When is Cancer Care Cost-Effective? A Systematic Overview of Cost - Utility Analyses in Oncology
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DOI: 10.1093/jnci/djp472 © The Author 2010. Published by Oxford University Press. All rights reserved.
Advance Access publication on January 7, 2010. For Permissions, please e-mail: journals.permissions@oxfordjournals.org.
REVIEW
When is Cancer Care Cost-Effective? A Systematic Overview of
Cost–Utility Analyses in Oncology
Dan Greenberg, Craig Earle, Chi-Hui Fang, Adi Eldar-Lissai, Peter J. Neumann
Manuscript received April 15, 2009; revised November 17, 2009; accepted November 19, 2009.
Correspondence to: Peter J. Neumann, ScD, The Center for the Evaluation of Value and Risk in Health, Tufts Medical Center, 800 Washington St,
No. 063, Boston, MA 02111 (e-mail: pneumann@tuftsmedicalcenter.org).
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New cancer treatments pose a substantial financial burden on health-care systems, insurers, patients, and society. Cost–utility
analyses (CUAs) of cancer-related interventions have received increased attention in the medical literature and are being used
to inform reimbursement decisions in many health-care systems. We identified and reviewed 242 cancer-related CUAs pub-
lished through 2007 and included in the Tufts Medical Center Cost-Effectiveness Analysis Registry (www.cearegistry.org).
Leading cancer types studied were breast (36% of studies), colorectal (12%), and hematologic cancers (10%). Studies have
examined interventions for tertiary prevention (73% of studies), secondary prevention (19%), and primary prevention (8%). We
present league tables by disease categories that consist of a description of the intervention, its comparator, the target popula-
tion, and the incremental cost-effectiveness ratio. The median reported incremental cost-effectiveness ratios (in 2008 US $) were
$27 000 for breast cancer, $22 000 for colorectal cancer, $34 500 for prostate cancer, $32 000 for lung cancer, and $48 000 for he-
matologic cancers. The results highlight the many opportunities for efficient investment in cancer care across different cancer
types and interventions and the many investments that are inefficient. Because we found only modest improvement in the
quality of studies, we suggest that journals provide specific guidance for reporting CUA and assure that authors adhere to
guidelines for conducting and reporting economic evaluations.
J Natl Cancer Inst 2010;102:82–88
Innovative interventions in cancer prevention, diagnosis, and treat- as those targeted at patients with metastatic disease, produce rela-
ment may improve patients’ survival and quality of life, but such tively small gains in life expectancy or quality of life in relation to
improvements may come at a substantial economic cost. The cost existing treatments. Therefore, it has become crucial to under-
of cancer treatment has risen dramatically in recent years and has stand the potential costs and benefits of each intervention to deter-
created financial burdens for both patients and third-party payers mine whether they provide good value.
(1–7). In the United States, for example, the National Institutes of Economic evaluations of health-care interventions have become
Health estimated that the overall cost of cancer care in 2007 was more common in the medical and health economics literature and
$219.2 billion: direct medical care costs accounted for $89.0 billion are increasingly being used to inform reimbursement and coverage
of this total, $18.2 billion was attributed to indirect morbidity costs decisions in Australia, Canada, the United Kingdom, and other
(ie, costs of lost productivity because of illness), and the remainder European countries (14–17), although results from economic evalu-
to indirect mortality costs (ie, cost of lost productivity because of ations have not traditionally been used in the United States for these
premature death) (8). Jönsson and Wilking (9) found that the purposes (18–20). Because reimbursement and coverage decisions
direct cost for cancer care in 19 selected European countries in influence patient care, it is important for both decision makers and
2004 was approximately €57 billion (US $71 billion). Recently, a medical practitioners to be able to adequately interpret the design,
study by Yabroff et al. suggested that the value of life lost from all the results, and the conclusions of economic evaluations.
