Use Of Quality-adjusted Life Years Research Articles

Using QALYs as an Outcome for Assessing Global Prediction Accuracy in Diabetes Simulation Models.

(1) To demonstrate the use of quality-adjusted life-years (QALYs) as an outcome measure for comparing performance between simulation models and identifying the most accurate model for economic evaluation and health technology assessment. QALYs relate directly to decision making and combine mortality and diverse clinical events into a single measure using evidence-based weights that reflect population preferences. (2) To explore the usefulness of Q2, the proportional reduction in error, as a model performance metric and compare it with other metrics: mean squared error (MSE), mean absolute error, bias (mean residual), and R2. We simulated all EXSCEL trial participants (N = 14,729) using the UK Prospective Diabetes Study Outcomes Model software versions 1 (UKPDS-OM1) and 2 (UKPDS-OM2). The EXSCEL trial compared once-weekly exenatide with placebo (median 3.2-y follow-up). Default UKPDS-OM2 utilities were used to estimate undiscounted QALYs over the trial period based on the observed events and survival. These were compared with the QALYs predicted by UKPDS-OM1/2 for the same period. UKPDS-OM2 predicted patients' QALYs more accurately than UKPDS-OM1 did (MSE: 0.210 v. 0.253; Q2: 0.822 v. 0.786). UKPDS-OM2 underestimated QALYs by an average of 0.127 versus 0.150 for UKPDS-OM1. UKPDS-OM2 predictions were more accurate for mortality, myocardial infarction, and stroke, whereas UKPDS-OM1 better predicted blindness and heart disease. Q2 facilitated comparisons between subgroups and (unlike R2) was lower for biased predictors. Q2 for QALYs was useful for comparing global prediction accuracy (across all clinical events) of diabetes models. It could be used for model registries, choosing between simulation models for economic evaluation and evaluating the impact of recalibration. Similar methods could be used in other disease areas. Diabetes simulation models are currently validated by examining their ability to predict the incidence of individual events (e.g., myocardial infarction, stroke, amputation) or composite events (e.g., first major adverse cardiovascular event).We introduce Q2, the proportional reduction in error, as a measure that may be useful for evaluating and comparing the prediction accuracy of econometric or simulation models.We propose using the Q2 or mean squared error for QALYs as global measures of model prediction accuracy when comparing diabetes models' performance for health technology assessment; these can be used to select the most accurate simulation model for economic evaluation and to evaluate the impact of model recalibration in diabetes or other conditions.

QALYs, Disability Discrimination, and the Role of Adaptation in the Capacity to Recover: The Patient-Sensitive Health-Related Quality of Life Account.

Quality-Adjusted Life Years (QALYs) and Disability-Adjusted Life Years (DALYs) are two of the most commonly used health measures to determine resource prioritization and the population burden of disease, respectively. There are different types of problems with the use of QALYs and DALYs for measuring health benefits. Some of these problems have to do with measurement, for example, the weights they ascribe to health states might fail to reflect with exact accuracy the actual well-being or health levels of individuals. But even if these weights represent accurately the well-being levels of individuals, there is room for questioning whether these measures capture everything that we care about in these cases, or whether there are important issues that they leave out, including considerations of fairness or equality. In this regard, the measures have been criticized for treating the aggregation of small benefits as greater than the aggregation of fewer but bigger benefits,1 for disregarding fair chances in favor of utility maximization,2 and for raising problems when applied in the context of variable population size.3 Perhaps one of the most pervasive ethical issues that has been associated with the use of these measures is the fact that they seem to discriminate against disabled people.4 Since the measures assume that disabled people have lower well-being and a shorter life span, treating a disabled person's medical condition contributes less to the maximization of years of life with good health than treating a non-disabled patient's medical condition.

