Richard H. Chapman

Systematic Overview of Cost-Utility Assessments in Oncology

PURPOSE Cost-utility analyses (CUAs) present the value of an intervention as the ratio of its incremental cost divided by its incremental survival benefit, with survival weighted by utilities to produce quality-adjusted life years (QALYs). We critically reviewed the CUA literature and its role in informing clinical oncology practice, research priorities, and policy. METHODS The English-language literature was searched between 1975 and1997 for CUAs. Two readers abstracted from each article descriptions of the clinical situation and patients, the methods used, study perspective, the measures of effectiveness, costs included, discounting, and whether sensitivity analyses were performed. The readers then made subjective quality assessments. We also extracted utility values from the reviewed papers, along with information on how and from whom utilities were measured. RESULTS Our search yielded 40 studies, which described 263 health states and presented 89 cost-utility ratios. Both the number and quality of studies increased over time. However, many studies are at variance with current standards. Only 20% of studies took a societal perspective, more than a third failed to discount both the costs and QALYs, and utilities were often simply estimates from the investigators or other physicians. CONCLUSION The cost-utility literature in oncology is not large but is rapidly expanding. There remains much room for improvement in the methodological rigor with which utilities are measured. Considering quality-of-life effects by incorporating utilities into economic studies is particularly important in oncology, where many therapies obtain modest improvements in response or survival at the expense of nontrivial toxicity.

Measuring costs in cost-utility analyses. Variations in the literature.

OBJECTIVES Although cost-utility analysis (CUA) has been recommended by some experts as the preferred technique for economic evaluation, there is controversy regarding what costs should be included and how they should be measured. The purpose of this study was to: a) identify the cost components that have been included in published CUAs; b) catalogue the sources of valuation used; c) examine the methods employed for estimating costs; and d) explore whether methods have changed over time. METHODS We conducted a comprehensive search of the published literature and systematically collected data on the cost estimation of CUAs. We audited the cost estimates in 228 CUAs. RESULTS In most studies (99%), analysts included some direct healthcare costs. However, the inclusion of direct non-healthcare and time costs (17%) was generally lacking, as was productivity costs (8%). Only 6% of studies considered future costs in added life-years. In general, we found little evidence of change in methods over time. The most frequently used source for valuation of healthcare services was published estimates (73%). Few studies obtained utilization data from RCTs (10%) or relied on other primary data (23%). About two-thirds of studies conducted sensitivity analyses on cost estimates. CONCLUSIONS We found wide variations in the estimation of costs in published CUAs. The study underscores the need for more uniformity and transparency in the field, and continued vigilance over cost estimates in CUAs on the part of analysts, reviewers, and journal editors.

Cost-utility analyses of clinical preventive services: published ratios, 1976-1997.

BACKGROUND Cost-effectiveness analyses of clinical preventive services are a potential means to aid public health resource allocation. Cost-utility analysis (CUA) is a specific form of cost-effectiveness analysis where results are expressed in terms of cost per quality-adjusted life year (QALY) gained. To increase the transparency and comparability of CUAs, standardization of methods has been recommended. OBJECTIVES The purposes of this study were as follows: (1) identify published articles with original CUAs of primary and secondary clinical preventive services, (2) summarize the ratios found in these analyses, (3) identify articles employing comparable methods, and (4) explore analytic methods employed over time. METHODS As part of a larger study we conducted a comprehensive search of published CUAs in the area of clinical preventive services and systematically collected data on the results of the analyses and analytic methods employed. Cost-effectiveness ratios were standardized and organized into a table. RESULTS We found 50 CUAs pertaining to clinical preventive services (primary, n=22, 44%; and secondary, n=28, 56%) and 174 cost-effectiveness ratios. These ratios ranged from cost-savings up to

An Off-the-Shelf Help List A Comprehensive Catalog of Preference Scores from Published Cost-Utility Analyses

27,000,000/QALY, with a median of

Can We Better Prioritize Resources for Cost-Utility Research?:

14,000/QALY. Only three (6%) of the CUAs met minimum reference case requirements. There was no apparent improvement of methods over time. CONCLUSIONS Immunizations and chemoprophylaxis have the most favorable cost-effectiveness ratios, and preventive services are more cost-effective when targeted at high-risk populations. However, there is wide variation in the methods used in these analyses. This study allows us to define where improvements in methodologic rigor need to occur, provides a base-line for future audits, and highlights disease areas in clinical preventive services that have been omitted or underevaluated.

