The Use of Incremental Cost-Effectiveness Ratio Thresholds in Health Technology Assessment Decisions

10/27/15
Issue
Affiliation

Merena Nanavaty: MKTXS, Market Access Solutions, LLC, Raritan, NJ. 

Satyin Kaura: Celgene Corporation, Summit, NJ. 

Mkaya Mwamburi: Tufts University School of Medicine, Boston, MA; MKTXS, Market Access Solutions, LLC, Raritan, NJ. 

John Proach: MKTXS, Market Access Solutions, LLC, Raritan, NJ. 

Abner Nyandege: MKTXS, Market Access Solutions, LLC, Raritan, NJ. 

Zeba Khan: Celgene Corporation, Summit, NJ. 

Correspondence

Merena Nanavaty, MKTXS, Market Access Solutions, LLC, 575 Route 28, Suite 205, Raritan, NJ 08869, Phone: 908-864-4090, Fax: 908-450-1526, Email: mnanavaty@mktxs.com

Disclosures

Merena Nanavaty, Mkaya Mwamburi, Anagha Gogate, John Proach and Abner Nyandege work for Market Access Solutions, LLC, and received consulting fees from Celgene Corporation towards the conduct and publication of this review. Satyin Kaura and Zeba M. Khan are employees of Celgene Corporation.

Key Words

Abstract: The incremental cost-effectiveness ratio (ICER) is used to determine the cost-effectiveness of new health care interventions. A literature review was conducted to determine the ICER thresholds used by different countries in their healthcare reimbursement decisions, the extent to which they are used, and how they may have changed over time to reflect inflation and medical progress. Treatments that received contrasting approval decisions from different health technology assessment (HTA) bodies were identified. Countries use both static and dynamic thresholds for approval processes, and static ICER thresholds are not regularly updated. Between 2012 and 2015, eight therapies received different reimbursement approval decisions in different countries. ICERs established for type 2 diabetes (T2DM) and non-small-cell lung cancer (NSCLC) were compared and were found to vary significantly. The author’s findings suggest that ICER thresholds may be outdated and may not account for innovation in technology, inflation, and increased research and development costs. Furthermore, it may be more appropriate for different ICER thresholds to be set for therapies for different disease states to account for differences in value assessment.

Citation: Journal of Clinical Pathways. 2015;1(1):29–36. 

Received August 10, 2015; accepted August 31, 2015.
__________________________________________________________________________________________________________

Cost-effectiveness analysis is an economic evaluation tool applied to assess the costs and outcomes of different health care interventions in order to arrive at an overall valuation for those options.1 One method for analyzing the cost-effectiveness of a health care intervention is to estimate the incremental cost-effectiveness ratio (ICER), which is typically expressed as the additional cost associated with a given a unit of measure—for example, quality-adjusted life-year (QALY)—to quantify the improvement in outcome associated with that cost.2 ICERs are used to assign a quantifiable value to the healthcare intervention; an intervention with a low ICER is considered more favorable for drug reimbursement decisions by healthcare programs.3

Health technology assessment (HTA) bodies in many countries have set an ICER threshold, above which an intervention is considered to be not cost-effective, in order to aid their respective processes of decision-making.2 Some of these ICER threshold were established as long ago as 1982.4 Over the past few decades, there has been extraordinary growth and progress in medical technologies and drug discovery. Examples include antiretroviral therapies, biologics, and immune-modulators that have enhanced quality of life and improved survival in numerous therapeutic areas.5–8 However, these more effective therapies tend to be associated with higher costs.9 Additionally, inflation has led to higher healthcare costs as well as an increase in healthcare expenditures other than treatment costs.10 In light of these developments, the present applicability of ICER thresholds established 20–30 years ago are greatly debated. It has not been systematically evaluated whether or how ICER thresholds have evolved over time to respond to the changing landscape of healthcare options.

Another concern raised by researchers is that, when used as the only or main decision-making tool, ICER thresholds fail to account for aspects of non-monetary-based value of the product, such as the extent to which the treatment is addressing previously unmet needs, the severity of disease treated by the treatment, and the population size to be impacted by the new treatment.11 The variability in ICERs for therapies for different disease states has not, to date, been systematically evaluated.

Different countries evaluate new technologies using different decision-making tools and ICER thresholds, leading to varying approval decisions.12 A better understanding of how ICER thresholds have been set and used in the past decades is needed to contribute to the ongoing debate on whether ICER thresholds and their current role in assessing new drugs and technologies are appropriate.

The purpose of this study was to evaluate the landscape of ICER thresholds and to gain insight on the past and current use of ICER thresholds in HTA processes for making reimbursement decisions for new drugs and technologies. A systematic literature review was conducted in order to document the ICER thresholds set in different countries, to determine changes that may have occurred since inception of the initial ICER thresholds, assess whether and how reimbursement decisions by countries with different ICER thresholds may have differed, and to determine the discrepancies between ICERs of treatments for different disease states. The future recommendations of other researchers relating to the use of ICER thresholds in healthcare decision-making are also discussed.

