Public funding of new cancer drugs: Is NICE getting nastier?

The normative grounds for NICE decision-making: a narrative cross-disciplinary review of empirical studies

The National Institute for Health and Care Excellence (NICE) is the UK's primary health care priority-setter, responsible for advising the National Health Service on its adoption of health technologies. The normative basis for NICE's advice has long been the subject of public and academic interest, but the existing literature does not include any comprehensive summary of the factors observed to have substantively shaped NICE's recommendations. The current review addresses this gap by bringing together 29 studies that have explored NICE decision-making from different disciplinary perspectives, using a range of quantitative and qualitative methods. It finds that although cost-effectiveness has historically played a central role in NICE decision-making, 10 other factors (uncertainty, budget impact, clinical need, innovation, rarity, age, cause of disease, wider societal impacts, stakeholder influence and process factors) are also demonstrably influential and interact with one another in ways that are not well understood. The review also highlights an over-representation in the literature of appraisals conducted prior to 2009, according to methods that have since been superseded. It suggests that this may present a misleading view of the importance of allocative efficiency to NICE's current approach and illustrates the need for further up-to-date research into the normative grounds for NICE's decisions.

The value of anticancer drugs - a regulatory view

The high prices of new anticancer drugs and the marginal added benefit perceived by some stakeholders have fuelled a debate on the value of anticancer drugs in the European Union, even though an agreed definition of what constitutes a drug's value does not exist. In this Perspective, we discuss the value of drugs from different viewpoints and objectives of decision makers: for regulators, assessment of the benefit-risk balance of a drug is a cornerstone for approval; payers rely on cost-effectiveness analyses carried out by health technology assessment agencies for reimbursement decisions; for patients, treatment choices are based on personal preferences and attitudes to risk; and clinicians can use several scales (such as the ESMO Magnitude of Clinical Benefit Scale (ESMO-MCBS)) that have been developed as an attempt to measure value objectively. Although a unique definition that fully captures the concept of value is unlikely to emerge, herein we discuss the importance of understanding different perspectives, and how regulators can help to inform different decision makers.

Preventing Leading Causes of Death: Systematic Review of Cost-Utility Literature

INTRODUCTION

Heart disease, cancer, unintentional injury, chronic lower respiratory disease, and stroke are the 5 leading causes of death in the U.S. The objective of this review is to examine the economic value of prevention interventions addressing these 5 conditions.

METHODS

Tufts Medical Center Cost-Effectiveness Analysis Registry data were queried from 2010 to 2018 for interventions that addressed any of the 5 conditions in the U.S. Results were stratified by condition, prevention stage, type of intervention, study sponsorship, and study perspective. The analyses were conducted in 2020, and all costs were reported in 2019 dollars.

RESULTS

In total, 549 cost-effectiveness analysis studies examined interventions addressing these 5 conditions in the U.S. Tertiary prevention interventions were assessed in 61.4%, whereas primary prevention was assessed in 8.6% of the studies. Primary prevention studies were predominantly funded by government, whereas industry sources funded more tertiary prevention studies, especially those dealing with pharmaceutical interventions. The median incremental cost-effectiveness ratio for the 5 conditions combined was $68,500 per quality-adjusted life year. Median incremental cost-effectiveness ratios were lowest for primary prevention and highest for tertiary prevention.

DISCUSSION

Primary prevention may be more cost effective than secondary and tertiary prevention interventions; however, research investments in primary prevention interventions, especially by industry, lag in comparison. These findings help to highlight the gaps in the cost-effectiveness analysis literature related to the 5 leading causes of death and identify understudied interventions and prevention stages for each condition.

Trends in and drivers of healthcare expenditure in the English NHS: a retrospective analysis

BACKGROUND

In England, rises in healthcare expenditure consistently outpace growth in both GDP and total public expenditure. To ensure the National Health Service (NHS) remains financially sustainable, relevant data on healthcare expenditure are needed to inform decisions about which services should be delivered, by whom and in which settings.

METHODS

We analyse routine data on NHS expenditure in England over 9 years (2008/09 to 2016/17). To quantify the relative contribution of the different care settings to overall healthcare expenditure, we analyse trends in 14 healthcare settings under three broad categories: Hospital Based Care (HBC), Diagnostics and Therapeutics (D&T) and Community Care (CC). We exclude primary care and community mental health services settings due to a lack of consistent data. We employ a set of indices to aggregate diverse outputs and to disentangle growth in healthcare expenditure that is driven by activity from that due to cost pressures. We identify potential drivers of the observed trends from published studies.

RESULTS

Over the 9-year study period, combined NHS expenditure on HBC, D&T and CC rose by 50.2%. Expenditure on HBC rose by 54.1%, corresponding to increases in both activity (29.2%) and cost (15.7%). Rises in expenditure in inpatient (38.5%), outpatient (57.2%), and A&E (59.5%) settings were driven predominately by higher activity. Emergency admissions rose for both short-stay (45.6%) and long-stay cases (26.2%). There was a switch away from inpatient elective care (which fell by 5.1%) and towards day case care (34.8% rise), likely reflecting financial incentives for same-day discharges. Growth in expenditure on D&T (155.2%) was driven by rises in the volume of high cost drugs (270.5%) and chemotherapy (110.2%). Community prescribing grew by 45.2%, with costs falling by 24.4%. Evidence on the relationship between new technologies and healthcare expenditure is mixed, but the fall in drug costs could reflect low generic prices, and the use of health technology assessment or commercial arrangements to inform pricing of new medicines.

CONCLUSIONS

Aggregate trends in HCE mask enormous variation across healthcare settings. Understanding variation in activity and cost across settings is an important initial step towards ensuring the long-term sustainability of the NHS.

Why do health technology assessment drug reimbursement recommendations differ between countries? A parallel convergent mixed methods study

Using quantitative and qualitative research designs, respectively, two studies investigated why countries make different health technology assessment (HTA) drug reimbursement recommendations. Building on these, the objective of this study was to (a) develop a conceptual framework integrating the factors explaining these decisions, (b) explore their relationship and (c) assess if they are congruent, complementary or discrepant. A parallel convergent mixed methods design was used. Countries included in both previous studies were selected (England, Sweden, Scotland and France). A conceptual framework that integrated and organised the factors explaining the decisions from the two studies was developed. Relationships between factors were explored and illustrated through case studies. The framework distinguishes macro-level factors from micro-level ones. Only two of the factors common to both studies were congruent, while two others reached discrepant conclusions (stakeholder input and external review of the evidence processes). The remaining factors identified within one or both studies were complementary. Bringing together these findings contributed to generating a more complete picture of why countries make different HTA recommendations. Results were mostly complementary, explaining and enhancing each other. We conclude that differences often result from a combination of factors, with an important component relating to what occurs during the deliberative process.

