Blood First Edition Paper, prepublished online February 5, 2015; DOI 10.1182/blood-2014-07-592832
I.
Title page
Value of Innovation in Hematologic Malignancies: A Systematic Review of Published CostEffectiveness Analyses
Short title: Value of Innovation in Hematologic Malignancies
Authors: Saret, Cayla J;1 Winn, Aaron;2 Shah, Gunjan;3 Parsons, Susan K;3 Lin, Pei-Jung;1
Cohen, Joshua T;1 Neumann, Peter J1
Affiliations: 1Center for the Evaluation of Value and Risk in Health, Institute for Clinical
Research and Health Policy Studies, Tufts Medical Center, Boston, MA
2
Department of Health Policy and Management, Gillings School of Global Public Health,
University of North Carolina at Chapel Hill, Chapel Hill, NC
3
Center for Health Solutions, Institute for Clinical Research and Health Policy Studies, Boston,
MA
Corresponding author: Peter J. Neumann, Director, Center for the Evaluation of Value and Risk
in Health, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center;
Professor, Tufts University School of Medicine; 800 Washington Street, Box 63, Boston MA,
20111; phone: 617-636-2335, fax: 617-636-8628, e-mail: [email protected].
Scientific category: LYMPHOID NEOPLASIA; MYELOID NEOPLASIA
1
Copyright © 2015 American Society of Hematology
II.
Abstract
We analyzed cost-effectiveness studies related to hematologic malignancies from the Tufts CostEffectiveness Analysis Registry (www.cearegistry.org), focusing on studies of innovative
therapies. Studies that met inclusion criteria were categorized by four cancer types (chronic
myeloid leukemia (CML), chronic lymphocytic leukemia (CLL), non-Hodgkin’s lymphoma
(NHL), and multiple myeloma (MM)) and nine treatment agents (α interferon, alemtuzumab,
bendamustine, bortezomib, dasatinib, imatinib, lenalidomide, rituximab alone or in combination,
and thalidomide). We examined study characteristics and stratified cost-effectiveness ratios by
type of cancer, treatment, funder, and year of study publication. Twenty-nine studies published
1996-2012 (including 44 cost-effectiveness ratios) met inclusion criteria, twenty-two (76%) of
which were industry-funded. Most ratios fell below $50,000/QALY (73%) and $100,000/QALY
(86%). Industry-funded studies (n=22) reported a lower median ratio ($26,000/QALY) than
others (n=7) ($33,000/QALY), although the difference was not statistically significant. Published
data suggest innovative treatments for hematologic malignancies may provide reasonable value
for money.
III.
Introduction
During the past fifteen years, treatment of hematologic malignancies changed radically.
In 1997, the FDA approved rituximab, now widely used to treat hematologic malignancies
including NHL. Later, tyrosine kinase inhibitors (TKIs) were introduced to treat CML. TKIs
exceeded survival benefit expectations1; however, they also have a notably high cost.
The first TKI, imatinib, was introduced in 2001 at roughly $30,000/year of treatment.
Others, introduced more recently, cost roughly $100,000/year or more.2 These prices have
prompted significant outcry, with some questioning whether these medications provide good
value for money.2 The use of bortezomib, a proteasome inhibitor, and novel anti-angiogenesis
agent lenalidomide have improved MM outcomes. These and other innovative treatments have
increased patients’ life expectancy.1, 3
Cost-effectiveness analysis (CEA) is a technique to assess interventions’ benefit relative
to costs. Cost-utility analysis (CUA) is a type of CEA that measures health benefits in qualityadjusted life-years (QALYs). This generic measure facilitates comparison of health care
interventions addressing varied conditions. CUA has been used extensively in oncology.4
We identified innovative treatments for hematologic malignancies and performed a
systematic review of peer-reviewed CUAs. It is important to understand the current literature
regarding these treatments, which have undergone dramatic changes in cost and effectiveness.
We synthesized analyses of care for hematologic malignancies, examined the number, quality,
and related characteristics of analyses, and summarized cost-utility ratios by treatment and
disease types. To our knowledge, this review is the first of its kind.
3
IV.
Methods
We analyzed data from the Tufts CEA Registry (www.cearegistry.org), a database of
over 9800 cost-effectiveness ratios published in the peer-reviewed medical and economic
literature through 2012. The Registry’s development and inclusion criteria are described
elsewhere.5 Briefly, English-language publications identified by a MEDLINE search that contain
an original cost per QALY estimate are retrieved. Two trained researchers evaluate articles for
inclusion and extract article information. Disagreement is resolved by consensus.