METHODS

Current Landscape of ICER Thresholds

First, we conducted a targeted literature review using the PubMed database to determine: (1) the initially established ICER thresholds in countries that use them as part of their HTA assessment process; and (2) whether current ICER thresholds differ from originally established ICER thresholds. Search terms included “ICER threshold” and its variations (Table 1). The titles of studies published in the English language, between January 1970 and January 2015, were reviewed with no geographic limitations. Additionally, we conducted a grey literature search using Google Scholar with similar search terms. Subsequently, a secondary manual search of bibliographies of the included studies was conducted. Studies that provided information on the above criteria were selected and added to the list of included studies. Finally, key information was collated using descriptive data from the studies included.

strategy for targeted literature

The yield was 1857 studies, of which 44 titles and abstracts qualified for full text review. The grey literature search did not yield any additional studies. Of the 44 full texts that were reviewed, 10 were excluded because they did not provide data on any of the following: (1) the established ICER thresholds; (2) updates or changes to previously established ICER thresholds; or (3) recommendations or expectations provided by researchers relating to the use of ICER thresholds in the healthcare decision-making process. In addition, two studies were obtained from the secondary manual search of bibliographies of the included studies. The 36 studies included in the analysis were published between 1992 and 2015 and provided data about Australia, Belgium, Canada, Ireland, the Netherlands, New Zealand, Poland, Spain, Sweden, the United Kingdom, and the United States.

Differences in Coverage Decisions in Countries with Different ICER Thresholds

Second, we reviewed HTA decisions to determine whether products received different coverage decisions from different countries (Canada and the United Kingdom) and whether this was due to differences in ICER thresholds. A search was conducted on the official websites of the national HTA bodies in Canada (Canadian Agency for Drugs and Technologies in Health (CADTH)) and in the UK (The National Institute for Health and Care Excellence (NICE)). Products that were rejected by either HTA body between 2012 and 2015 were identified.

Comparing ICERs Across Therapeutic Areas

Third, we compared ICERs of drugs across two disease states, chosen because of their varying attributes, to sample the variability in ICERs. Type 2 diabetes mellitus (T2DM) and non-small cell lung cancer (NSCLC) were selected for the informal analysis due to the differences in the levels of unmet need, disease severity, quality of life, etc. Two systematic literature reviews were conducted to identify empirical cost-effectiveness and cost-utility studies for T2DM and for NSCLC treatments. The search terms used were (1) disease-related (“Type 2 diabetes mellitus” and “Nonsmall cell lung cancer”, with variations); and (2) study type-related (“Cost-effectiveness analysis”, “Cost-utility analysis”, with variations). The search was limited to studies published between January 2012 and January 2015 reporting ICERs in T2DM and NSCLC. The search strategy is summarized in Table 2

strategy for systematic literature

A total of 288 studies related to ICERs for T2DM therapies were identified, of which 20 titles and abstracts qualified for full text review. Of the 20 full texts that were reviewed, 2 were excluded. Data were extracted from 18 studies. A total of 91 studies related to ICERs for NSCLC therapies were identified, of which 24 titles and abstracts qualified for full-text review. Of the 24 full texts that we reviewed, 7 were excluded. ICERs were extracted from the 17 identified studies in the currency in which they were originally reported.

Extracted ICERs were converted into 2015 USD ($) and 2015 GBP (£) using the Campbell and Cochrane Economics Methods Group (CCEMG) tool recommended by Cochrane.13,14 We calculated the median (range) ICER for treatments of each therapy area in order to compare them.For nine studies,18–26 cost conversions were not possible since they reported ICERs in currencies other than their own (Euros); the CCEMG tool uses original “country” and “year” during conversion and does not incorporate “currency” into the conversion.

RESULTS

Current Landscape of ICER Thresholds

Data regarding ICER thresholds used to make reimbursement decisions by HTA bodies internationally were extracted from 36 studies. Belgium, Poland, and Sweden do not use any formal ICER thresholds in their decision-making processes.15,16 In countries that use ICER thresholds for HTA decisions, thresholds vary widely (Table 3). Converted into USD, ICER thresholds ranged from $13,000 (New Zealand) to $104,000 (Canada). In Australia, Canada, the Netherlands, ranges are used rather than a defined threshold.

ICER Thresholds

The ICER thresholds in the UK and the US have not undergone changes since their inception, and thus can be considered “static.” New Zealand, the Netherlands, Australia, and Canada use dynamic ICER threshold values that vary periodically and are determined from past resource allocation decisions, but these ICER threshold are not officially established.2

Differences in Coverage Decisions by Countries with Differing ICER Thresholds

The rationale of reviewing reimbursement approval decisions by CADTH and NICE was to understand the disparities in patient access across countries resulting from the dissimilar processes and nature of tools used in decision-making. To determine the extent to which differences between countries’ ICER thresholds are associated with differences in reimbursement coverage decisions, we evaluated HTA reports to identify products that received differential reimbursement decisions from different countries.19 HTA reports were reviewed related to reimbursement approval decisions by CADTH and NICE. Between the years 2012 and 2015, eight unique products were identified as receiving differential reimbursement approval decisions from CADTH and NICE (Table 4). The products can be classified into three categories: (i) products rejected by NICE and approved by CADTH (trastuzumab emtansine, everolimus, pemetrexed, bosutinib); (ii) products approved by NICE after initial rejection, and approved by CADTH (abiraterone, vemurafenib); (iii) products rejected by NICE and approved by CADTH after initial rejection (crizotinib); and (iv) products rejected by NICE and CADTH (aflibercept).

Reimbursement decisions

NICE’s approval process relies heavily on their static ICER threshold range, while CADTH relies on a dynamic ICER threshold but also takes other factors into consideration. One exception with NICE is an initiative to evaluate life-extending technologies through an elaborate set of “end-of-life” criteria, in which therapies with ICERs above £30,000 will be considered.17 As a result, some treatments were rejected (and, for some, later approved) by NICE but were approved by CADTH. 