Is the National Institute for Health and Care Excellence (NICE) in England more 'innovation-friendly' than the Federal Joint Committee (G-BA) in Germany?

Objectives: Our study explores whether, and how, different methodological choices are associated with different health technology assessment (HTA) outcomes. We focus on the Federal Joint Committee (Gemeinsamer Bundesausschuss, G-BA) in Germany and the National Institute for Health and Care Excellence (NICE) in England. Both agencies may be considered as exemplars for the application of the principles of evidence-based medicine and the logic of cost-effectiveness, respectively. Methods: We extracted data from all publically available G-BA appraisals until April 2015, as well as all NICE single technology appraisals completed during this period. We compared HTA results for matched condition-intervention pairs by G-BA and NICE, and explored other factors including therapeutic area, clinical effectiveness and cost-effectiveness. Results: NICE issued guidance for 88 technologies (125 subgroups) and recommended 67/88 technologies (99/125 subgroups). G-BA completed 105 appraisals (226 subgroups) and determined additional benefit for 64/105 appraisals (90/226 subgroups). We identified 37 matched pairs; for 24/37 drugs, evaluations diverged. NICE recommended 78% (29/37) of technologies appraised, whereas G-BA confirmed additional benefit for 57% (21/37) only (p < 0.05). Conclusions: NICE evaluates new drugs more favorably than G-BA. However, our analysis suggests differences by therapeutic area. Results indicate that different methods are associated with systematic differences in HTA outcomes.

What is driving HTA decision-making? Evidence from cancer drug reimbursement decisions from 6 European countries

BACKGROUND

Decisions on the reimbursement of the same cancer drugs are different across European countries, but empirical work on the reasons behind these differences has been scarce. The main objective of this paper is to make a methodological contribution to existing research, specifically by outlining the systematic process of analysis to address such questions and determining the factors that might lead to different drug reimbursement decisions, and to explore its application in the field of oncology.

METHODS

Reimbursement decisions on cancer drugs in six European countries (Belgium, England, Poland, Portugal, Scotland, and Sweden) between 2006 and 2014 were included in the study. A taxonomy was developed, comprising two groups of variables (system-level and product-specific) and an econometric model was specified (multilevel mixed-effects ordered probit).

RESULTS

Only one in six evaluations in the sample reach the same reimbursement recommendation. Most health system variables were not determinants of a higher or lower probability of a positive reimbursement recommendation. However, the probability of reimbursement was higher when a drug was considered cost-effective by NICE/SMC and when there was a financial Managed Entry Agreement. This work also demonstrated a possible econometric approach for analysing differences in reimbursement decisions and contributes a structured approach for collecting and preparing data for such analyses.

CONCLUSIONS

Drug reimbursement decisions can be analysed in detail along a set of factors that are related to each decision. This information is essential, not only for understanding why a particular drug is accepted in one country and not in another but also when trying to implement a new HTA system or reform an existing one. This analysis provides policy makers and stakeholders with a model that enables a better understanding of the factors that drive HTA decisions and is adaptable to answer similar questions. Moreover, the data collection limitations encountered and described in this work shed light on the need for greater accessibility and transparency in HTA systems and regarding HTA outcomes.

Eligibility of real-world patients with chemo-refractory, K-RAS wild-type, metastatic colorectal cancer for palliative intent regorafenib monotherapy

The CORRECT trial demonstrated survival benefits with regorafenib monotherapy in patients with treatment-refractory, metastatic colorectal cancer (mCRC). However, the trial's stringent eligibility criteria for regorafenib may limit its external validity. We aimed to examine treatment attrition rates and eligibility for regorafenib in routine practice. We identified patients at the British Columbia Cancer Agency diagnosed with mCRC who demonstrated disease progression or intolerable toxicity on 2 or more lines of systemic therapy. During the study timeframe, panitumumab and cetuximab were only used in the chemo-refractory setting. Data on clinicopathologic variables and patient outcomes were ascertained and analyzed. Eligibility was determined using the CORRECT trial criteria. A total of 391 patients were identified, among whom only 39% were eligible for regorafenib: 35% in the panitumumab group and 51% in the cetuximab group. The main reasons for ineligibility in all patients were Eastern Cooperative Oncology Group Performance Status (ECOG PS) > 1 (69%), an elevated total bilirubin (21%), and thromboembolic events in the past 6 months (10%). No difference in eligibility for regorafenib was observed between patients previously receiving panitumumab or cetuximab (P = 0.914; 95% CI 0.550-1.951). Kaplan-Meier analyses showed that regorafenib-eligible compared to regorafenib-ineligible patients had an increased median overall survival of 5.3 versus 2.1 months, respectively (P < 0.001). However, Cox proportional hazard analyses showed that only ECOG PS rather than trial eligibility was correlated with outcomes. The strict eligibility criteria disqualify most patients with treatment-refractory mCRC for regorafenib therapy. Future trials should broaden the eligibility criteria to improve external validity.

Healthcare quality and medicine reimbursement criteria in Iran

Purpose

This study aims to measure the quality of services provided to elderly people at the most crowded governmental ambulatory clinics of Tehran Province using the SERVQUAL scale (Study 1). Moreover, the research indicates the medicine reimbursement criteria to inform the decision-makers of public health insurance organizations using the Borda method (Study 2).

Design/methodology/approach

This study was done as a cross-sectional research on 425 elderly patients who came to the clinics during 2014 and 2015. Finally, using the paired t-test, Friedman test, Borda method, SPSS, Matlab software and Delphi method, the collected data were analysed.

Findings

Regarding the perceived quality, the services assurance dimension was ranked as having the highest quality (4.48) and the accessibility dimension as the lowest one (3.22). Based on the Borda method, the most important criterion for the Iranian health insurance companies to accept a medicine in their reimbursement list is the “life-threatening conditions” factor. On the other hand, “evidence quality” is accounted as the fifth important factor.

Research limitations/implications

The main limitation was the senility of participants that makes it difficult for understanding and completing the questionnaires.

Practical implications

The results can be useful for healthcare policy makers and related authorities. Besides, public health insurers can use the findings for decision-making about the elderly diseases and the problems such as the medical expenses.