Our review included studies that addressed treatment for hematologic malignancies. We
excluded review, editorial, or methodological articles, CEAs that did not measure health effects
in QALYs, and non-English-language articles. We included therapeutic agents the FDA
approved since 1997 and excluded hematopoietic stem cell transplant, symptom management,
and supportive care. The studies were manually checked for duplication. No duplicates were
found.
We collected data regarding study origin, methods, and reporting of results. For each
CUA, descriptive characteristics collected included publication year, country of origin,
intervention type, publication journal, funding source, and methodological and analytic
characteristics including study perspective, discounting of future costs and life-years, whether
economic data were collected alongside a clinical trial, and type of sensitivity analysis performed
(i.e., univariate, multivariable, or probabilistic). Each study was assigned a subjective quality
score on a Likert scale from 1 (low) to 7 (high) based on rigor of methodology, presentation, and
value to decision-makers. We conducted a sub-group analysis of ICER distributions including
only high quality scores with a quality score of 5 or higher and compared this analysis with the
distribution in all studies.
To facilitate comparison of standardized outcomes, non-United States (US) currencies
were converted into US dollars using the appropriate foreign exchange factor for the relevant
year, and ratios were inflated to 2012 dollars using the general Consumer Price Index (CPI).
We grouped studies into four subcategories by cancer type: CLL, CML, MM, and NHL,
and nine treatment agents: α interferon, alemtuzumab, bendamustine, bortezomib, dasatinib,
imatinib, lenolidomide, rituximab alone or in combination, and thalidomide. Some studies
contributed multiple ICERs, because they compared several interventions or included scenarios
for multiple settings. For analysis, we assigned each ratio a statistical weight of 1 divided by the
number of ratios contributed by that study.
V.
Results and discussion
Table 1 describes characteristics of the 29 studies (published 1996-2012) analyzed.
Journals that published the most studies were Leukemia & Lymphoma (5 studies),
Pharmacoeconomics (4), Value in Health (4), and European Journal of Haematology (3). Nine
studies were conducted from a US perspective, followed by the United Kingdom (UK) (6),
Norway (3), Sweden (3), and France (2). Most studies (18) were conducted from a health care
payer perspective. Seven were conducted from a societal perspective (as recommended by the
US Panel on Cost-Effectiveness and Health in Medicine6, 7). The pharmaceutical industry funded
22 studies (76%). Six studies collected economic data alongside a clinical trial. The mean quality
rating was 4.85 (±0.61) (the mean rating overall in the Registry was 4.45 (±1.03)). The mean
quality rating was analyzed using a two-tailed t-test and did not differ significantly between
industry and non-industry-funded studies.
5
The studies reported 44 cost-effectiveness ratios (some studies report multiple ratios).
Most ratios addressed interventions for NHL (41%) or CML (30%). Most ratios pertained to
treatments for rituximab (43%), α interferon (18%), or imatinib (16%). The most common
intervention-disease combination was rituximab alone or in combination for NHL (36%).
Across cancers, the median reported ratio was highest for CML ($55,000/QALY) and
lowest for NHL ($21,500/QALY). Median reported ratios fluctuated across time periods:
$35,000/QALY (1996-2002), $52,000/QALY (2003-2006), and $22,000/QALY (2007-2012).
The median ratio reported by industry-funded studies ($26,000/QALY) was lower (more
favorable) than the median reported by non-industry-funded studies ($33,000/QALY). These
differences were analyzed using a chi-square test and results for trends across time periods were
confirmed with a logistics regression; the differences were not statistically significant.
Most ratios fell below (were more favorable than) the $50,000/QALY (73%) or
$100,000/QALY (86%) threshold (Figure 1). These thresholds are commonly used in the US as
benchmarks for cost-effectiveness. Although their origins are unclear, evidence suggests that
thresholds at these levels or higher may be appropriate depending on the context. 8 (A higher
threshold would expand the range of analyses that are considered cost-effective, which would
mean that our analysis is conservative and more of the CEAs included should be considered costeffective). Four ratios, one industry-funded, exceeded $100,000/QALY, including two pertaining
to treatment of MM with bortezomib,9, 10 one pertaining to treatment of CML with α interferon,11
and one pertaining to treatment of CML with imatinib. In two cases, both industry-funded,
(alemtuzumab to treat CLL and bortezomib to treat MM), the treatment improved health and
reduced costs.
The distribution of ICERs by value in the high quality (quality score >= 5) subsample
was similar to the distribution in all studies, yielding findings that were not significantly different
than those in the overall analysis. For example, when comparing ICERs from industry- and nonindustry-funded-studies in the high quality subsample, there was not a statistically significant
different in the number of ICERs with values greater than over equal to $100,000/QALY.
