast cancer research has qualitatively identified the range of outcomes or benefits of breast cancer screening, but a dollar value of those outcomes remains an unresolved issue. Cost-benefit analysis, the most desirable and comprehensive of the six economic evaluation methods, aims to address many outcome valuation problems. However, because the valuation of outcomes is difficult, cost-benefit analysis is a more complex and time-consuming method. We acknowledge that data limitations are a prominent rea- 32 CANCER PRACTICE Jan u ary/Febru ary 1 9 9 9 , Vol. 7 , No. 1 son for the lack of cost-benefit analyses. Nonetheless, it is a concern that rigorous cost-benefit analyses have not been applied to breast cancer screening programs. Because the possible contributions and potential of cost-benefit analysis applied to breast cancer screening have not been realized, numerous opportunities exist for using the technique in future economic evaluation research. 2. Clinical Implications 4. These findings have important implications for physicians and clinical administrators. Concerns for cost containment in healthcare are now a major issue both in general policy making and in clinical decision making. 45 For instance, the recent debate on the appropriate age to begin routine annual mammography screening is as much a resource allocation issue as it is a clinical issue. Clinical guidelines are developed to be not only efficacious, but costeffective as well. Similarly, physicians and clinical administrators are often interested in stage-specific and long-term costs to assess the cost-effectiveness of preventive services, such as screening and breast cancer treatments, and the impact of these services and treatments on their patients. 34 This review demonstrates that when these assessments are based on published estimates, careful attention should be given to the specific analytic and methodological assumptions made and to the data used. For example, let us assume that the effectiveness of screening programs is measured in terms of detection rates (programs A and B have incremental cost-effectiveness measures of $7,000 and $12,000 per cancer detected). Despite each estimate’s face value, there may be valid reasons to prefer program B to program A based on false-positive costs (biopsy costs, surgeons’ fees, needle aspirations, additional mammograms, and consultations), anxiety costs, and equity issues that may not appear in the cost-per-cancer-detected measure. 46 While the physician’s primary role is to provide the best possible care for his or her patient, physicians inc reasingly partic ipate in benefits administration and healthcare policy decisions. Healthcare resources are limited, and the scarcity of these resources must be accounted for in the clinical decision-making process. 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