Originality/value

The present research has been done in a two-year time frame, and it is more recent than other related studies. Thus, the results are far more authentic and applicable.

Differences in Incremental Cost-Effectiveness Ratios for Common Versus Rare Conditions: A Case from Oncology

BACKGROUND

Incremental cost-effectiveness ratios (ICERs) are used to assess the value for money of new drugs. Many believe that ICERs for drugs that treat rare diseases are much higher than those of common drugs. Our objective was to compare the proportion of ICERs that are cost effective for rare and common cancers.

METHODS

We used the Tufts Medical Center Cost-Effectiveness Analysis (CEA) Registry to identify cost-effectiveness studies of pharmaceutical interventions for cancers. Studies that assessed FDA-approved 'orphan drugs' were categorized as assessing rare cancers. The proportion of common and rare cancer drugs that were cost effective at various ICER thresholds were compared along with study characteristics. Logistic regressions were conducted to assess important predictors of cost effectiveness.

RESULTS

We identified 303 studies that reported 701 ICERs. Seventy nine percent (n = 240) of studies evaluated drugs for common cancers. At a threshold of US$50,000/QALY, 58% (n = 321) of ICERs for drugs treating common cancers and 64% (n = 94) of ICERs for drugs treating rare cancers were cost effective (p = 0.23). At US$100,000/QALY, 74% (n = 409) of ICERs for common cancers and 78% (n = 115) of ICERs for rare cancers were cost effective (p = 0.35). Results from the logistic regressions demonstrated that rarity was not a statistically significant predictor of cost effectiveness at both thresholds with publication year, study sponsorship, and cancer type as covariates.

CONCLUSIONS

The proportion of ICERs that were cost effective at both thresholds does not appear to be significantly different between the two groups. Rarity is not statistically significantly associated with cost effectiveness, even when adjusted for important covariates.

Stated and Revealed Preferences for Funding New High-Cost Cancer Drugs: A Critical Review of the Evidence from Patients, the Public and Payers

BACKGROUND

The growing focus on patient-centred care has encouraged the inclusion of patient and public input into payer drug reimbursement decisions. Yet, little is known about patient/public priorities for funding high-cost medicines, and how they compare to payer priorities applied in public funding decisions for new cancer drugs.

OBJECTIVES

The aim was to identify and compare the funding preferences of cancer patients and the general public against the criteria used by payers making cancer drug funding decisions.

METHODS

A thorough review of the empirical, peer-reviewed English literature was conducted. Information sources were PubMed, EMBASE, MEDLINE, Web of Science, Business Source Complete, and EconLit. Eligible studies (1) assessed the cancer drug funding preferences of patients, the general public or payers, (2) had pre-defined measures of funding preference, and (3) had outcomes with attributes or measures of 'value'. The quality of included studies was evaluated using a health technology assessment-based assessment tool, followed by extraction of general study characteristics and funding preferences, which were categorized using an established WHO-based framework.

RESULTS

Twenty-five preference studies were retrieved (11 quantitative, seven qualitative, seven mixed-methods). Most studies were published from 2005 onward, with the oldest dating back to 1997. Two studies evaluated both patient and public perspectives, giving 27 total funding perspectives (41 % payer, 33 % public, 26 % patients). Of 41 identified funding criteria, payers consider the most (35), the general public considers fewer (23), and patients consider the fewest (12). We identify four unique patient criteria: financial protection, access to medical information, autonomy in treatment decision making, and the 'value of hope'. Sixteen countries/jurisdictions were represented.

CONCLUSIONS

Our results suggest that (1) payers prioritize efficiency (health gains per dollar), while citizens (patients and the general public) prioritize equity (equal access to cancer medicines independent of cost or effectiveness), (2) citizens prioritize few criteria relevant to payers, and (3) citizens prioritize several criteria not considered by payers. This can explain why payer and citizen priorities clash when new cancer medicines are denied public funding.

Effective but costly: How to tackle difficult trade-offs in evaluating health improving technologies in liver diseases

In the current context of rising health care costs and decreasing sustainability, it is becoming increasingly common to resort to decision analytical modeling and health economics evaluations. Decision analytic models are analytical tools that help decision makers to select the best choice between alternative health care interventions, taking into consideration the complexity of the disease, the socioeconomic context, and the relevant differences in outcomes. We present a brief overview of the use of decision analytical models in health economic evaluations and their applications in the area of liver diseases. The aim is to provide the reader with the basic elements to evaluate health economic analysis reports and to discuss some limitations of the current approaches, as highlighted by the case of the therapy of chronic hepatitis C. To serve its purpose, health economics evaluations must be able to do justice to medical innovation and the market while protecting patients and society and promoting fair access to treatment and its economic sustainability.

CONCLUSION

New approaches and methods able to include variables such as prevalence of the disease, budget impact, and sustainability into the cost-effectiveness analysis are needed to reach this goal. (Hepatology 2016;64:1331-1342).

A Tale of Two Thresholds: A Framework for Prioritization within the Cancer Drugs Fund

BACKGOUND

The Cancer Drugs Fund (CDF) has been the subject of controversy since its inception, with critics arguing that it creates a "backdoor" to the National Health Service (NHS), circumventing the National Institute for Health and Care Excellence and its health technology assessment program. Nonetheless, with its creation comes a new decision problem, how to best allocate resources among cancer drugs.

OBJECTIVES

Our objective was to estimate CDF's willingness and ability to pay for cancer drugs, providing guidance regarding where CDF funds are best spent, and determining the number of NHS quality-adjusted life-years (QALYs) displaced through the existence of the fund.

METHODS

Using CDF utilization figures, cost-per-QALY, and treatment episode costs from National Institute for Health and Care Excellence health technology assessment reports, the league-table approach was applied to determine appropriate cost-effectiveness thresholds to inform the CDF's decision making.

RESULTS

The CDF exhibits a willingness-to-pay value of £223,627 per QALY, with 74% and 33% of expenditure for drugs with incremental cost-effectiveness ratios of more than £50,000 and more than £90,000, respectively. During 2013-2014, CDF expenditure generated 4,677 QALYs, compared with a potential 13,485 if the same funds were used as part of routine NHS commissioning, displacing 8,808 QALYs. By ring fencing 10%, 25%, and 50% of the CDF budget for the provision of unevaluated drugs, cost-effectiveness thresholds of £149,000, £111,400, and £68,600 were calculated, respectively.