Estimating the EQ-5D-5L value set for the Philippines

BackgroundThe Philippines has recommended the use of Quality-Adjusted Life Years (QALYs) in government health technology assessments (HTA). We aimed to develop a value set for the EQ-5D-5L based on health preferences of the healthy general adult population in the Philippines.MethodsHealthy, literate adults were recruited from the Philippine general population with quota targets based on age, sex, administrative region, type of residence, education, income, and ethnolinguistic groups. Each participant’s preference was elicited by completing Composite Time Trade-Off (C-TTO) and Discrete Choice Experiment (DCE) tasks. Tasks were computer-assisted using the EuroQol Valuation Technology 2.0. To estimate the value set, we explored 20- and 8-parameter models that either use c-TTO-only data or both c-TTO and DCE (also called hybrid models). Final model choice was guided by principles of monotonicity, out-of-sample likelihood, model fit, and parsimony.ResultsWe recruited 1000 respondents with demographic characteristics that approximate the general population such as 49.6% Female, 82% Roman Catholic, 40% in urban areas, and 55% finished high school. None of the 20-parameter models demonstrated monotonicity (logical worsening of coefficients with increasing severity). From the 8-parameter models, the homoscedastic TTO-only model exhibited the best fit. From this model, mobility and pain/ discomfort had the highest effect on utilities.ConclusionThe selected model for representing the Philippine general population preferences for EQ-5D-5L health states was an 8-parameter homoscedastic TTO-only model. This value set is recommended for use in QALY calculations in support of HTA-informed coverage decisions in the Philippines.

Risk of ageism in the use of cost-effectiveness thresholds in the recommendations of the national commission for incorporation of technologies in the Brazilian Unified Health System

Government agencies perform health technology assessment when evaluating requests to incorporate technologies in public health systems. To promote participation in this decision-making process, the National Commission for the Incorporation of Technologies in the Unified Health System (CONITEC) makes its recommendations available for public consultation for 20 days, which may occasionally be reduced or extended. Recently, CONITEC published its recommendations about the use of cost-effectiveness thresholds in health care decision-making. When reviewing the criteria for alternative cost-effectiveness thresholds, given that they promote innovation and equity in the Brazilian Unified Health System, we realized that the criterion “diseases affecting individuals at the end of life” was excluded from the list. This viewpoint article is a request for CONITEC to reconsider this position. The report disregards technical aspects related to the use of quality-adjusted life years as a metric in patients with low life expectancy, indicating the potential to discriminate against older adults and ignore the practical considerations of international organizations on this topic.

Study protocol of EMPOWER: A cluster randomized trial of a multimodal eHealth intervention for promoting mental health in the workplace following a stepped wedge trial design.

Objective: This article describes the EMPOWER study, a controlled trial aiming to determine the effectiveness and cost-effectiveness of an eHealth intervention to prevent common health problems and reduce presenteeism and absenteeism in the workplace. Intervention: The EMPOWER intervention spans universal, secondary and tertiary prevention and consists of an eHealth platform delivered via a website and a smartphone app designed to guide employees throughout different modules according to their specific profiles. Design: A stepped-wedge cluster randomized trial will be implemented in four countries (Finland, Poland, Spain and UK) with employees from small and medium enterprises (SMEs) and public agencies. Companies will be randomly allocated in one of three groups with different times at which the intervention is implemented. The intervention will last 7 weeks. Employees will answer several questionnaires at baseline, pre- and post-intervention and follow-up. Outcome measures: The main outcome is presenteeism. Secondary outcomes include depression, anxiety, insomnia, stress levels, wellbeing and absenteeism. Analyses will be conducted at the individual level using the intention-to-treat approach and mixed models. Additional analyses will evaluate the intervention effects according to gender, country or type of company. Cost-effectiveness and cost-utility analyses [based on the use of quality-adjusted life-years (QALYS)] will consider a societal, employers’ and employees’ perspective.

The Methodological Quality and Challenges in Conducting Economic Evaluations of Newborn Screening: A Scoping Review.