Comparing ICERs Across Therapeutic Areas

We compared ICERs of drugs across two disease states—T2DM and NSCLC—chosen because of their varying attributes, to sample the variability in ICERs. The individual ICERs reported by the 35 included studies (18 for T2DM and 17 for NSCLC) are listed in Supplemental Table 1 and Supplemental Table 2. The median (range) of the adjusted ICERs revealed that the ICERs of treatments for T2DM ($19,535 per QALY ($1,114–70,061 per QALY) or £13,284 per QALY (£778–47,642 per QALY)) was approximately two-fold greater than that of treatments for NSCLC ($54,020 per QALY ($1,001–464,681 per QALY) or £36,734 per QALY (£681–315,983 per QALY)).

ICERs for Type 2 Diabetes

supplemental table

supplemental table

ICERs for NSCLC

supplemental table

DISCUSSION

The literature contains little evidence that the ICER thresholds being used have been modified since their inception. The $50,000 per QALY threshold currently used in the US was established in 1982 based on the cost-effectiveness of hemodialysis for the treatment of end-stage renal disease.4,16 The £20,000-30,000 per QALY threshold currently used in the UK was established in 1999 and has no reported basis.27,28 The absence of a justification for the arbitrarily set thresholds likely stemmed from the lack of policy related decision-making context or precedent at that time. Currently, adjustments to account for inflation, innovation, increasing cost of research and development, satisfying unmet needs, or for severe diseases, may not be adequately addressed. Our findings were comparable to those by Claxton and associates,11 who used a similar targeted literature review approach, although they focused on NICE and implications for the National Health Service. They found that many institutions set “hard thresholds” and referred to literature that conveys the dissatisfaction with a “hard threshold” that does not reflect the following considerations: the benefits of a new treatment; the argument for using multiple thresholds; and the need for an update of ICER thresholds based on reasons such as increased NHS budget, inflation, advancements in technology, and congruency with societal willingness-to-pay.11

Researchers have published their concerns with the stagnant and unique ICER threshold value being used. There is concern that the static thresholds become outdated because they fail to account for a number of factors including the evolving medical landscape in terms of both diagnosis and management. In the past three decades, treatments for diseases that had no cure have now been developed and are currently in use. New technologies have been discovered that improve life expectancy for cancers or quality of life for viral infections, immune disorders, and rare diseases significantly. As an example, in 2011 two new technologies were discovered that offered better cure rates for Hepatitis C, a disease that affects approximately 150 million people.29,30 Several other new technologies under investigation have the potential for significantly improved quality of life and longer survival.31 With increased and earlier access to screening and healthcare, more patients can be diagnosed and treated at an earlier point in disease progression, leading to better health and economic outcomes.

The experience in using the thresholds over the past decades could appropriately inform decision makers to revisit the initially established thresholds since ICER thresholds play a significant role among other factors in the decision-making process in many countries. Some researchers recommended that the ICER thresholds be reevaluated regularly to account for inflation, per capita-income, disease burden, innovation in diagnosis and treatment, and patient preferences;10,27 be increased to reflect societal willingness-to-pay, increased healthcare funding, and inflation;10,32–35 be raised to $200,000 or more per QALY;10,36,37 or be set $109,000–297,000 per QALY.38 Others recommend that ICER thresholds be lowered and not raised;  these recommendations are based on theoretical concepts such as opportunity costs and value of precedents of previously funded technologies.39,40

Although some ICER thresholds can be considered “static” (UK, US), some countries use a “dynamic” threshold (Australia, Canada, Netherlands, and New Zealand) that varies periodically. In such cases, ICER thresholds are not the sole decision-making criteria in the HTA process. Another evolution that has occurred since the inception of ICER thresholds is the development of real-world data. Various countries use real-world data to a different extent and fashion.41 HTA processes are becoming more dynamic and embracing different types of assessments that help inform real-world value of new technologies.42

Our findings regarding varying reimbursement approval decisions by different HTA bodies result from differences in the extent to which ICER thresholds are considered within that HTA process. Some researchers recommended that the ICER thresholds incorporate other important criteria, rather than a rigid implementation of only one single, quantitative criterion during resource allocation decisions.2,32 Others recommend considering the use of multiple thresholds since using a single ceiling target is not the most efficient way to allocate the overall healthcare budget of a country and is challenging to defend across varying indications10,32 or adopting a variable threshold approach to cost-effectiveness analysis.43 Others suggest integrating public and societal preferences into decision-making.15,33

Different approval decisions may arise from importance in economic parameters versus clinical/scientific implications or societal impact of the new technologies. Examples of clinical/scientific implications or societal impact of the new technologies include considerations for innovation, addressing unmet needs, and/or having a significant impact on life expectancy or quality of life. This is observable when we consider that the median and range of ICERs for T2DM technologies were lower than those for NSCLC technologies. Our findings suggest that treatments for a disease with a lower level of unmet need and severity (eg, T2DM) tend to have lower ICERs compared to a more severe disease with a higher level of unmet need (eg, NSCLC). However, only an informal comparison was made between median ICERs for these two disease states; our results should thus be interpreted with caution. The difference in the median ICERs may also be credited to vast differences in cost of manufacturing, research and development, and population characteristics, among other factors. These differences suggest that technologies associated with varying levels of unmet needs, severities, etc. may need to be evaluated against different thresholds.

CONCLUSIONS

To the best of our knowledge, this is the first summary of the landscape of ICER thresholds and provides insights into previously reported recommendations while also providing case studies of approval decisions across two HTA bodies. The targeted literature review approach inherently introduces a level of bias; however, our research questions were structured to directly address previously raised issues and to be the least susceptible to bias. Future research should consider evaluating the impact of alternative methodologies on the healthcare decision-making process.