CONCLUSIONS

Adopting the proposed framework for CDF prioritization would result in disinvestment from a number of highly cost-ineffective drugs applicable for CDF reimbursement. The present lack of a formal economic evaluation not only results in net health losses but also compromises a founding principle of the NHS, that of "equal access for equal need."

Using CART to Identify Thresholds and Hierarchies in the Determinants of Funding Decisions

There is much interest in understanding decision-making processes that determine funding outcomes for health interventions. We use classification and regression trees (CART) to identify cost-effectiveness thresholds and hierarchies in the determinants of funding decisions. The hierarchical structure of CART is suited to analyzing complex conditional and nonlinear relationships. Our analysis uncovered hierarchies where interventions were grouped according to their type and objective. Cost-effectiveness thresholds varied markedly depending on which group the intervention belonged to: lifestyle-type interventions with a prevention objective had an incremental cost-effectiveness threshold of $2356, suggesting that such interventions need to be close to cost saving or dominant to be funded. For lifestyle-type interventions with a treatment objective, the threshold was much higher at $37,024. Lower down the tree, intervention attributes such as the level of patient contribution and the eligibility for government reimbursement influenced the likelihood of funding within groups of similar interventions. Comparison between our CART models and previously published results demonstrated concurrence with standard regression techniques while providing additional insights regarding the role of the funding environment and the structure of decision-maker preferences.

Cost-Utility Analysis of Cancer Prevention, Treatment, and Control: A Systematic Review

CONTEXT

Substantial innovation related to cancer prevention and treatment has occurred in recent decades. However, these innovations have often come at a significant cost. Cost-utility analysis provides a useful framework to assess if the benefits from innovation are worth the additional cost. This systematic review on published cost-utility analyses related to cancer care is from 1988 through 2013. Analyses were conducted in 2013-2015.

EVIDENCE ACQUISITION

This review analyzed data from the Tufts Medical Center Cost-Effectiveness Analysis Registry (www.cearegistry.org), a comprehensive registry with detailed information on 4,339 original cost-utility analyses published in the peer-reviewed medical and economic literature through 2013.

EVIDENCE SYNTHESIS

There were 721 cancer-related cost-utility analyses published from 1998 through 2013, with roughly 12% of studies focused on primary prevention and 17% focused on secondary prevention. The most often studied cancers were breast cancer (29%); colorectal cancer (11%); and prostate cancer (8%). The median reported incremental cost-effectiveness ratios (in 2014 U.S. dollars) were $25,000 for breast cancer, $24,000 for colorectal cancer, and $34,000 for prostate cancer.

CONCLUSIONS

The current evidence indicates that there are many interventions that are cost effective across cancer sites and levels of prevention. However, the results highlight the relatively small number of cancer cost-utility analyses devoted to primary prevention compared with secondary or tertiary prevention.

Methods for the estimation of the National Institute for Health and Care Excellence cost-effectiveness threshold

BACKGROUND

Cost-effectiveness analysis involves the comparison of the incremental cost-effectiveness ratio of a new technology, which is more costly than existing alternatives, with the cost-effectiveness threshold. This indicates whether or not the health expected to be gained from its use exceeds the health expected to be lost elsewhere as other health-care activities are displaced. The threshold therefore represents the additional cost that has to be imposed on the system to forgo 1 quality-adjusted life-year (QALY) of health through displacement. There are no empirical estimates of the cost-effectiveness threshold used by the National Institute for Health and Care Excellence.

OBJECTIVES

(1) To provide a conceptual framework to define the cost-effectiveness threshold and to provide the basis for its empirical estimation. (2) Using programme budgeting data for the English NHS, to estimate the relationship between changes in overall NHS expenditure and changes in mortality. (3) To extend this mortality measure of the health effects of a change in expenditure to life-years and to QALYs by estimating the quality-of-life (QoL) associated with effects on years of life and the additional direct impact on QoL itself. (4) To present the best estimate of the cost-effectiveness threshold for policy purposes.

METHODS

Earlier econometric analysis estimated the relationship between differences in primary care trust (PCT) spending, across programme budget categories (PBCs), and associated disease-specific mortality. This research is extended in several ways including estimating the impact of marginal increases or decreases in overall NHS expenditure on spending in each of the 23 PBCs. Further stages of work link the econometrics to broader health effects in terms of QALYs.

RESULTS

The most relevant 'central' threshold is estimated to be £12,936 per QALY (2008 expenditure, 2008-10 mortality). Uncertainty analysis indicates that the probability that the threshold is < £20,000 per QALY is 0.89 and the probability that it is < £30,000 per QALY is 0.97. Additional 'structural' uncertainty suggests, on balance, that the central or best estimate is, if anything, likely to be an overestimate. The health effects of changes in expenditure are greater when PCTs are under more financial pressure and are more likely to be disinvesting than investing. This indicates that the central estimate of the threshold is likely to be an overestimate for all technologies which impose net costs on the NHS and the appropriate threshold to apply should be lower for technologies which have a greater impact on NHS costs.

LIMITATIONS

The central estimate is based on identifying a preferred analysis at each stage based on the analysis that made the best use of available information, whether or not the assumptions required appeared more reasonable than the other alternatives available, and which provided a more complete picture of the likely health effects of a change in expenditure. However, the limitation of currently available data means that there is substantial uncertainty associated with the estimate of the overall threshold.

CONCLUSIONS

The methods go some way to providing an empirical estimate of the scale of opportunity costs the NHS faces when considering whether or not the health benefits associated with new technologies are greater than the health that is likely to be lost elsewhere in the NHS. Priorities for future research include estimating the threshold for subsequent waves of expenditure and outcome data, for example by utilising expenditure and outcomes available at the level of Clinical Commissioning Groups as well as additional data collected on QoL and updated estimates of incidence (by age and gender) and duration of disease. Nonetheless, the study also starts to make the other NHS patients, who ultimately bear the opportunity costs of such decisions, less abstract and more 'known' in social decisions.

FUNDING

The National Institute for Health Research-Medical Research Council Methodology Research Programme.