Our review suggests many new treatments for hematologic malignancies may confer
reasonable value for money. Despite the high costs of new drugs, the cost-effectiveness ratio
distributions are comparable to those for cancers overall and other health care fields.4, 12 For
example, a 2010 study found the majority of published cost-effectiveness ratios for cancer
interventions were below $50,000/QALY.4 As in similar reviews, our results may reflect
publication bias.12 In particular, they may reflect selective conduct of studies and underreporting
of unfavorable findings, particularly by industry-funded studies, which were a majority of
reviewed studies.12
Treatments for NHL may appear more cost-effective than treatment for CML, because
innovative agents such as rituximab for NHL were introduced in earlier years than TKIs for
CML, which may have affected the manufacturers’ pricing strategies. In addition, unlike
rituximab, the TKI market has experienced a flurry of agents approved for the same target.
Churning in this market based on loss of efficacy, concern about gene mutation, differences in
dosing administration (e.g. daily vs twice daily), and side effect profiles may results in increasing
costs for CML treatment as compared with NHL.
We believe that this kind of global overview of the literature will be useful to provide a
broad perspective for clinicians on how their individual focus relates to associated interventions
and malignancies. In the context of recent discussions about the cost-effectiveness of various
7
interventions in the popular media, it may be particularly useful for clinicians to understand the
literature in the field as a whole. We appreciate that individual clinicians may concentrate on
specific malignancies and therapies, and we have therefore included data that we hope will be
useful in these circumstances regarding the proportion of studies and median ratios for specific
diseases and interventions.
Faced with rising costs, many payers use economic analyses to inform coverage
decisions; frequently, they limit access to expensive new drugs.13 For example, after reviewing
the cost-effectiveness evidence, the UK’s National Institute for Health and Clinical Excellence
recently approved nilotinib, a second generation TKI, but only after the manufacturer discounted
it.14
Our study has several limitations. First, our review only includes CEAs in the Tufts CEA
Registry and therefore only those that quantified health benefits in QALYs. Other evaluations
may have used other measures, such as life-years. Second, our review was limited to Englishlanguage peer-reviewed publications indexed in MEDLINE. We did not include health
technology assessment reports. Third, we did not evaluate the analyses’ clinical or modeling
assumptions, nor assess the quality of data collected in studies conducted alongside clinical
trials. Alternate approaches to quality assessment have been provided in the literature, such as
the Consolidated Health Economic Evaluation Reporting Standards (CHEERS).15 Finally, the
ratios depend on cost and benefit assumptions that may have changed since publication. For
example, Novartis increased imatinib’s price from about $30,000 per year of treatment in 2001 to
roughly three times that amount as of 2012.2 A 2001 CUA would evaluate imatinib as more costeffective than it is at its higher 2012 price.
In summary, many new treatments for hematologic malignancies appear to be costeffective based on the published literature. Industry-funded studies reported a lower (more
favorable) median ratio than non-industry funded studies. However, both groups reported
medians below $50,000/QALY. Although prices are high, the treatments confer substantial
health benefits as measured by QALYs. However, decision-makers consider factors other than
cost-effectiveness (e.g., health impact, values, preferences, overall budget impact, affordability
for patients) and determine how best to weight these factors according to the situation at
hand.16,17 Decision-makers can use cost-effectiveness as one tool when determining appropriate
coverage for these and other drugs.
VI.
Acknowledgements
This study was funded by internal sources at the Center for the Evaluation for Value and Risk in
Health at the Institute for Clinical Research and Health Policy Studies at Tufts Medical Center in
Boston. Research reported in this publication was also supported by the National Cancer Institute
of the National Institutes of Health under award number T32 CA009429 (S.K.P., G.S.) The
content is solely the responsibility of the authors and does not necessarily represent the official
views of the National Institutes of Health.
VII.
Authorship contributions and disclosure of conflicts of interest
Contribution: A.W. and C.J.S. designed the research and collected and analyzed the data; G.S.
collected the data and provided clinical input; S.K.P. designed the research and provided clinical
input; P.J.L. designed the research; J.T.C. and P.J.N. directed and designed the research; and all
authors contributed to the analysis and interpretation of the results and wrote the paper.
9
Conflict-of-interest disclosure: The Center for the Evaluation of Value and Risk in Health
receives funding from government, private foundation, and industry sources. The authors have
no further conflicts of interest to disclose.
Correspondence: Peter J. Neumann, Director, Center for the Evaluation of Value and Risk in
Health, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center;
Professor, Tufts University School of Medicine; e-mail: [email protected].
VIII. References
1. Haznedaroglu IC. Current management of chronic myeloid leukemia with tyrosine kinase
inhibitors. Turk J Haematol 2013;30(3):247-255.