Cost-Effectiveness of Sacubitril–Valsartan in Patients With Heart Failure With Reduced Ejection Fraction

Purpose. The Panel on Cost-Effectiveness in Health and Medicine recommends an organized collection of preference measure values for health states that can be used in cost-utility analyses (CUAs). The authors sought to construct a catalog of preference scores from published CUAs, organize the catalog by clinical categories, and identify methods of preference score assessment. Method. The authors systematically searched Medline and other databases to identify original CUAs published through 1997. Information was abstracted on the health state descriptions, corresponding preference scores, method of preference score elicitation, and the source of the estimate. Results. Two hundred twenty-eight CUAs were appraised. The authors found 949 health states and corresponding preference scores. Most frequently, health states pertained to the circulatory system (21.7%), health states were valued by experts (35.8%), and values were derived through community-based preference scores (23.5%). Conclusion. A catalog of preference scores for health states can be constructed. The catalog (http://www.hsph.harvard.edu/organizations/hcra/cuadatabase/intro.html) may provide a useful reference tool for producers and consumers of CUAs but also underscores the methodologic variation and inconsistencies present in the field.

Assessing the value of mepolizumab for severe eosinophilic asthma: a cost-effectiveness analysis

Purpose. We examined 512 published cost-utility analyses (CUAs) in the U.S. and other developed countries from 1976 through 2001 to determine: 1) the types of interventions studied; 2) whether they cover diseases and conditions with the highest burden; and, 3) to what extent they have covered leading health concerns defined by the Healthy People 2010 report. Data and Methods. We compared rankings of the most common diseases covered by the CUAs to rankings of U.S. disease burden. We also examined the extent to which CUAs covered key Healthy People 2010 priorites. Results. CUAs have focused mostly on pharmaceuticals (40%) and surgical procedures (16%). When compared to leading causes of DALYs, the data show overrepresentation of CUAs in cerebrovascular disease, diabetes, breast cancer, and HIV/AIDS, and underrepresentation in depression and bipolar disorder, injuries, and substance abuse disorders. Few CUAs have targeted Healthy People 2010 areas, such as physical activity. Conclusions. Published CUAs are associated with burden measures, but have not covered certain important health problems. These discrepancies do not alone indicate that society has been targeting resources for research inefficiently, but they do suggest the need to formalize the question of where each CUA research dollar might do the most good.

Comparison of self-reported survey (SHIELD) versus NHANES data in estimating prevalence of dyslipidemia.

Heart failure continues to cause substantial morbidity despite therapeutic advances over the past 3 decades (1). One of the cornerstones of therapy for heart failure with reduced ejection fraction is treatment with an angiotensin-converting enzyme inhibitor (ACEI) or an angiotensin-receptor blocker (ARB) to inhibit the reninangiotensinaldosterone system, a neurohormonal system that plays a large role in disease progression (2, 3). The natriuretic peptide system is a distinct neurohormonal system that induces positive hemodynamic effects in patients with heart failure. Sacubitrilvalsartan (Entresto [Novartis]) is a novel medication consisting of the ARB valsartan and sacubitril, a neprilysin inhibitor that decreases the degradation of natriuretic peptides. The PARADIGM-HF (Prospective Comparison of ARNI with ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure) trial was a randomized, double-blind trial that compared twice-daily treatment with sacubitrilvalsartan (200 mg) or enalapril (10 mg) in patients with chronic heart failure and reduced ejection fraction who were tolerating therapy with an ACEI or an ARB (4). It included a sequential run-in period before randomization, during which 10.5% of enrolled patients dropped out during the enalapril phase followed by 10.4% in the sacubitrilvalsartan phase. The trial randomly assigned 8442 patients and was stopped after a median follow-up of 27 months due to an overwhelming survival benefit. The study found that treatment with sacubitrilvalsartan reduced cardiovascular mortality, decreased hospitalizations and emergency department (ED) visits for heart failure, and improved quality of life compared with enalapril therapy (4, 5). However, at