Introduction: Cost-effectiveness (CEA) and cost–utility analyses (CUA) have become popular types of economic evaluations (EE) used for evidence-based decision-making in healthcare resource allocation. Newborn screening programs (NBS) can have significant clinical benefits for society, and cost-effectiveness analysis may help to select the optimal strategy among different screening programs, including the no-screening option, on different conditions. These economic analyses of NBS, however, are hindered by several methodological challenges. This study explored the methodological quality in recent NBS economic evaluations and analyzed the main challenges and strategies adopted by researchers to deal with them. Methods: A scoping review was conducted according to PRISMA methodology to identify CEAs and CUAs of NBS. The methodological quality of the retrieved studies was assessed quantitatively using a specific guideline for the quality assessment of NBS economic evaluations, by calculating a general score for each EE. Challenges in the studies were then explored using thematic analysis as a qualitative synthesis approach. Results: Thirty-five studies met the inclusion criteria. The quantitative analysis showed that the methodological quality of NBS economic evaluations was heterogeneous. Lack of clear description of items related to results, discussion, and discounting were the most frequent flaws. Methodological challenges in performing EEs of neonatal screenings include the adoption of a long time horizon, the use of quality-adjusted life years as health outcome measure, and the assessment of costs beyond the screening interventions. Conclusions: The results of this review can support future economic evaluation research, aiding researchers to develop a methodological guidance to perform EEs aimed at producing solid results to inform decisions for resource allocation in neonatal screening.

Appropriate frameworks for economic evaluation of end of life care: A qualitative investigation with stakeholders

Background: The use of quality-adjusted life years rests on the assertion that the objective of the health care system is to improve health. Aim: To elicit the views of expert stakeholders on the purpose and evaluation of supportive end of life care, and explore how different purposes of end of life care imply the need for different evaluative frameworks. Design: Semi-structured qualitative interviews, analysed through an economic lens using a constant comparative approach. Participants: Twenty professionals working in or visiting the United Kingdom or Republic of Ireland, with clinical experience and/or working as academics in health-related disciplines. Results: Four purposes of end of life care were identified from and are critiqued with the aid of the qualitative data: to improve health, to enable patients to die in their preferred place, to enable the patient to experience a good death, and to enable the patient to experience a good death, and those who are close to the patient to have an experience which is as free as possible from fear, stress and distress. Conclusion: Managing symptoms and reducing anxiety were considered to be core objectives of end of life care and fit with the wider health service objective of improving/maximising health. A single objective across the entire health system ensures consistency in the way that resource allocation is informed across that entire system. However, the purpose of care at the end of life is more complex, encompassing diverse and patient-centred objectives which we have interpreted as enabling the patient to experience a good death.

Bursting Bubbles? QALYs and Discrimination

The use of Quality-Adjusted Life Years (QALYs) in healthcare allocation has been criticized as discriminatory against people with disabilities. This article considers a response to this criticism from Nick Beckstead and Toby Ord. They say that even if QALYs are discriminatory, attempting to avoid discrimination – when coupled with other central principles that an allocation system should favour – sometimes leads to irrationality in the form of cyclic preferences. I suggest that while Beckstead and Ord have identified a problem, it is a misdiagnosis to lay it at the feet of an anti-discrimination principle. The problem in fact comes from a basic tension between respecting reasonable patient preferences and other ways of ranking treatment options. As such, adopting a QALY system does not solve the problem they identify.

Clinical decision analysis in perinatology

Clinical decision-making in perinatology involves trade-offs between two intricately related individuals - mother and fetus. Decision-making in perinatology is challenging due to competing interests of the mother and the fetus. Although decision analytic methods are increasingly used to develop processes for clinical and cost-effectiveness analyses in perinatology, there are no guidelines on the conduct and reporting of decision analysis studies that takes into account the complexities of the mother-fetus dyad. This article describes the basics of decision analysis and highlights areas that require special consideration in the perinatal context. It emphasizes the importance of obtaining patient preferences related to combined maternal-fetal health states, stresses the relevance of both maternal and offspring health outcomes over appropriate time horizons, and explains challenges around the use of quality-adjusted life years as an outcome measure in perinatology. It also provides insight into the complexities of dyad status in clinical and cost-effectiveness analyses in perinatology.

Quality-adjusted tooth years (QATY) as an outcome measure of periodontal treatment

Background The use of quality-adjusted life years (QALY) as an outcome measure of economic evaluations is well-established in the literature. A measure of dental utility analogous to QALY, the quality-adjusted tooth years (QATY), had been initiated but only met with limited success, partly because of its inability to compare across a variety of dental interventions. This study aimed to develop a simple approach to estimate QATY by using an established oral health-related quality of life instrument.