The Influence of Cost-Effectiveness and Other Factors on Nice Decisions

The National Institute for Health and Care Excellence (NICE) emphasises that cost-effectiveness is not the only consideration in health technology appraisal and is increasingly explicit about other factors considered relevant but not the weight attached to each. The objective of this study is to investigate the influence of cost-effectiveness and other factors on NICE decisions and whether NICE's decision-making has changed over time. We model NICE's decisions as binary choices for or against a health care technology in a specific patient group. Independent variables comprised of the following: clinical and economic evidence; characteristics of patients, disease or treatment; and contextual factors potentially affecting decision-making. Data on all NICE decisions published by December 2011 were obtained from HTAinSite [www.htainsite.com]. Cost-effectiveness alone correctly predicted 82% of decisions; few other variables were significant and alternative model specifications had similar performance. There was no evidence that the threshold has changed significantly over time. The model with highest prediction accuracy suggested that technologies costing £40 000 per quality-adjusted life-year (QALY) have a 50% chance of NICE rejection (75% at £52 000/QALY; 25% at £27 000/QALY). Past NICE decisions appear to have been based on a higher threshold than £20 000-£30 000/QALY. However, this may reflect consideration of other factors that cannot be easily quantified. © 2014 The Authors. Health Economics published by John Wiley & Sons Ltd.

Cancer mortality reductions were greatest among countries where cancer care spending rose the most, 1995-2007

Health care spending and health outcomes vary markedly across countries, but the association between spending and outcomes remains unclear. This inevitably raises questions as to whether continuing growth in spending is justified, especially relative to the rising cost of cancer care. We compared cancer care across sixteen countries over time, examining changes in cancer spending and two measures of cancer mortality (amenable and excess mortality). We found that compared to low-spending health systems, high-spending systems had consistently lower cancer mortality in the period 1995-2007. Similarly, we found that the countries that increased spending the most had a 17 percent decrease in amenable mortality, compared to 8 percent in the countries with the lowest growth in cancer spending. For excess mortality, the corresponding decreases were 13 percent and 9 percent. Additionally, the rate of decrease for the countries with the highest spending growth was faster than the all-country trend. These findings are consistent with the existence of a link between higher cancer spending and lower cancer mortality. However, further work is needed to investigate the mechanisms that underlie this correlation.

Value of innovation in hematologic malignancies: a systematic review of published cost-effectiveness analyses

We analyzed cost-effectiveness studies related to hematologic malignancies from the Tufts Medical Center Cost-Effectiveness Analysis Registry (www.cearegistry.org), focusing on studies of innovative therapies. Studies that met inclusion criteria were categorized by 4 cancer types (chronic myeloid leukemia, chronic lymphocytic leukemia, non-Hodgkin lymphoma, and multiple myeloma) and 9 treatment agents (interferon-α, 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 in the years 1996-2012 (including 44 cost-effectiveness ratios) met inclusion criteria, 22 (76%) of which were industry funded. Most ratios fell below $50,000 per quality-adjusted life-years (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 that innovative treatments for hematologic malignancies may provide reasonable value for money.

Is there an economic rationale for cancer drugs to have a separate reimbursement review process for resource allocation purposes?

In Canada, there are two separate review processes for the public reimbursement of drugs: one for cancer drugs (originally called the Joint Oncology Drug Review [JODR] and now called the pan-Canadian Oncology Drug Review [pCODR]) and one for drugs in all other disease areas (called the Common Drug Review). We explore whether a justification that is derived from an economic perspective has been provided, in Canada or elsewhere, for cancer drugs to have a separate reimbursement review process (i.e. to be 'treated separately') relative to drugs in all other disease areas. Literature reviews and internet searches were undertaken to identify, collect and analyze relevant documents that would provide information regarding whether an economic rationale has been provided for cancer drugs to be treated separately for resource allocation purposes. Although a number of reasons for cancer drugs to be treated separately were cited both by the JODR and pCODR and in the peer-reviewed literature, a rationale derived from an economic perspective did not appear to be documented. From an economic perspective, separating cancer drugs for resource allocation purposes is likely to impede drug plan decision makers' ability to allocate resources in a manner that maximizes the total aggregate health benefit for the population from available resources. While we acknowledge the challenges that cancer drugs pose to drug reimbursement decision makers, we suggest that separating the reimbursement review of cancer drugs requires further scrutiny.

Early Benefit Assessment of Pharmaceuticals in Germany

Background. Since 2011, when the German Pharmaceutical Market Restructuring Act (AMNOG) came into effect, newly licensed pharmaceuticals must demonstrate an added benefit over a comparator treatment to be reimbursed at a value greater than the reference price. Evidence submitted by manufacturers is assessed by the Institute for Quality and Efficiency in Health Care (IQWiG) and subsequently appraised by the German Federal Joint Committee (FJC) as part of so-called early benefit assessments (EBA). This study aims to explain the decisions made, clarify the roles of the parties (manufacturers, IQWiG, FJC) involved, and guide manufacturers in developing future submissions by analyzing 42 EBAs concluded since January 2011. Methods. We developed a variable list representing the essential components of the EBA: the rating decisions of manufacturers, IQWiG, and the FJC regarding each pharmaceutical’s added benefit; the characteristics of the pharmaceutical; the characteristics of the EBA process; the types of evidence submitted; the methods used to generate evidence; and the pharmaceutical’s maximum possible budget impact. We used Cohen’s kappa to analyze agreement between the rating decisions of the different parties. The chi-square test and bivariate regression were used to identify associations between components of the EBA process and the rating decisions of the FJC. Results. We observed a low level of agreement between manufacturers and the FJC (kappa = 0.21; 95% CI 0.107–0.31) and a substantial level of agreement between IQWiG and the FJC (kappa = 0.64; 95% CI 0.451–0.827) in their rating decisions. The characteristics of the EBA process—for example, duration of the process ( P = 0.357), participation in the official hearing ( P = 0.227), and the pharmaceutical’s budget impact ( P = 0.725)—did not have a significant effect on the rating decisions of the FJC. There was, however, an association between the type of evidence submitted and the FJC’s rating decision when the manufacturer’s dossier reported outcomes related to morbidity ( P = 0.009) or adverse events ( P < 0.001) but not mortality ( P = 0.718) or quality of life ( P = 0.783). Conclusions. While the FJC tends to disagree with the rating of benefit by manufacturers, it softens IQWiG’s decisions, potentially to make the final outcome more acceptable. Concerns voiced that the FJC might be exceeding its statutory authority by taking cost or procedural considerations into account appear to be unfounded. Choosing appropriate evidence to submit for each endpoint remains a challenge, as submission of health outcomes evidently influences decisions.