The future recommendations and expectations elucidated by previous researchers relating to the use of ICER thresholds in healthcare decision-making vary significantly. These recommendations and expectations set forth by researchers mainly point to the need for an update to the ICER threshold based on increase in budget, inflation, advancements in technology, and congruency with societal willingness-to-pay; as well as the establishment of multiple thresholds for varying situations. Studies suggest that ICERs are subjective to specific contexts at a specific time point and conditions; hence, they are inherently dynamic in nature, implying that ICER thresholds need to be updated regularly due to changing settings.2,27,44 Based on these findings, ICER thresholds appear to have a place within the HTA decision-making process but should be regularly updated to account for budgetary changes, inflation, advancements in technologies, and payer and societal willingness-to-pay. Additionally, decision-makers should reflect on the evidence that points toward the inclusion of factors other than cost-effectiveness, such as innovation, unmet need, disease severity, and target population size, when determining the “value” of a healthcare intervention. 

-----

References

1.    Robinson R. Cost-effectiveness analysis. BMJ. 1993;307(6907):793-795.

2.    Cleemput I, Neyt M, Thiry N, De Laet C, Leys M. Using threshold values for cost per quality-adjusted life-year gained in healthcare decisions. Int J Technol Assess Health Care. 2011;27(1):71-76. Published ahead of print on January 25, 2011. 

3.    Drummond MF, Sculpher MJ, Torrance GW, O’Brien BJ, Stoddart GL. Methods for the Economic Evaluation of Health Care Programmes, 3rd Edition. New York, NY: Oxford University Press; 2005.

4.    Rocchi A, Menon D, Verma S, Miller E. The role of economic evidence in Canadian oncology reimbursement decision‐making: to lambda and beyond. Value Health. 2008;11(4):771-783.

5.    Alvarez-Mon M, Miravitlles M, Morera J, Callol L, Alvarez-Sala JL. Treatment with the immunomodulator AM3 improves the health-related quality of life of patients with COPD. CHEST. 2005;127(4):1212-1218.

6.    Calvet X, Gallardo O, Coronas R, et al. Remission on thiopurinic immunomodulators normalizes quality of life and psychological status in patients with Crohn’s disease. Inflamm Bowel Dis. 2006;12(8):692-696.

7.    The History of Cancer. The American Cancer Society Website. www.cancer.org/cancer/cancerbasics/thehistoryofcancer/index?sitearea.Updated June 12, 2014; accessed September 12, 2015.

8.    HIV Surveillance Supplemental Report. Monitoring Selected National HIV Prevention and Care Objectives by Using HIV Surveillance Data - United States and 6 Dependent Areas - 2012. Centers for Disease Control and Prevention Website. 2012;19(3). www.cdc.gov/hiv/library/reports/surveillance/index.html. Accessed September 12, 2015. 

9.    PriceRX. Medi-Span’s Master Drug Database. https://pricerx.medispan.com/ Accessed August 5, 2015. 

10.    Ubel PA, Hirth RA, Chernew ME, Fendrick AM. What is the price of life and why doesn’t it increase at the rate of inflation? Arch Intern Med. 2003;163(14):1637-1641. http://archinte.jamanetwork.com/article.aspx?articleid=215852. Accessed September 12, 2015. 

11.    Claxton K, Martin S, Soares M, et al. Systematic review of the literature on the cost-effectiveness threshold: Appendix 1. In: Methods for the estimation of the National Institute for Health and Care Excellence cost-effectiveness threshold. Southampton, UK: NIHR Journals Library; 2015.

12.    Context Matters, Inc. Global Variability in HTA Decisions Poses Challenges for Innovative Biopharmaceutical Research and Development. PhRMA Website. www.phrma.org/sites/default/files/pdf/context-matters-global.pdf. Published 2014; accessed September 12, 2015. 

13.    Shemilt I, Thomas J, Morciano M. A web-based tool for adjusting costs to a specific target currency and price year. Evidence & Policy: A Journal of Research, Debate and Practice. 2010;6(1):51-59.

14.    Higgins JPT, Green S. Cochrane Handbook for Systematic Reviews Of Interventions Version 5.1.0. The Cochrane Collaboration, 2011. Updated March 2011; accessed September 12, 2015. 

15.    Pauwels K, Huys I, Casteels M, De Nys K, Simoens S. Market access of cancer drugs in European countries: improving resource allocation. Target Oncol. 2014;9(2):95-110.

16.    Laufer F. Thresholds in cost-effectiveness analysis--more of the story. Value Health. 2005;8(1):86-87.

17.    The National institute for Health and Clinical Excellence (NICE). Appraising life-extending, end of life treatments. NICE Website. www.nice.org.uk/guidance/gid-tag387/resources/appraising-life-extending-end-of-life-treatments-paper2. Revised July 2009; accessed September 14, 2015. 

18.    Grzeszczak W, Czupryniak L, Kolasa K, Sciborski C, Lomon ID, McEwan P. The cost-effectiveness of saxagliptin versus NPH insulin when used in combination with other oral antidiabetes agents in the treatment of type 2 diabetes mellitus in Poland. Diabetes Technol Ther. 2012;14(1):65-73.

19.    van Haalen HG, Pompen M, Bergenheim K, McEwan P, Townsend R, Roudaut M. Cost effectiveness of adding dapagliflozin to insulin for the treatment of type 2 diabetes mellitus in the Netherlands. Clin Drug Investig. 2014;34(2):135-146.

20.    Tzanetakos C, Melidonis A, Verras C, Kourlaba G, Maniadakis N. Cost-effectiveness analysis of liraglutide versus sitagliptin or exenatide in patients with inadequately controlled Type 2 diabetes on oral antidiabetic drugs in Greece. BMC Health Serv Res. 2014;14:419.