cancer deaths in the year 2000 was $960.6 billion, and this value is Cost-effectiveness analysis (CEA) provides a standard well-
projected to be $1472.5 billion in 2020 (10). This projected accepted methodological technique for judging whether a medical
increase is because of increasing life expectancy and to the expected service provides “good value for money.” The approach has
growth and aging of the US population. emerged as an important tool for evaluating the impact of a wide
The economic impact of cancer-related interventions has variety of health interventions. A cost–utility analysis (CUA) is a
received increased attention in the medical literature and in the type of CEA in which benefits are measured in terms of quality-
popular media because of the very high cost of many newer cancer adjusted life-years (QALYs) to allow comparison of the relative
drugs and treatment protocols (3,4,7,11–13). The debate has efficiency of health-care interventions across a spectrum of condi-
focused not only on the costs of treatments but also on their rela- tions. The main elements of CUAs and their application and inter-
tively modest benefits. Many new interventions in oncology, such pretation in oncology are described in greater detail elsewhere
82 Review | JNCI Vol. 102, Issue 2 | January 20, 2010(21,22). Also, we briefly describe the main elements that should be 2007), which reflect the different data collection phases in the CEA
addressed when designing, performing, and reporting findings Registry.
from a CUA in an appendix (Supplementary Material, available We arbitrarily classified journals as “high volume” (those which
online). published 10 or more CUAs over the review period, ie, the Journal
CUAs have the potential to inform coverage decisions and of Clinical Oncology, Cancer, Pharmacoeconomics, International Journal
patient care if they are of high quality and use standard recom- of Radiation Oncology Biology and Physics, and Breast Cancer Research
mended methods. Nearly a decade ago, we published an overview and Treatment) and “low volume” (those that published fewer than
of cost–utility assessments in oncology, which examined the liter- 10 CUAs, eg, Annals of Oncology, British Journal of Cancer, European
ature published before 1998 (23). In this article, we have described Journal of Cancer, Journal of the National Cancer Institute, Journal of
and synthesized published analyses of cancer-related care, exam- the American Medical Association, and others) and compared the
ined the number and quality of such analyses over time and related quality of studies in these groups of journals.
factors, and summarized the resulting standardized cost–utility The CUAs of cancer-related interventions that were included
ratios. in our review were conducted in numerous countries using dif-
ferent currencies for a period of almost 20 years. To allow compar-
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isons across countries, all non-US currencies were converted into
Methods US dollars using the appropriate foreign exchange factor for the
We analyzed data from the Tufts Medical Center Cost-Effectiveness relevant year, and all ratios were inflated to 2008 US dollars using
Analysis Registry (www.cearegistry.org), a database with detailed the Consumer Price Index. However, because changes in relative
information on 1677 CEAs published in the peer-reviewed med- and absolute treatment costs and their associated benefits can sub-
ical and economic literature through 2007. Our methodology for stantially alter cost per QALY over time, we also have presented
searching the literature and extracting information, which is the original cost-effectiveness ratios converted to US dollars with-
described in more detail elsewhere (24), involved searching out adjusting for inflation. Finally, we constructed a league table
MEDLINE by the keywords, QALYs, quality-adjusted, and cost–utility consisting of a description of the intervention, its comparator, the
analysis and then retrieving English-language publications that target population, the incremental cost-effectiveness ratio (ICER),
contained an original cost per QALY estimate. Our review in- and the study rating. A cost-effectiveness league table is a listing of
cluded all studies that pertained to prevention, screening, and health interventions ranked by their ICER presented in terms of
treatment of cancer. We excluded review, editorial, or methodo- cost per QALYs gained (25).
logical articles; CEAs that measured health effects in units other Studies that pertained to cancer were grouped into nine broad
than QALYs; and articles in languages other than English. subcategories by the type of cancer that was treated or prevented:
We used a standard data auditing form to review each CUA for breast cancer, colorectal cancer, cervical cancer, gastrointestinal
clarity, completeness, and health economic methodological quality. and hepatocellular cancers, hematologic cancers, lung cancer, mel-
The form was developed based on a variety of sources, including anoma, prostate cancer, and other cancers. Because some CUAs
the “checklist” for reporting reference-case CUAs recommended compared several interventions and included scenarios specific to
by the Panel on Cost-Effectiveness in Health and Medicine as well patient subgroups or settings, each study may have contributed
as other published guidelines (25,26). Two readers with advanced more than one ICER.
training in decision analysis and CUA independently read each We used t tests and analysis of variance to determine differ-
article and then convened for a consensus review to resolve dis- ences in study quality scores. All analyses were conducted using
crepancies. Readers received a detailed set of instructions to help SPSS 15.0 (SPSS, Inc, Chicago, IL) and SAS 9.1 software (SAS,
ensure that they interpreted items uniformly. Readers were not Cary, NC); a P value less than .05 determined statistical signifi-
masked to the identity of the authors or the journal where the cance for all comparisons. All statistical tests were two-sided.
study was published. We collected data on a wide variety of ele-
ments related to study origin, methods, and reporting of results.