Cost-utility analyses of clinical preventive services1

12.50 per day, sacubitrilvalsartan represents a substantial price increase compared with generic ACEIs that can cost less than 10 cents per day (6). We performed an independent analysis of the cost-effectiveness of sacubitrilvalsartan compared with usual care in a cohort of patients with New York Heart Association (NYHA) class II to IV heart failure based on the PARADIGM-HF trial population, as well as in subgroups defined by NYHA class. Methods Decision Model We developed a Markov model to evaluate the cost-effectiveness of sacubitrilvalsartan compared with lisinopril in patients at a mean age of 64 years, NYHA class II to IV heart failure, and reduced ejection fraction (<0.40), with a subgroup composition based on that of the PARADIGM-HF trial (72.9% with class II heart failure, 26.2% with class III, and 0.9% with class IV) (4, 7). We excluded patients with class I heart failure (4.7% of the trial population), who were unintentionally enrolled because they were more ill during screening and improved during the run-in phase; we included these patients in a sensitivity analysis (4, 7). We analyzed cost-effectiveness in the subgroups of patients with class II or class III/IV heart failure. We modeled a cohort of patients based on the PARADIGM-HF trial, which excluded patients with systolic blood pressure less than 95 to 100 mm Hg, chronic kidney disease (glomerular filtration rate <30 mL/min/1.73 m2), or inability to tolerate therapy during the run-in phase (4). Patients initially received sacubitrilvalsartan, 200 mg twice daily, or lisinopril, 20 mg daily (the target dose for heart failure). We modeled lisinopril instead of enalapril (the comparator in PARADIGM-HF) because it is less expensive, is more widely used, and has demonstrated functionally equivalent benefits compared with enalapril (6, 8, 9). In the model, patients incurred a monthly risk for heart failure hospitalization, nonheart failure hospitalization, ED visit for heart failure, treatment intolerance, and cardiovascular or noncardiovascular death (Appendix Figure 1). In addition, those with severe angioedema experienced a hospitalization. Patients with treatment intolerance during receipt of sacubitrilvalsartan were switched to lisinopril, and those with intolerance while receiving lisinopril were switched to the ARB losartan (100 mg/d). We used losartan as the alternative ARB therapy because it has effects similar to those of valsartan but lower cost (6, 8). We assumed that no patients would have intolerance of losartan or would discontinue its use. Appendix Figure 1. Model schema. The square is the treatment decision to start therapy with sacubitrilvalsartan or lisinopril (angiotensin-converting enzyme inhibitor). The Ms represent monthly models during which surviving patients are at risk for multiple events at chance nodes (circles): HF hospitalization, ED visits for HF without subsequent hospitalization, non-HF hospitalization (not shown), and death. Patients are also at risk for therapy intolerance, including angioedema, and death. The triangles signify the end of a monthly cycle and the initial state of the subsequent cycle. Surviving patients receiving sacubitrilvalsartan who have therapy intolerance switch to lisinopril the following month. Those receiving lisinopril with intolerance switch to losartan. ED = emergency department; HF = heart failure. The model followed patients over their lifetime with a monthly time cycle. We used a series of willingness-to-pay thresholds based on the cost-effectiveness guidelines of the American Heart Association and the World Health Organization, with less than

Cost-effectiveness of Drugs to Treat Relapsed/Refractory Multiple Myeloma in the United States

50000 per quality-adjusted life-year (QALY) (approximately the U.S. gross domestic product per capita) considered very cost-effective,