21.    Viriato D, Calado F, Gruenberger JB, et al. Cost-effectiveness of metformin plus vildagliptin compared with metformin plus sulphonylurea for the treatment of patients with type 2 diabetes mellitus: a Portuguese healthcare system perspective. J Med Econ. 2014;17(7):499-507.

22.    Fonseca T, Clegg J, Caputo G, Norrbacka K, Dilla T, Alvarez M. The cost-effectiveness of exenatide once weekly compared with exenatide twice daily and insulin glargine for the treatment of patients with type two diabetes and body mass index >30 kg/m(2) in Spain. J Med Econ. 2013;16(7):926-938.

23.    Erhardt W, Bergenheim K, Duprat-Lomon I, McEwan P. Cost effectiveness of saxagliptin and metformin versus sulfonylurea and metformin in the treatment of type 2 diabetes mellitus in Germany: a Cardiff diabetes model analysis. Clin Drug Investig. 2012;32(3):189-202.

24.    Søgaard R, Fischer BM, Mortensen J, Rasmussen TR, Lassen U. The optimality of different strategies for supplemental staging of non-small-cell lung cancer: a health economic decision analysis. Value Health. 2013;16(1):57-65.

25.    Ramaekers BL, Joore MA, Lueza B, et al. Cost effectiveness of modified fractionation radiotherapy versus conventional radiotherapy for unresected non-small-cell lung cancer patients. J Thorac Oncol. 2013;8(10):1295-1307.

26.    Matter-Walstra K, Joerger M, Kühnel U, Szucs T, Pestalozzi B, Schwenkglenks M. Cost-effectiveness of maintenance pemetrexed in patients with advanced nonsquamous-cell lung cancer from the perspective of the Swiss health care system. Value Health. 2012;15(1):65-71.

27.    McCabe C, Claxton K, Culyer AJ. The NICE cost-effectiveness threshold: what it is and what that means. Pharmacoeconomics. 2008;26(9):733-744.

28.    Appleby J, Devlin N, Parkin D. NICE’s cost effectiveness threshold. BMJ. 2007;335(7616):358-359. www.ncbi.nlm.nih.gov/pmc/articles/PMC1952475/. Accessed September 14, 2015. 

29.    FDA approves Victrelis for Hepatitis C. US Food and Drug Administration Website. www.fda.gov. Published May 13, 2011; accessed September 14, 2015. 

30.    Holtzman D. Traveler’s Health, Chapter 3: Infectious Diseases Related to Travel. Centers for Disease Control and Prevention Website. wwwnc.cdc.gov/travel/yellowbook/2014/chapter-3-infectious-diseases-related-to-travel/hepatitis-c. Published July 10, 2015; accessed September 14, 2015.

31.    U.S. National Institutes of Health. Clinical Trials Website. Accessed September 14, 2015.

32.    Eichler HG, Kong SX, Gerth WC, Mavros P, Jönsson B. Use of cost-effectiveness analysis in health-care resource allocation decision-making: how are cost-effectiveness thresholds expected to emerge? Value Health. 2004;7(5):518-528.

33.    Buxton MJ. Economic evaluation and decision making in the UK. Pharmacoeconomics. 2006;24(11):1133-1142.

34.    Simoens S. How to Assess the Value of Medicines? Front Pharmacol. 2010;1:115.

35.    Towse A. Should NICE’s threshold range for cost per QALY be raised? Yes. BMJ. 2009;338:b181. http://www.bmj.com/content/338/bmj.b181. Accessed September 13, 2015. 

36.    Birch S, Gafni A. The biggest bang for the buck or bigger bucks for the bang: the fallacy of the cost-effectiveness threshold. J Health Serv Res Policy. 2006;11(1):46-51.

37.    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. http://www.nejm.org/doi/full/10.1056/NEJMp1405158. Updated August 28, 2014; accessed September 13, 2015. 

38.    Braithwaite RS, Meltzer DO, King JT Jr, Leslie D, Roberts MS. What does the value of modern medicine say about the $50,000 per quality-adjusted life-year decision rule? Med Care. 2008;46(4):349-356.

39.    Paulden M, Claxton K. Budget allocation and the revealed social rate of time preference for health. Health Econ. 2012;21(5):612-618.

40.    Raftery J. Should NICE’s threshold range for cost per QALY be raised? No. BMJ. 2009;338:b185. http://www.bmj.com/content/338/bmj.b185. Accessed on September 13, 2015. 

41.    O’Donnell JC, Pham SV, Pashos CL, Miller DW, Smith MD. Health technology assessment: lessons learned from around the world--an overview. Value Health. 2009;12 Suppl 2:S1-5. www.ispor.org/htaspecialissue/odonnell.pdf. Accessed September 13, 2015. 

42.    Drummond MF, Schwartz JS, Jönsson B, et al. Key principles for the improved conduct of health technology assessments for resource allocation decisions. Int J Technol Assess Health Care. 2008;24(3):244-258; discussion 362-248.

43.    Bridges JF, Onukwugha E, Mullins CD. Healthcare rationing by proxy: cost-effectiveness analysis and the misuse of the $50,000 threshold in the US. Pharmacoeconomics. 2010;28(3):175-184.

44.    Kingsbury K. The Value of a Human Life: $129,000. Time Magazine Website. http://content.time.com/time/health/article/0,8599,1808049,00.html. Published May 20, 2008; accessed September 14, 2015. 

45.    George B, Harris A, Mitchell A. Cost-effectiveness analysis and the consistency of decision making: evidence from pharmaceutical reimbursement in australia (1991 to 1996). Pharmacoeconomics. 2001;19(11):1103-1109.

46.    Laupacis A, Feeny D, Detsky AS, Tugwell PX. How attractive does a new technology have to be to warrant adoption and utilization? Tentative guidelines for using clinical and economic evaluations. CMAJ. 1992;146(4):473-481.