QUALITY-ADJUSTED LIFE-YEARS FOR THE ESTIMATION OF EFFECTIVENESS OF SCREENING PROGRAMS: A SYSTEMATIC LITERATURE REVIEW

The aim of this study was to identify and characterize studies that have used quality-adjusted life-years (QALYs) based on measurements of patients' health-related quality of life (HRQoL) as an indicator of effectiveness of screening programs. Systematic search of the literature until March 2010, using several electronic databases. Initial screening of articles based on abstracts, and evaluation of full-text articles were done by at least two of the authors. The search identified 1,610 articles. Based on review of abstracts, 431 full-text articles were obtained for closer inspection and, of these, 81 reported QALYs based on patient-derived data using a valid HRQoL assessment. The most frequently used method to assess HRQoL was Time Trade-Off (55 percent) followed by EQ-5D (26 percent). The most frequently studied medical conditions were malignant diseases (23 percent) followed by cardiovascular diseases (19 percent). All studies employed some kind of modeling with the Markov model being the most prevalent type (65 percent). Majority of the articles (59 percent) concluded that the screening program studied was cost-effective. The use of QALYs in the evaluation of screening programs has expanded during the last few years. However, only a minority of studies have used HRQoL data derived from patients, using direct or indirect valuation. Further investigation and harmonization of the methodology in evaluation of screening programs is needed to ensure better comparability across different screening programs.

Methods and issues associated with the use of quality-adjusted life-years

In this article, we will focus on how preferences and utilities are measured, including the strengths and limitations of various approaches, discuss their use in estimating quality-adjusted life-years (QALYs) and make some recommendations for further research. Preferences are either measured using direct (visual analog scale, time trade-off or standard gamble) or indirect methods. The most commonly used generic indirect measures include the Quality of Well-Being scale, EuroQol-5 Dimension, Health Utilities Index and Short Form-6 Dimension. Disease-specific preference measures are increasingly being developed and applied in studies as more sensitive measures of health status. Preference-based measures and QALY measurement need to be enhanced, and additional research is needed to improve scientific methods for estimating preferences for health assessment. Given the increased focus on comparative effectiveness research, QALYs have the potential for helping researchers, clinicians, health policy-makers and patients to understand the relative effectiveness of alternative interventions for treating medical conditions.

Commentary on: Quality-of-Life Evaluation of Patients Undergoing Lumbar Discectomy Using Short Form 36.

Dear Editor, Farzanegan et al. have presented an important and interesting study looking at the patient reported outcomes using the SF-36 after lumbar discectomy for low back pain (1). This is an important study because it uses patient reported outcomes to evaluate a common problem and a common intervention. In addition the SF-36 can now be used to evaluate any medical intervention and convert that change in to quality adjusted life years (QALYs). The use of QALYs allows comparison of the treatment benefit across different medical conditions. When combined with cost data, a cost per QALY can be determined. Given limited resources and nearly unlimited demands, this concept allows for the rationale allocation of medical resources in order to achieve the greatest benefit. Different societies and different health care systems will have different thresholds to determine what interventions are cost effective for them, but this is clearly the emerging trend. There are several limitations of this study. The first limitation is that we do not have sufficient detail to really understand the selection process for the patients included versus those excluded from this study. Were they consecutive patients or some sort of convenience sample? The next limitation is understanding what their pre-operative treatment regimen was. Presumably it was usual care for their locale. The next consideration is that the authors have described the procedure as discectomy for low back pain. The most well accepted indication for discectomy is radiculopathy rather than an axial pain pattern. Finally this is simply a cohort treatment study without a comparator group. Cohort studies almost always demonstrate a greater treatment effect size than do randomized controlled trials. Presuming that the cohort had failed usual therapy, an alternative treatment strategy might include cognitive behavioral therapy as advocated by Fairbanks (BMJ 2005) (2). This demonstrated a significant effect size on what might be a comparable cohort. Similarly Brox and colleagues have demonstrated no incremental benefit of fusion compared to cognitive therapy for patients with chronic low back pain (3-5). So the intriguing aspect of this report is that the patients receiving a lesser intervention than fusion (discectomy) had significant improvement. So we are left with the question of why do these results appear so much better? Is it the patient selection criteria? It appears from the paper that patients had pain for > 3 months. It appears from the SPORT study (Rihn 2011) that duration of symptoms might be a prognostic factor (6). So if the intervention was performed relatively early it may have greater benefit. The challenge to this concept is what is the natural history of these patients and how many would have gotten how much better without the surgery? Recently the SPORT study has clearly demonstrated the benefit of surgical treatment over usual care for lumbar disc herniation in patients with radiculopathy (Weinstein JAMA 2006). These results have been durable at 4 years (Weinstein Spine 2008) (7, 8). It is difficult to determine if the effect sizes are similar between the Farzanegan study and the SPORT study due to differences in reporting. The SPORT study reported SF36 data using the subscale of bodily pain and physical function. The Farzanegan study reported the SF 36 data using the composite physical component subscale which combines multiple items in a different way. If they would report their data in the same format as the SPORT trial, it would potentially provide some external validation of their results presuming that the Farzanegan study information is available. Finally and most importantly, the question of importance of the improvement to the patient must be taken into account. Here the concept of minimal clinically important difference (MCID) and substantial clinical benefit (SCB) need to be considered. MCID is the minimum change (improvement) necessary for the patient to be able to tell that they are better (above the signal to noise ratio) (9-11). The SCB is the amount of improvement necessary for the patient to consider the intervention. So MCID is a minimum improvement whereas SCB is the targeted improvement. The MCID for SF 36 PCS is 5.4 points. It appears that these patients did achieve MCID. The authors have reported mean change scores, but it would be important to report the number and percentage of patients achieving MCID rather than just men changes. Similarly for SCB the SF 36 PCS is 6.2. I would encourage the authors to present their data in the public domain addressing the above points. If they are able to do so, they may open a new chapter on appropriate intervention for low back pain in patients with lumbar disc herniations.