For each CUA, descriptive characteristics collected included year Results
of publication, country of origin, intervention type, publication We identified 242 original cancer-related CUAs in the Tufts
journal, and study funding source. Methodological and analytic Medical Center Cost-Effectiveness Analysis Registry (www
characteristics included the study perspective, discounting of .cearegistry.org). The rate at which CUAs are published has risen
future costs and life-years, whether the economic data were col- markedly over time, and the annual average number of cancer-
lected alongside a clinical trial, and the type of sensitivity analysis related CUAs has increased from seven per year between 1988
performed (ie, univariate, multivariable, or probabilistic). We and 2001 to 25 per year between 2002 and 2007. Overall, 14% of
assigned each study a quality score based on subjective assessment the studies in the CEA Registry pertained to cancer, and this pro-
of the overall study quality on a Likert scale from 1 (low) to portion did not change substantially over time (Figure 1). The
7 (high). The quality score was calculated as the mean of the eval- most frequent cancers studied were breast cancer (36% of studies),
uations from two readers who considered the rigor of the method- colorectal cancer (12%), and hematologic cancers (10%). Studies
ology, the quality of the presentation, and the potential value of have pertained to the United States (50% of studies), followed by
the study to decision makers. Studies were summarized and tabu- the United Kingdom (11%), Canada (8%), and the Netherlands (7%)
lated in three phases (CUAs published through 1997, CUAs pub- (Table 1). Most studies have examined interventions for tertiary
lished in 1998 through 2001, and CUAs published in 2002 through prevention (ie, chemotherapy and postdiagnosis interventions; 73%),
jnci.oxfordjournals.org JNCI | Review 83300
Non-Cancer CUAs Cancer CUAs
250
200
No. of CUAs
Figure 1. Growth of the cost–utility literature
over time. The rate at which cost–utility analyses
(CUAs) are published in the medical and health 150
economic literature has risen markedly over
time. Overall, 14% of the studies in the Tufts
Medical Center Cost-Effectiveness Analysis Reg- 100
istry pertained to cancer, and this proportion did
not change substantially over time.
50
0
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20 9
19 8
19 0
81
19 9
19 3
19 3
19 6
88
90
00
19 1
92
19 6
77
19 2
85
94
19 5
96
19 7
20 1
20 2
20 3
04
20 5
20 6
07
9
9
8
8
9
8
8
9
7
8
9
9
0
0
0
0
0
19
19
19
19
19
19
19
19
19
20
20
Year
followed by secondary prevention (ie, cancer screening; 19%) not be determined. The average quality of CUAs published in “high
and primary prevention (eg, vaccination; 8%). Pharmaceuticals volume” journals (ie, J Clin Oncol, Pharmacoeconomics, Cancer, Int J
comprised the largest category of interventions that were analyzed Radiat Oncol Biol Phys) as a group was higher compared with “low
among published CUAs (53%), followed by medical procedures volume” journals as a group (mean score = 4.48 vs 4.16, differ-
(18%) and screening strategies (16%). Approximately 28% of ence = 0.32, 95% confidence interval = 0.03 to 0.61, P = .028). Among
studies were funded by industry, 42% were funded solely by non- “high volume” journals, the average paper quality was highest in J
industry sources (ie, government, foundations, and health-care or- Clin Oncol (mean score = 5.0), followed by Breast Cancer Res Treat
ganizations), and 28% did not disclose their funding source (Table (mean score = 4.7), Pharmacoeconomics (mean score = 4.5), Cancer
1). Nearly half of all studies used a lifetime time horizon, most (mean score = 4.1), and Int J Radiat Oncol Biol Phys (mean score = 3.9).