47.    Barry M, Tilson L. Recent developments in pricing and reimbursement of medicines in Ireland. Expert Rev Pharmacoecon Outcomes Res. 2007;7(6):605-611.

48.    Franken M, le Polain M, Cleemput I, Koopmanschap M. Similarities and differences between five European drug reimbursement systems. Int J Technol Assess Health Care. 2012;28(4):349-357.

49.    Franken M, Koopmanschap M, Steenhoek A. Health economic evaluations in reimbursement decision making in the Netherlands: time to take it seriously? [Article in German.] Z Evid Fortbild Qual Gesundhwes. 2014;108(7):383-389.

50.    Metcalfe S, Rodgers A, Werner R, Schousboe C. PHARMAC has no cost-effectiveness threshold. N Z Med J. 2012;125(1350):99-101. www.nzma.org.nz/journal/read-the-journal/all-issues/2010-2019/2012/vol-125-no-1350/letter-metcalfe. Accessed September 14, 2015. 

51.    Simoens S. Health Economic Assessment: Cost-Effectiveness Thresholds and Other Decision Criteria. Int J Environ Res Public Health. 2010;7(4):1835-1840.

52.    Rodríguez Barrios JM, Pérez Alcántara F, Crespo Palomo C, González García P, Antón De Las Heras E, Brosa Riestra M. The use of cost per life year gained as a measurement of cost-effectiveness in Spain: a systematic review of recent publications. Eur J Health Econ. 2012;13(6):723-740.

53.    Rodriguez JM, Paz S, Lizan L, Gonzalez P. The Use Of Quality-Adjusted Life-Years in the Economic Evaluation of Health Technologies In Spain: A Review of the 1990-2009 Literature. Value Health. 2011;14(4):458-464.

54.    Appleby J, Devlin N, Parkin D, Buxton M, Chalkidou K. Searching for cost effectiveness thresholds in the NHS. Health Policy. 2009;91(3):239-245.

55.    Devlin N, Appleby J, Parkin D. Patients’ views of explicit rationing: what are the implications for health service decision-making? J Health Serv Res Policy. 2003;8(3):183-186.

56.    Devlin N, Parkin D. Does NICE have a cost-effectiveness threshold and what other factors influence its decisions? A binary choice analysis. Health Econ. 2004;13(5):437-452.

57.    Claxton K, Sculpher M, Palmer S, Culyer AJ. Causes for concern: is NICE failing to uphold its responsibilities to all NHS patients? Health Econ. 2015;24(1):1-7. Published ahead of print December 8, 2014. 

58.    Culyer A, McCabe C, Briggs A, et al. Searching for a threshold, not setting one: the role of the National Institute for Health and Clinical Excellence. J Health Serv Res Policy. 2007;12(1):56-58.

59.    Gafni A, Birch S. Incremental cost-effectiveness ratios (ICERs): the silence of the lambda. Soc Sci Med. 2006;62(9):2091-2100. Published ahead of print December 1, 2005. 

60.    Rutten F. Health technology assessment and policy from the economic perspective. Int J Technol Assess Health Care. 2004;20(1):67-70.

61.    Shah K, Praet C, Devlin N, Sussex J, Appleby J, Parkin D. Is the aim of the English health care system to maximize QALYs? J Health Serv Res Policy. 2012;17(3):157-163. Published ahead of print July 5, 2012. 

62.    Stevens AJ, Longson C. At the center of health care policy making: the use of health technology assessment at NICE. Med Decis Making. 2013;33(3):320-324.

63.    Walker S, Palmer S, Sculpher M. The role of NICE technology appraisal in NHS rationing. Br Med Bull. 2007;81-82:51-64. Published ahead of print April 4, 2007. 

64.    Jönsson B. Changing health environment: the challenge to demonstrate cost-effectiveness of new compounds. Pharmacoeconomics. 2004;22 Suppl 4:5-10.

65.    Bae YH, Mullins CD. Do value thresholds for oncology drugs differ from nononcology drugs? J Manag Care Spec Pharm. 2014;20(11):1086-1092.

66.    Pan-Canadian Oncology Drug Review (pCODR) Expert Review Committee (pERC) Final Recommendation - Zytiga. Canadian Agency for Drugs and Technologies in Health (CADTH) Website. www.cadth.ca/sites/default/files/pcodr/pcodr-zytiga-mcrpc-fn-rec.pdf. Published October 2013; accessed September 15, 2015. 

67.    Raftery J. Abaritarone for metastatic castration resistant prostate cancer—whose victory? The BMJ Website. http://blogs.bmj.com/bmj/2012/05/29/james-raftery-abaritarone-for-metastatic-castration-resistant-prostate-cancer-whose-victory/. Published May 29, 2012; accessed September 15, 2015.

68.    The National Institute for Health and Care Excellence (NICE) Technology Appraisal Guidance. Abiraterone for castration-resistant metastatic prostate cancer previously treated with a docetaxel-containing regimen. NICE Website. www.nice.org.uk/guidance/ta259. Published June 2012; accessed September 15, 2015.

69.    Pan-Canadian Oncology Drug Review (pCODR) Expert Review Committee (pERC) Final Recommendation - Zaltrap. CADTH Website. www.cadth.ca/sites/default/files/pcodr/pcodr-zaltrap-mcrc-fn-rec.pdf. Published August 2014; accessed September 15, 2015.

70.    The National Institute for Health and Care Excellence (NICE) Technology Appraisal Guidance. Aflibercept in combination with irinotecan and fluorouracil-based therapy for treating metastatic colorectal cancer that has progressed following prior oxaliplatin-based chemotherapy. NICE Website. www.nice.org.uk/guidance/ta307. Published March 2014; accessed September 15, 2015.