Regression analysis of indicating multiple incremental cost-effectiveness ratios for non-small cell lung cancer treatment

OBJECTIVES

The value of a health technology can be measured in terms of cost and benefit on two-dimensional co-ordinates. This study is to quantitatively analyze the correlation and to conduct a regression on the X-Y plane constituted by cost and QALYs (quality-adjusted life years) associated with the first line treatment, the maintenance treatment, and the second line treatment for non-small cell lung cancer (NSCLC).

METHODS

The cost-effectiveness data of the cost and QALYs were extracted, with respect to the three categories of the NSCLC treatment, from the CEA Registry at Tufts Medical Center, regarding the literature published from 2000-2011. As a result, 44 QALY-cost ratios were identified.

RESULTS

Based on those extracted data, the correlation and regression analyses were performed by mathematical model using log and square-root functions. The plotted ratios stratified by the three stages for the NSCLC treatment were visually grouped into three clusters. There were statistically significant differences among the correlation coefficients of the cluster. In regression, the log model was found to be better fitted than the square-root model; formulating QALY = -1.12 + 0.16 log(Cost), -1.99 + 0.28 log(Cost), and -0.69 + 0.10 log(Cost) for the first line, the maintenance, and the second line treatment, respectively. Monetary units were standardized to 2008 US dollars.

CONCLUSION

A good methodological potential was confirmed so as to assess the Incremental Cost Effectiveness Ratio (ICER) variations, considering stratification by multiple factors such as disease and treatment categories. This study has certain limitations, such as the small number of included articles and the stratification, not reflecting a factor of new genetic findings.

Does comparative effectiveness research promote rationing of cancer care?

Comparative effectiveness research aims to inform health-care decisions by patients, clinicians, and policy makers. However, questions related to what information is relevant, and how to view the relative attributes of alternative interventions have political, social, and medical considerations. In particular, questions about whether cost is a relevant factor, and whether cost-effectiveness is a desirable or necessary component of such research, have become increasingly controversial as the area has gained prominence. Debate has emerged about whether comparative effectiveness research promotes rationing of cancer care. At the heart of this debate are questions related to the role and limits of patient autonomy, physician discretion in health-care decision making, and the nature of scientific knowledge as an objective good. In this article, we examine the role of comparative effectiveness research in the USA, UK, Canada, and other health-care systems, and the relation between research and policy. As we show, all health systems struggle to balance access to cancer care and control of costs; comparative effectiveness data can clarify choices, but does not itself determine policy or promote rationing of care.

Oncologists' and family physicians' views on value for money of cancer and congestive heart failure care

BACKGROUND

Previous studies suggest that cancer-related interventions are valued by policy makers more favorably than interventions for other medical conditions, but the views of practicing physicians have not yet been assessed in Israel. Attitudes and judgments of practicing physicians may assist decision-makers in their deliberations on coverage of new technologies. We conducted a national survey in Israel among oncologists and family physicians to explore their views on access to care, coverage decisions and treatment recommendations for cancer and congestive heart failure (CHF) patients.

METHODS

We administered a web-based survey to 300 family physicians and 156 oncologists. The questionnaire included 24 statements and physicians were asked to indicate their level of agreement with each statement on a 5-point Likert scale, ranging from "strongly agree" to "strongly disagree". Where relevant, physicians were asked to express their views on interventions for cancer and CHF respectively.

RESULTS

Response rates were 39% for family physicians and 36% for oncologists. Participants expressed similar views on cancer and CHF care and no significant differences were found between the two medical specialties. More than 85% of physicians believe that inclusion of a treatment in the National List of Health Services (NLHS) strongly affects their patients' access to care. Approximately 80% suggest that more use of comparative-effectiveness and cost-effectiveness analysis is needed in coverage decisions. The vast majority of respondents (75%) suggest that assessment of value-for-money should be made by an independent (academic) institution or the national committee responsible for recommending coverage decisions, Seventy percent believe that treatments not included in the NLHS should be included in supplementary health insurance programs and only a small minority of respondents (<30%) believe that cancer-related interventions should receive higher priority than non-cancer interventions in coverage decisions.

CONCLUSIONS

Our findings suggest that both oncologists and family physicians value cancer and CHF interventions equally. We could not find evidence for a "cancer premium" as implied from previous surveys and analysis of coverage decisions in various countries.

Decision making by NICE: examining the influences of evidence, process and context

The National Institute for Health and Clinical Excellence (NICE) provides guidance to the National Health Service (NHS) in England and Wales on funding and use of new technologies. This study examined the impact of evidence, process and context factors on NICE decisions in 2004–2009. A data set of NICE decisions pertaining to pharmaceutical technologies was created, including 32 variables extracted from published information. A three-category outcome variable was used, defined as the decision to ‘recommend’, ‘restrict’ or ‘not recommend’ a technology. With multinomial logistic regression, the relative contribution of explanatory variables on NICE decisions was assessed. A total of 65 technology appraisals (118 technologies) were analysed. Of the technologies, 27% were recommended, 58% were restricted and 14% were not recommended by NICE for NHS funding. The multinomial model showed significant associations (p ⩽ 0.10) between NICE outcome and four variables: (i) demonstration of statistical superiority of the primary endpoint in clinical trials by the appraised technology; (ii) the incremental cost-effectiveness ratio (ICER); (iii) the number of pharmaceuticals appraised within the same appraisal; and (iv) the appraisal year. Results confirm the value of a comprehensive and multivariate approach to understanding NICE decision making. New factors affecting NICE decision making were identified, including the effect of clinical superiority, and the effect of process and socio-economic factors.

Transparency vs. closed-door policy: do process characteristics have an impact on the outcomes of coverage decisions? A statistical analysis

The aim of this study was to analyze influences of process- and technology-related characteristics on the outcomes of coverage decisions. Using survey data on 77 decisions from 13 countries, we examined whether outcomes differ by 14 variables that describe components of decision-making processes and the technology. We analyzed the likelihood of committees covering a technology, i.e. positive (including partial coverage) vs. negative coverage decisions. We performed non-parametric univariate tests and binomial logistic regression with a stepwise variable selection procedure. We identified a negative association between a positive decision and whether the technology is a prescribed medicine (p=0.0097). Other significant influences on a positive decision outcome included one disease area (p=0.0311) and whether a technology was judged to be (cost-)effective (p<0.0001). The first estimation of the logistic regression yielded a quasi-complete separation for technologies that were clearly judged (cost-)effective. In uncertain decisions, a higher number of stakeholders involved in voting (odds ratio=2.52; p=0.03) increased the likelihood of a positive outcome. The results suggest that decisions followed the lines of evidence-based decision-making. Despite claims for transparent and participative decision-making, the phase of evidence generation seemed most critical as decision-makers usually adopted the assessment recommendations. We identified little impact of process configurations.