discounted both costs and QALYs, and most used univariate or Overall, the 242 analyses presented 636 ICERs (of which 120
multivariable sensitivity analyses and threshold values to interpret CUAs presented more than one ratio). A league table and descrip-
study results, presenting a correct incremental analysis. However, tion of these ratios by main cancer sites is presented in
only one-quarter of studies were taken from a societal perspective, Supplementary Table 2 (available online). The median reported
and only few analyses were conducted alongside a clinical trial cost-effectiveness ratios (in 2008 US $) were $27 000 for breast
(Table 2). cancer, $22 000 for colorectal cancer, $32 000 for lung cancer, and
In general, adherence to recommended methods for conduct- $48 000 for hematologic cancers (Table 4). When the distribution
ing and reporting CEA results (eg, applying a societal perspective, of ICERs found in our study (in 2008 US $) was examined, 8.2%
discounting both costs and QALYs, providing a clear presentation of the interventions were reported to be both cost-saving and more
of the intervention, comparator and the target population; 25,26) effective (dominant) and 52.2% were reported to have an ICER of
was high and has somewhat improved over time. During 2002– less than $50 000 per QALY gained. The ICER was greater than
2007, almost all studies clearly presented the relevant intervention, $100 000 per QALY gained in 14.0% of interventions examined,
the comparator, and the target population. The proportion of and interventions were cost-increasing and less effective (domi-
studies that correctly calculated ICERs increased from 48% before nated) in 10.8% of analyses (Figure 2). This distribution of cost-
1998 to 84% after 2001. Most studies performed a sensitivity effectiveness ratios is similar to the distribution found in other
analysis to explore uncertainties in cost-effectiveness results, and studies, which have examined measures used for preventive
the proportion of studies that presented a probabilistic sensitivity medicine and other disease areas (27–29).
analysis increased from zero during 1976–1997 to 44% during
2002–2007 (Table 3). It is also noteworthy that more than two-
thirds of the utility weights used for the analyses came from pub- Discussion
lished sources and were not directly elicited and reported as part of We critically reviewed all published cancer-related CUAs and
the described economic evaluation. determined their characteristics for more than a 20-year period.
Although the field has improved in terms of adherence to meth- The rapid increase in the number of published CUAs is perhaps
odological guidelines, we did not observe a statistically significant not surprising because payers worldwide now require data from
change on our subjective quality score (on a 1–7 scale). The mean economic evaluations to inform and support reimbursement
quality score for all studies was 4.26 and was 4.0 for studies published decisions (5,14–16,29,30). It is important, however, to understand
during 1976–1997, 4.3 for studies published during 1998–2001, and whether CUAs are improving in quality and whether researchers
4.3 for studies published during 2002–2007. The quality of industry- are following published guidelines for conducting economic evalu-
sponsored studies was similar to that of studies sponsored by other ations and reporting their results (25,26). We found, among cancer-
organizations and of studies for which the sponsorship source could related CUAs, good adherence to methodological standards in
84 Review | JNCI Vol. 102, Issue 2 | January 20, 2010Table 1. Characteristics of the cancer cost–utility analysis Table 2. Methods and quality of the cost–utility analysis
literature literature*
Number of Number of
studies Percentage studies Percentage
Characteristic (total N = 242) of studies Characteristic (total N = 242) of studies
Country of study* Clear presentation of
United States 120 49.6 The relevant intervention 236 97.5
United Kingdom 26 10.7 The comparator 233 96.3
Canada 20 8.3 The target population 236 97.5
The Netherlands 16 6.6 Time horizon
Norway 9 3.7 Lifetime 113 46.7
Australia 8 3.3 Other 90 37.2