2. The price of drugs for chronic myeloid leukemia (CML) is a reflection of the unsustainable
prices of cancer drugs: from the perspective of a large group of CML experts. Blood
2013;121(22):4439-4442.
3. Bianchi G, Ghobrial IM. Molecular mechanisms of effectiveness of novel therapies in
multiple myeloma. Leuk Lymphoma 2013;54(2):229-241.
4. Greenberg D, Earle C, Fang CH, Eldar-Lissai A, Neumann PJ. When is cancer care costeffective? A systematic overview of cost-utility analyses in oncology. J Natl Cancer Inst
2010;102(2):82-88.
5. Neumann PJ, Greenberg D, Olchanski NV, Stone PW, Rosen AB. Growth and quality of
the cost-utility literature, 1976-2001. Value Health 2005;8(1):3-9.
6. Siegel JE, Weinstein MC, Russell LB, Gold MR. Recommendations for reporting costeffectiveness analyses. Panel on Cost-Effectiveness in Health and Medicine. JAMA
1996;276(16):1339-1341.
7. Weinstein MC, Siegel JE, Gold MR, Kamlet MS, Russell LB. Recommendations of the
Panel on Cost-effectiveness in Health and Medicine. JAMA 1996;276(15):1253-1258.
8. Neumann PJ, Cohen JT, Weinstein MC. Updating cost-effectiveness--the curious resilience
of the $50,000-per-QALY threshold. N Engl J Med 2014;371(9):796-797.
9. Hornberger J, Rickert J, Dhawan R, Liwing J, Aschan J, Lothgren M. The costeffectiveness of bortezomib in relapsed/refractory multiple myeloma: Swedish perspective.
Eur J Haematol 2010;85(6):484-491.
10. Doss S, Hay N, Sutcliffe F. NICE guidance on bortezomib and thalidomide for first-line
treatment of multiple myeloma. Lancet Oncol 2011;12(9):837-838.
11. Liberato NL, Quaglini S, Barosi G. Cost-effectiveness of interferon alfa in chronic
myelogenous leukemia. J Clin Oncol 1997;15(7):2673-2682.
12. Bell CM, Urbach DR, Ray JG et al. Bias in published cost effectiveness studies: systematic
review. BMJ 2006;332(7543):699-703.
13. Mason AR, Drummond MF. Public funding of new cancer drugs: Is NICE getting nastier?
Eur J Cancer 2009;45(7):1188-1192.
14. National Institute for Health and Clinical Excellence (NICE). Dasatinib, nilotinib and
standard-dose imatinib for the first-line treatment of chronic myeloid leukaemia. London
(UK): National Institute for Health and Clinical Excellence (NICE), 2012
15. Husereau D, Drummond M, Petrou S et al. Consolidated Health Economic Evaluation
Reporting Standards (CHEERS)--explanation and elaboration: a report of the ISPOR
Health Economic Evaluation Publication Guidelines Good Reporting Practices Task Force.
Value Health 2013;16(2):231-250.
16. Drummond MF, Sculpher MJ, Torrance GW, O'Brien BJ, Stoddart GL. Basic types of
economic evaluation. Methods for the Economic Evaluation of Health Care Programmes.
Third ed. Oxford: Oxford University Press; 2005:7-26.
17. Gold MR, Russell LB, Siegel JE, Weinsten MC. Cost-Effectiveness Analysis as a Guide to
Resource Allocation in Health: Roles and Limitations. Cost-Effectiveness in Health and
Medicine. New York: Oxford University Press; 1996:3-24.
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IX.
Tables
Table 1. Study characteristics
Total Studies
Journal
Leuk Lymphoma
Pharmacoeconomics
Value Health
Eur J Haematol
Acta Oncol
Cancer
Ann Intern Med
Ann Oncol
Br J Cancer
Other
Country
United States
United Kingdom
Norway
Sweden
France
Canada
Finland
Other
Perspective
Health Care Payer
Societal
Industry Funded
Economic Data Collected Alongside Clinical
Trial
Quality Rating, Mean (Range, SD)
# of
articles
29
%
100
5
4
4
3
2
2
1
1
1
6
17%
14%
14%
10%
7%
7%
3%
3%
3%
21%
9
6
3
3
2
1
1
4
31%
21%
10%
10%
7%
3%
3%
14%
18
7
22
6
62%
24%
76
21
4.85 (3.5-6.5, 0.61)
X.
Figure legends
Figure 1. Ratios by incremental cost-effectiveness ratio ($/QALY) and funding source.
Note: Ratios were inflated to 2012 US dollars using the general Consumer Price Index (CPI).
13