71.    Pan-Canadian Oncology Drug Review (pCODR) Expert Review Committee (pERC) Final Recommendation - Bosulif. CADTH Website. www.cadth.ca/sites/default/files/pcodr/pcodr_bosutinib_bosulif_cml_fn_rec.pdf. Published April 2015; accessed September 15, 2015.

72.    The National Institute for Health and Care Excellence (NICE) Technology Appraisal Guidance. Bosutinib for previously treated chronic myeloid leukaemia. NICE Website. www.nice.org.uk/guidance/ta299. Published November 2013; accessed September 15, 2015.

73.    Pan-Canadian Oncology Drug Review (pCODR) Expert Review Committee (pERC) Final Recommendation - Xalkori. CADTH Website. www.cadth.ca/sites/default/files/pcodr/pcodr-xalkorinsclc-fn-rec.pdf. Published September 2012; accessed September 15, 2015.

74.    Xalkori. pCODR Expert Review Committee Final Recommendation. Pan-Canadian Oncology Drug Review. May 2013; https://www.cadth.ca/sites/default/files/pcodr/pcodr-xalkoriresub-fn-rec.pdf. Accessed August 4, 2015.

75.    The National Institute for Health and Care Excellence (NICE) Technology Appraisal Guidance. Crizotinib for previously treated non-small-cell lung cancer associated with an anaplastic lymphoma kinase fusion gene. NICE Website. www.nice.org.uk/guidance/ta296. Published September 2013; accessed September 15, 2015.

76.    Pan-Canadian Oncology Drug Review (pCODR) Expert Review Committee (pERC) Final Recommendation - Afinitor. CADTH Website. www.cadth.ca/sites/default/files/pcodr/pcodr-afinitorab-fn-rec.pdf. Published March 2013; accessed September 15, 2015.

77.    The National Institute for Health and Care Excellence (NICE) Technology Appraisal Guidance. Everolimus in combination with exemestane for treating advanced HER2-negative hormone-receptor-positive breast cancer after endocrine therapy. NICE Website. www.nice.org.uk/guidance/ta295. Published August 2013; accessed September 15, 2015.

78.    Pan-Canadian Oncology Drug Review (pCODR) Expert Review Committee (pERC) Final Recommendation - Alimta. CADTH Website. www.cadth.ca/sites/default/files/pcodr/pcodr-alimta-ns-nsclc-fn-rec.pdf. Published November 2013, accessed September 15, 2015.

79.    The National Institute for Health and Care Excellence (NICE) Technology Appraisal Guidance. Pemetrexed maintenance treatment following induction therapy with pemetrexed and cisplatin for non-squamous non-small-cell lung cancer. NICE Website. www.nice.org.uk/guidance/ta309. Published April 2014, accessed September 15, 2015.

80.    Pan-Canadian Oncology Drug Review (pCODR) Expert Review Committee (pERC) Final Recommendation - Kadcyla. CADTH Website. www.cadth.ca/sites/default/files/pcodr/pcodr-kadcyla-mbc-fn-rec.pdf. Published December 2013; accessed September 15, 2015.

81.    The National Institute for Health and Care Excellence (NICE). Kadcyla: NICE disappointed by manufacturer’s decision. NICE Website. www.nice.org.uk/news/press-and-media/kadcyla-nice-disappointed-by-manufacturers-decision. Published August 7, 2014; accessed September 15, 2015.

82.    Pan-Canadian Oncology Drug Review (pCODR) Expert Review Committee (pERC) Final Recommendation - Zelboraf. CADTH Website. www.cadth.ca/sites/default/files/pcodr/pcodr-zelboraf-adv-mel-fn-rec.pdf. Published May 2012; accessed September 15, 2015. 

83.    The National Institute for Health and Care Excellence (NICE) consults on a new treatment for skin cancer. NICE Website. Published June 15, 2012; accessed September 15, 2015.

84.    The National Institute for Health and Care Excellence (NICE) Technology Appraisal Guidance. Vemurafenib for treating locally advanced or metastatic BRAF V600 mutation positive malignant melanoma. NICE Website. www.nice.org.uk/guidance/ta269. Published December 2012; accessed September 15, 2015.

85.    DeKoven M, Lee WC, Bouchard J, Massoudi M, Langer J. Real-world cost-effectiveness: lower cost of treating patients to glycemic goal with liraglutide versus exenatide. Adv Ther. 2014;31(2):202-216.

86.    Samyshkin Y, Guillermin AL, Best JH, Brunell SC, Lloyd A. Long-term cost-utility analysis of exenatide once weekly versus insulin glargine for the treatment of type 2 diabetes patients in the US. J Med Econ. 2012;15 Suppl 2:6-13.

87.    Pollock RF, Curtis BH, Smith-Palmer J, Valentine WJ. A UK analysis of the cost-effectiveness of Humalog Mix75/25 and Mix50/50 versus long-acting basal insulin. Adv Ther. 2012;29(12):1051-1066.

88.    Evans M, Wolden M, Gundgaard J, Chubb B, Christensen T. Cost-effectiveness of insulin degludec compared with insulin glargine for patients with type 2 diabetes treated with basal insulin - from the UK health care cost perspective. Diabetes Obes Metab. 2014;16(4):366-375.

89.    Ericsson A, Pollock RF, Hunt B, Valentine WJ. Evaluation of the cost-utility of insulin degludec vs insulin glargine in Sweden. J Med Econ. 2013;16(12):1442-1452.