France 8 3.3 Not stated 39 16.1
Sweden 7 2.9 Study perspective
Italy 6 2.5 Societal 56 23.1
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Other 27 11.2 Health-care payer 183 75.6
Intervention type* Not stated/could not determine 3 1.2
Pharmaceuticals 129 53.3 Discounting
Medical procedure 43 17.8 Costs only 11 4.5
Screening 38 15.7 QALYs only 4 1.7
Diagnostic 36 14.9 Both costs and QALYs 168 69.4
Surgical 32 13.2 Not needed 23 9.5
Other 24 9.9 No/could not determine 36 14.9
Prevention stage† Clinical trial based economic analysis
Primary 19 7.9 Yes 31 12.8
Secondary 46 19.0 No 209 86.4
Tertiary 177 73.1 Could not be determined 2 0.8
Study theme* Incremental analysis
Women 75 31.0 Correct 184 76.0
Public health 22 9.1 Incorrect 54 22.3
Men 22 9.1 Not reported 4 1.7
Children 3 1.2 Sensitivity analysis†
Elderly 8 3.3 Univariate or multivariable 219 90.5
None/not stated 127 52.5 Probabilistic 69 28.5
Sponsorship Other/unknown 7 2.9
Industry 52 21.5 Not performed 14 5.8
Nonindustry 101 41.7 Presentation of cost-effectiveness
Industry and nonindustry 16 6.6 acceptability curve
None 6 2.5 Yes 39 16.1
Not disclosed 67 27.7 No 203 83.9
Journal Use of threshold value to interpret
Journal of Clinical Oncology 22 9.1 study results
Cancer 18 7.4 Yes 151 62.4
Pharmacoeconomics 15 6.2 No 91 37.6
International Journal of Radiation 12 5.0 Data source for utility weights (n = 1171)
Oncology Biology and Physics Primary only 260 22.2
Breast Cancer Research and Treatment 11 4.5 Secondary only 655 55.9
Annals of Oncology 8 3.3 Both primary and secondary 50 4.3
British Journal of Cancer 8 3.3 Could not be determined/unknown 206 17.6
European Journal of Cancer 7 2.9
Journal of the National Cancer Institute 7 2.9 * QALY = quality-adjusted life-years.
Journal of the American Medical 7 2.9 † Non-exclusive.
Association
Other 127 52.5
Study quality
Mean (SD) 4.26 (1.08)
recent years clearly state the framework of the analysis (interven-
* Non-exclusive.
tion, comparator, and target population) and perform a sensitivity
† These terms are defined as follows: primary prevention = measures to
analysis to examine the robustness of the cost-effectiveness results.
prevent onset of condition (eg, vaccination); secondary prevention = Still, there is room for improvement because almost 15% of the
measures to identify and treat asymptomatic persons with risk factors or studies still did not state the time horizon of the analysis and 13%
preclinical disease (eg, screening); tertiary prevention = interventions to
limit disability after harm has occurred (eg, chemotherapy).
did not discount costs or QALYs. We found that the quality of
the studies published in journals that were more experienced
with cost-effectiveness research was substantially higher than
the field, as well as evidence that reporting practices have been those in less-experienced journals. These findings, which were
improving over time. It is encouraging that almost all studies in similar to our findings in another review (31), were not surprising
jnci.oxfordjournals.org JNCI | Review 85Table 3. Changes over time in methods used in cost–utility
analyses*
1976–1997 1998–2001 2002–2007
Characteristic (n = 42) (n = 48) (N = 152)
Clear presentation of
The relevant intervention, % 100.0 91.7 98.7
The comparator, % 95.2 91.7 98.0
The target population, % 100.0 91.7 98.7
Time horizon, %
Lifetime 57.1 45.8 44.1
Other 26.2 31.3 42.1
Not stated 16.7 22.9 13.8
Time horizon stated, % 83.3 77.1 86.2
Study perspective, % Figure 2. Distribution of published incremental cost-effectiveness ratios
Societal 21.4 29.2 22.7 (ICERs) in cancer studies. 8.2% of the cancer-related interventions were
reported to be both cost-saving and more effective (dominant), and
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Health-care payer 76.2 70.8 77.0
52.2% were reported to have an ICER of less than $50 000 per quality-
Discounting, %
adjusted life-year (QALY) gained. The ICER was greater than $100 000
Costs only 11.9 6.3 2.0 per QALY gained in 14.0% of interventions examined, and interventions
QALYs only 0.0 4.2 1.3 were cost-increasing and less effective (dominated) in 10.8% of
Both costs and QALYs 54.8 62.5 75.7 analyses.