[HTA-Perspective: Challenges in the early assessment of new oncological drugs]

Oncologic drug therapies have gained wide attention in the context of health policy priority setting for serious and socially significant diseases with high human and monetary costs. Due to uncertainties and scepticism about the actual therapeutic importance of newly approved oncology products, an early assessment programme was already established in Austria in 2007. The assessment of new oncology products is thereby faced with special challenges, since study populations are frequently not representative or the study design is laid out in such a manner that a definitive assessment of patient-relevant endpoints is not possible (cross-overs after interim assessments, surrogate parameters as primary endpoints, uncontrolled studies or those with unrealistic comparators, invalidated post-hoc identified biomarkers). On account of these major uncertainties, even the European Medicines Agency (EMA) is already contemplating multi-stage, "adaptive" approvals, and national reimbursement institutions are increasingly working with outcome-oriented, conditional reimbursement. (As supplied by publisher).

Alignment of practice guidelines with targeted-therapy drug funding policies in Ontario

BACKGROUND

We evaluated clinical practice guideline (cpg) recommendations from Cancer Care Ontario's Program in Evidence-Based Care (pebc) for molecularly targeted systemic treatments (tts) and subsequent funding decisions from the Ontario Ministry of Health and Long-Term Care.

METHODS

We identified pebc cpgs on tt published before June 1, 2010, and extracted information regarding the key evidence cited in support of cpg recommendations and the effect size associated with each tt. Those variables were compared with mohltc funding decisions as of June 2011.

RESULTS

From 23 guidelines related to 17 tts, we identified 43 recommendations, among which 38 (88%) endorsed tt use. Among all the recommendations, 38 (88%) were based on published key evidence, with 82% (31 of 38) being supported by meta-analyses or phase iii trials. For the 38 recommendations endorsing tts, funding was approved in 28 (74%; odds ratio related to cpg recommendation: 29.9; p = 0.003). We were unable to demonstrate that recommendations associated with statistically significant improvements in overall survival [os: 14 of 16 (88%) vs. 8 of 14 (57%); p = 0.10] or disease- (dfs) or progression-free survival [pfs: 16 of 21 (76%) vs. 3 of 5 (60%); p = 0.59] were more likely to be funded than those with no significant difference. Moreover, we did not observe significant associations between funding approvals and absolute improvements of 3 months or more in os [6 of 6 (100%) vs. 3 of 6 (50%), p = 0.18] or pfs [6 of 8 (75%) vs. 10 of 12 (83%), p = 1.00].

CONCLUSIONS

For use of tts, most recommendations in pebc cpgs are based on meta-analyses or phase iii data, and funding decisions were strongly associated with those recommendations. Our data suggest a trend toward increased rates of funding for therapies with statistically significant improvements in os.

Challenges in the development and reimbursement of personalized medicine-payer and manufacturer perspectives and implications for health economics and outcomes research: a report of the ISPOR personalized medicine special interest group

BACKGROUND

Personalized medicine technologies can improve individual health by delivering the right dose of the right drug to the right patient at the right time but create challenges in deciding which technologies offer sufficient value to justify widespread diffusion. Personalized medicine technologies, however, do not neatly fit into existing health technology assessment and reimbursement processes.

OBJECTIVES

In this article, the Personalized Medicine Special Interest Group of the International Society for Pharmacoeconomics and Outcomes Research evaluated key development and reimbursement considerations from the payer and manufacturer perspectives.

METHODS

Five key areas in which health economics and outcomes research best practices could be developed to improve value assessment, reimbursement, and patient access decisions for personalized medicine have been identified.

RESULTS

These areas are as follows: 1 research prioritization and early value assessment, 2 best practices for clinical evidence development, 3 best practices for health economic assessment, 4 addressing health technology assessment challenges, and 5 new incentive and reimbursement approaches for personalized medicine.

CONCLUSIONS

Key gaps in health economics and outcomes research best practices, decision standards, and value assessment processes are also discussed, along with next steps for evolving health economics and outcomes research practices in personalized medicine.

A systematic review of coverage decision-making on health technologies-evidence from the real world

OBJECTIVE

Quantitative analysis of real-world coverage decision-making offers insights into the revealed preferences of appraisal committees. Aim of this review was to structure empirical evidence of coverage decisions made in practice based on the components 'methods and evidence', 'criteria and standards', 'decision outcome' and 'processes'.

METHODS

Several electronic databases, key journals and decision committees' websites were searched for publications between 1993 and June 2011. Inclusion criteria were the analysis of past decisions and application of quantitative methods. Each study was categorized by the scope of decision-making and the components covered by the variables used in quantitative analysis.

RESULTS

Thirty-two studies were identified. Many focused on pharmaceuticals, the UK NICE or the Australian PBAC. The components were covered comprehensively, but heterogeneously. Seventy-two variables were identified of which the following were more prevalent: specifications of the decision outcome; the indications considered for appraisal, identification of incremental cost-effectiveness ratios, appropriateness of evaluation methods, type of economic or clinical evidence used for assessment, and the decision date.

CONCLUSIONS

Research was dominated by analysis of decision outcomes and appraisal criteria. Although common approaches were identified, the complexity of coverage decision-making - reflected by the heterogeneity of identified variables - will continue to challenge empirical research.

Societal values in the allocation of healthcare resources: is it all about the health gain?

Over the past decade, public distrust in unavoidable value-laden decisions on the allocation of resources to new health technologies has grown. In response, healthcare organizations have made considerable efforts to improve their acceptability by increasing transparency in decision-making processes. However, the social value judgments (distributive preferences of the public) embedded in them have yet to be defined. While the need to explicate such judgments has become widely recognized, the most appropriate approach to accomplishing this remains unclear. The aims of this review were to identify factors around which distributive preferences of the public have been sought, create a list of social values proposed or used in current resource allocation decision-making processes for new health technologies, and review approaches to eliciting such values from the general public. Social values proposed or used in making resource allocation decisions for new health technologies were identified through three approaches: (i) a comprehensive review of published, peer-reviewed, empirical studies of public preferences for the distribution of healthcare; (ii) an analysis of non-technical factors or social value statements considered by technology funding decision-making processes in Canada and abroad; and (iii) a review of appeals to funding decisions on grounds in part related to social value judgments. A total of 34 empirical studies, 10 technology funding decision-making processes, and 12 appeals to decisions were identified and reviewed. The key factors/patient characteristics addressed through policy statements and around which distributive preferences of the public have been sought included severity of illness, immediate need, age (and its relationship to lifetime health), health gain (amount and final outcome/health state), personal responsibility for illness, caregiving responsibilities, and number of patients who could benefit (rarity). Empirical studies typically examined the importance of these factors in isolation. Therefore, the extent to which preferences around one factor may be modified in the presence of others is still unclear. Research that seeks to clarify interactions among factors by asking the public to weigh several of them at once is needed to ensure the relevance of elicited preferences to real-world technology funding decisions.