90.    Ridderstråle M, Jensen MM, Gjesing RP, Niskanen L. Cost-effectiveness of insulin detemir compared with NPH insulin in people with type 2 diabetes in Denmark, Finland, Norway, and Sweden. J Med Econ. 2013;16(4):468-478.

91.    Gao L, Zhao FL, Li SC. Cost-utility analysis of liraglutide versus glimepiride as add-on to metformin in type 2 diabetes patients in China. Int J Technol Assess Health Care. 2012;28(4):436-444.

92.    Granström O, Bergenheim K, McEwan P, Sennfält K, Henriksson M. Cost-effectiveness of saxagliptin (Onglyza®) in type 2 diabetes in Sweden. Prim Care Diabetes. 2012;6(2):127-136.

93.    Davies MJ, Chubb BD, Smith IC, Valentine WJ. Cost-utility analysis of liraglutide compared with sulphonylurea or sitagliptin, all as add-on to metformin monotherapy in Type 2 diabetes mellitus. Diabet Med. 2012;29(3):313-320.

94.    Steen Carlsson K, Persson U. Cost-effectiveness of add-on treatments to metformin in a Swedish setting: liraglutide vs sulphonylurea or sitagplitin. J Med Econ. 2014;17(9):658-669.

95.    Lee WC, Samyshkin Y, Langer J, Palmer JL. Long-term clinical and economic outcomes associated with liraglutide versus sitagliptin therapy when added to metformin in the treatment of type 2 diabetes: a CORE Diabetes Model analysis. J Med Econ. 2012;15 Suppl 2:28-37.

96.    Elgart JF, Caporale JE, Gonzalez L, Aiello E, Waschbusch M, Gagliardino JJ. Treatment of type 2 diabetes with saxagliptin: a pharmacoeconomic evaluation in Argentina. Health Econ Rev. 2013;3(1):11.

97.    Roth JA, Billings P, Ramsey SD, Dumanois R, Carlson JJ. Cost-effectiveness of a 14-gene risk score assay to target adjuvant chemotherapy in early stage non-squamous non-small cell lung cancer. Oncologist. 2014;19(5):466-476.

98.    Borget I, Cadranel J, Pignon JP, et al. Cost-effectiveness of three strategies for second-line erlotinib initiation in nonsmall-cell lung cancer: the ERMETIC study part 3. Eur Respir J. 2012;39(1):172-179.

99.    Chouaid C, Le Caer H, Locher C, et al. Cost effectivenes of erlotinib versus chemotherapy for first-line treatment of non small cell lung cancer (NSCLC) in fit elderly patients participating in a prospective phase 2 study (GFPC 0504). BMC Cancer. 2012;12:301.

100.    Chouaid C, Le Caer H, Corre R, et al. Cost analysis of erlotinib versus chemotherapy for first-line treatment of non-small-cell lung cancer in frail elderly patients participating in a prospective phase 2 study (GFPC 0505). Clin Lung Cancer. 2013;14(2):103-107.

101.    Nelson RE, Stenehjem D, Akerley W. A comparison of individualized treatment guided by VeriStrat with standard of care treatment strategies in patients receiving second-line treatment for advanced non-small cell lung cancer: A cost-utility analysis. Lung Cancer. 2013;82(3):461-468.

102.    Djalalov S, Beca J, Hoch JS, et al. Cost effectiveness of EML4-ALK fusion testing and first-line crizotinib treatment for patients with advanced ALK-positive non-small-cell lung cancer. J Clin Oncol. 2014;32(10):1012-1019.

103.    Cromwell I, van der Hoek K, Malfair Taylor SC, Melosky B, Peacock S. Erlotinib or best supportive care for third-line treatment of advanced non-small-cell lung cancer: a real-world cost-effectiveness analysis. Lung Cancer. 2012;76(3):472-477.

104.    Wang S, Peng L, Li J, et al. A trial-based cost-effectiveness analysis of erlotinib alone versus platinum-based doublet chemotherapy as first-line therapy for Eastern Asian nonsquamous non-small-cell lung cancer. PLoS One. 2013;8(3):e55917.

105.    Lee VW, Schwander B, Lee VH. Effectiveness and cost-effectiveness of erlotinib versus gefitinib in first-line treatment of epidermal growth factor receptor-activating mutation-positive non-small-cell lung cancer patients in Hong Kong. Hong Kong Med J. 2014;20(3):178-186. Published ahead of print November 22, 2013. 

106.    Wang YT, Huang G. Is FDG PET/CT cost-effective for pre-operation staging of potentially operative non-small cell lung cancer? - From Chinese healthcare system perspective. Eur J Radiol. 2012;81(8):e903-909.

107.    Zeng X, Li J, Peng L, et al. Economic outcomes of maintenance gefitinib for locally advanced/metastatic non-small-cell lung cancer with unknown EGFR mutations: a semi-Markov model analysis. PLoS One. 2014;9(2):e88881.

108.    Zhu J, Li T, Wang X, et al. Gene-guided gefitinib switch maintenance therapy for patients with advanced EGFR mutation-positive non-small cell lung cancer: an economic analysis. BMC Cancer. 2013;13:39.

109.    Zeng X, Peng L, Li J, et al. Cost-effectiveness of continuation maintenance pemetrexed after cisplatin and pemetrexed chemotherapy for advanced nonsquamous non-small-cell lung cancer: estimates from the perspective of the Chinese health care system. Clin Ther. 2013;35(1):54-65.

110.    Mitera G, Swaminath A, Rudoler D, et al. Cost-effectiveness analysis comparing conventional versus stereotactic body radiotherapy for surgically ineligible stage I non-small-cell lung cancer. J Oncol Pract. 2014;10(3):e130-136.