Not needed 9.5 12.5 8.6
Any discounting, % 76.2 85.4 87.5
Clinical trial based economic 14.3 4.2 15.1
analysis, % The median cost-effectiveness ratios and the distributions of
Correct incremental 47.6 75.0 84.2 cost-effectiveness ratios in our study are similar to those found in
analysis, %
Sensitivity analysis†, %
other fields of health care (27–29). These findings are somewhat
Univariate or multivariable 83.3 93.8 91.5 surprising, given that many observers suggest that many new anti-
Probabilistic 0.0 4.2 44.1 cancer drugs do not present good value for money and thus have
Other/unknown 0.0 0.0 4.6 unfavorable cost-effectiveness ratios (5,14,15). There are three
Not performed 16.7 6.3 2.6 possible explanations for our findings. First, because our analysis
Any sensitivity analysis, % 83.3 93.8 96.1
Presentation of cost- 0.0 0.0 25.7
reflects only studies that were published through 2007, it is pos-
effectiveness sible that studies that examined the cost-effectiveness of new and
acceptability curve, % expensive biological drugs were published only in 2008 and there-
Use of threshold value to 33.3 58.3 71.7 after, beyond the time frame of our study. Indeed, economic eval-
interpret study results, %
uations of some of the most expensive drugs (eg, cetuximab,
* QALY = quality-adjusted life-years.
bevacizumab) have been published only in 2007, although they
† Non-exclusive.
were available on the market several years earlier (32,33). Economic
evaluations of other drugs (eg, sunitinib, sorafenib) were only re-
cently or not yet published. Second, the distribution of ratios for
cancer-related interventions that is described in our study may
because these journals may have acquired expertise in economic reflect the true distribution of cost-effectiveness ratios for health-
evaluations and may apply a more rigorous review process. Some of care interventions, and thus, economically unattractive interven-
these journals (eg, Pharmacoeconomics, Annals of Internal Medicine) tions may not have been brought to market (27). Finally, as in other
provide additional guidance and/or a checklist for reporting areas in medicine, the cancer-related cost-effectiveness literature
cost-effectiveness results. may have been subject to publication bias, and both selective con-
duct of cost-effectiveness studies and underreporting of unfavor-
able cost-effectiveness results may be a problem, particularly for
pharmaceutical industry–funded studies (27). Indeed, an examina-
Table 4. Number of studies and incremental cost-effectiveness tion of industry submissions to the National Institute for Clinical
ratios (ICERs) by main cancer types* Excellence (NICE) in the United Kingdom suggested that, in
No. of many cases, industry estimates were substantially lower (ie, more
studies Median ICER favorable) than the ICERs determined by NICE (5).
Type of cancer (ratio) (2008 US $/QALY) Faced with limited health-care budget and the rising costs of
Breast 86 (226) 27 000 health care, many countries are using economic analyses to inform
Hematologic 24 (37) 48 000 coverage decisions and they have frequently decided to limit
Colorectal 29 (62) 22 000 patients’ access to new and expensive drugs (5,14,15,17,34). Either
Lung 18 (61) 32 000
the absence of cost-effectiveness evidence or unfavorable cost-
Prostate 22 (42) 34 500
Gastrointestinal and hepatocellular 12 (38) 45 500 effectiveness results were often cited as the reasons for not recom-
mending the use of a drug (5,14,17). Many of these decisions,
* QALY = quality-adjusted life-years. however, were controversial, so the insurance coverage of anticancer
86 Review | JNCI Vol. 102, Issue 2 | January 20, 2010drug costs has gained attention both in the scientific literature and In summary, the large and rapidly growing cost–utility litera-
in the news media (12–14,35). ture yields opportunities to use the results from these analyses to
Acknowledging the unique circumstances of end-of-life care, better allocate scarce resources devoted to health care. The use of
several countries have adopted special mechanisms for coverage of economic evaluation to guide reimbursement decisions and med-
cancer drugs or more flexible reimbursement criteria (14,15,17). ical practice will most likely continue to increase. Decision makers
For example, a Canadian study recently suggested that cancer will have to deliberate on how other criteria (eg, values, prefer-
drugs are adopted at the highest threshold of acceptability (15). ences, patient affordability) will be incorporated in these decisions
Even more recently, following a public debate over the coverage of and whether priority should be given to anticancer interventions,
four expensive drugs for treating metastatic renal cell carcinoma specifically those targeted at patients with terminal illness.