Off-label use of anti-cancer drugs between clinical practice and research: the Italian experience

BACKGROUND

Off-label use is the practice of prescribing a drug outside the terms of its official labeling. Worldwide, about 20% of the commonly prescribed medications are off-label, and the percentage increases in specific patient populations, such as children, pregnant women, and cancer patients. Off-label use is particularly widespread in oncology for many reasons, including the wide variety of cancer subtypes, the difficulties involved in performing clinical trials, the rapid diffusion of preliminary results, and delays in the approval of new drugs by regulatory organizations/agencies.

OBJECTIVE

The aim of this article is to describe the use of off-label drugs in oncology, with an emphasis on the role of the world's leading regulatory agencies and an assessment of current Italian legislation.

CONCLUSION

Off-label drug utilization is essential in oncology when based on evidence. However, off-label drugs must be prescribed in accordance with existing national laws and only when the potential benefit outweighs the potential toxic effects.

Health technology funding decision-making processes around the world: the same, yet different

All healthcare systems routinely make resource allocation decisions that trade off potential health gains to different patient populations. However, when such trade-offs relate to the introduction of new, promising health technologies, perceived 'winners' and 'losers' are more apparent. In recent years, public scrutiny over such decisions has intensified, raising the need to better understand how they are currently made and how they might be improved. The objective of this paper is to critically review and compare current processes for making health technology funding decisions at the regional, state/provincial and national level in 20 countries. A comprehensive search for published, peer-reviewed and grey literature describing actual national, state/provincial and regional/institutional technology decision-making processes was conducted. Information was extracted by two independent reviewers and tabulated to facilitate qualitative comparative analyses. To identify strengths and weaknesses of processes identified, websites of corresponding organizations were searched for commissioned reviews/evaluations, which were subsequently analysed using standard qualitative methods. A total of 21 national, four provincial/state and six regional/institutional-level processes were found. Although information on each one varied, they could be grouped into four sequential categories: (i) identification of the decision problem; (ii) information inputs; (iii) elements of the decision-making process; and (iv) public accountability and decision implementation. While information requirements of all processes appeared substantial and decision-making factors comprehensive, the way in which they were utilized was often unclear, as were approaches used to incorporate social values or equity arguments into decisions. A comprehensive inventory of approaches to implementing the four main components of all technology funding decision-making processes was compiled, from which areas for future work or research aimed at improving the acceptability of decisions were identified. They include the explication of decision criteria and social values underpinning processes.

How long and how well: oncologists' attitudes toward the relative value of life-prolonging v. quality of life-enhancing treatments

OBJECTIVE

To determine how oncologists value quality-enhancing v. life-prolonging outcomes attributable to chemotherapy.

METHODS

The authors surveyed a random sample of 1379 US medical oncologists (members of the American Society of Clinical Oncology), presenting them with 2 scenarios involving a hypothetical new chemotherapy drug. Given their responses, the authors derived the implicit cost-effectiveness ratios each physician attributed to quality-enhancing and life-prolonging chemotherapies.

RESULTS

The authors received responses from 58% of the oncologists surveyed. On average, the responses implied that oncologists were willing to prescribe treatments that cost $245,972 per quality-adjusted life-year (QALY; SD $243,663 per QALY) in life-prolonging situations v. only $119,082 per QALY (SD $197,048 per QALY) for treatments that improve quality of life but do not prolong survival (P < 0.001). This difference did not depend on age, gender, percentage of time in clinical work, or self-reported preparedness to use and interpret cost-effectiveness information (P > 0.05 for all specifications). Differences across these situations persisted even among those who considered themselves to be "well-prepared" to make cost-effectiveness decisions.

CONCLUSION

Cost-effectiveness thresholds for oncologists vary widely for life-prolonging chemotherapy compared to treatments that only enhance quality of life. This difference suggests that oncologists value length of survival more highly than quality of life when making chemotherapy decisions.

Comparison of Anticancer Drug Coverage Decisions in the United States and United Kingdom: Does the Evidence Support the Rhetoric?

Purpose

In contrast to the United States, several European countries have health technology assessment programs for drugs, many of which assess cost effectiveness. Coverage decisions that consider cost effectiveness may lead to restrictions in access.

Methods

For a purposive sample of five decision-making bodies, we analyzed US and United Kingdom coverage decisions on all anticancer drugs approved by the US Food and Drug Administration (FDA) from 2004 to 2008. Data sources for the timing and outcome of licensing and coverage decisions included published and unpublished documentation, Web sites, and personal communication.

Results

The FDA approved 59 anticancer drugs over the study period, of which 46 were also approved by the European Medicines Agency. In the United States, 100% of drugs were covered, mostly without restriction. However, the United Kingdom bodies made positive coverage decisions for less than half of licensed drugs (National Institute for Health and Clinical Excellence [NICE]: 39%; Scottish Medicines Consortium [SMC]: 43%). Whereas the Centers for Medicare and Medicaid Services (CMS) and the Department of Veterans Affairs (VA) covered all 59 drugs from the FDA license date, delays were evident for some Regence Group decisions that were informed by cost effectiveness (median, 0 days; semi-interquartile range [SIQR], 122 days; n = 22). Relative to the European Medicines Agency license date, median time to coverage was 783 days (SIQR, 170 days) for NICE and 231 days (SIQR, 129 days) for the SMC.

Conclusion

Anticancer drug coverage decisions that consider cost effectiveness are associated with greater restrictions and slower time to coverage. However, this approach may represent an explicit alternative to rationing achieved through the use of patient copayments.

When is cancer care cost-effective? A systematic overview of cost-utility analyses in oncology

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 published 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 population, 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 hematologic 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.