and after a brief consultation, the National Institute for Clinical
Excellence (NICE) in the United Kingdom outlined a new ap-
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the cost-effectiveness ratios we present are not static because
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Methods for the Economic Evaluation of Health Care Programmes. 3rd ed. The sponsor helped to define the scope of this project but was not involved
New York, NY: Oxford University Press; 2005. in the study design, data collection, data analysis, interpretation of the data,
26. Gold MR, Siegel JE, Russell LB, Weinstein MC. Cost-Effectiveness in drafting the manuscript, and the decision to submit the manuscript for
Health and Medicine. New York, NY: Oxford University Press; 1996. publication.
27. Bell CM, Urbach DR, Ray JG, et al. Bias in published cost effectiveness We would like to thank the following individuals for reviewing articles for
studies: systematic review. BMJ. 2006;332(7543):699–703. the CEA Registry:
28. Cohen JT, Neumann PJ, Weinstein MC. Does preventive care save
money? Health economics and the presidential candidates. N Engl J Med. ■ Kathy Bungay, PharmD, MS
2008;358(7):661–663. ■ Michael Cangelosi, MPH, MA
29. Dalziel K, Segal L, Mortimer D. Review of Australian health economic ■ Natalie Carvalho, MPH
evaluation—245 interventions: what can we say about cost effectiveness? ■ Amit Chhabra, MD, MPH
Cost Eff Resour Alloc. 2008;6:9. ■ Maki Kamae, MD, MPH
30. Tengs TO. Cost-effectiveness versus cost-utility analysis of interventions ■ Lisa Meckley, PhD
for cancer: does adjusting for health-related quality of life really matter? ■ Chizanya Mpinja, MS
Value Health. 2004;7(1):70–78. ■ Mkaya Mwamburi, MD, PhD
■ Hansel Otero, MD
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31. Otero HJ, Rybicki FJ, Greenberg D, Neumann PJ. Twenty years of
cost-effectiveness analysis in medical imaging: are we improving? Radiology. ■ Ipek Özer Stillman, MS
2008;249(3):917–925. ■ Jenny Palmer, MS
32. Starling N, Tilden D, White J, Cunningham D. Cost-effectiveness ■ Ankur Pandya, MPH
analysis of cetuximab/irinotecan vs active/best supportive care for the ■ Corey Probst, BA
treatment of metastatic colorectal cancer patients who have failed previous ■ Lien Quach, MD, MPH
chemotherapy treatment. Br J Cancer. 2007;96(2):206–212. ■ Manu Sondhi, MD, MBA, MS
33. Tappenden P, Jones R, Paisley S, Carroll C. The cost-effectiveness of ■ DeeDee Tobias, MS
bevacizumab in the first-line treatment of metastatic colorectal cancer in ■ Zheng-Yi Zhou, MS.
England and Wales. Eur J Cancer. 2007;43(17):2487–2494. We would like to thank Dr Robin Yabroff and Dr Bryce Reeve for their
34. Shemer J. Year 2006 update of the National List of Health Services—an helpful comments on an earlier version of this manuscript.
endless process. Isr Med Assoc J. 2006;8(9):646–648.
35. O’Dowd A. Watchdog set to reject four drugs for kidney cancer on the
NHS. BMJ. 2008;337:a1262. Affiliations of authors: The Center for the Evaluation of Value and Risk in
36. Tunis SR. Why Medicare has not established criteria for coverage Health, Institute for Clinical Research and Health Policy Studies, Tufts
decisions. N Engl J Med. 2004;350(21):2196–2198. Medical Center, Boston, MA (DG, C-HF, PJN); Department of Health
Systems Management, Ben-Gurion University of the Negev, Beer-Sheva,
Funding Israel (DG); Institute for Clinical Evaluative Sciences, Sunnybrook Health
National Cancer Institute contract No. HHSN261200800748P to the Center Sciences Centre, Toronto, ON, Canada (CE); Department of Community and
for the Evaluation of Value and Risk in Health at Tufts Medical Center, Boston, Preventive Medicine, University of Rochester School of Medicine and
Massachusetts. Dentistry, Rochester, NY (AE-L).
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