Deriving Health Utility Values From a Health-Related Quality of Life Instrument in Non-Hodgkin Lymphoma Patients

Abstract 2065Health-related quality of life (HRQOL) is an important measure of health outcome in patients with non-Hodgkin lymphoma (NHL). Cost-effectiveness analyses incorporate health utility, a preference-based summary measure of HRQOL, through the use of quality-adjusted life years (QALYs). However, health utility scores are elicited using generic HRQOL instruments that are not commonly employed, since cancer specific HRQOL instruments generally provide more clinically relevant information. The EORTC QLQ-C30 is a multidimensional instrument designed to evaluate HRQOL in cancer patients, which is summarized using 15 separate scores. The EQ-5D tool, used to determine health utility values, asks patients to rate five domains of health on three different levels. Two hundred forty-three different health states are represented with this instrument, and each health state is converted into a single utility value on a scale anchored at 0 (representing death) and 1 (representing full health), based on societal valuations. The purpose of this study was to develop an algorithm to convert cancer specific HRQOL data obtained from the QLQ-C30 instrument in non-Hodgkin lymphoma (NHL) patients into health utility values elicited from the EQ-5D.NHL patients undergoing chemotherapy at Sunnybrook Health Sciences Centre in Ontario, Canada completed both the QLQ-C30 and EQ-5D questionnaires on each day they attended the clinic to receive a chemotherapy cycle. Fifteen summary scores were calculated from the QLQ-C30 instrument, and health utility values were assigned. A linear regression model was used to quantify the relationship between EQ-5D utility scores and QLQ-C30 summary scores. The QLQ-C30 summary scores were the predictor variables in the model and the utility score was the dependent variable. The final model was established using backward variable elimination with the Akaike Information Criterion (AIC). The predictive ability of the final model was tested using 10-fold cross validation, a technique in which data are divided into ten equal samples and each sample is used once to validate the model while the remaining nine samples are used to fit the model.Fifty-three patients participated in this study, and provided a total of 269 completed QLQ-C30 and EQ-5D questionnaires that were included in the analysis. The mean age of study patients was 61.4 years and 58% were female. 77% of patients had a diagnosis of the diffuse large B-cell subtype of NHL. The final model included four QLQ-C30 summary scores: physical (p<0.001), emotional (p<0.001), cognitive (p=0.06), and pain (p<0.001). Table 1 summarizes actual and predicted utility scores. Predicted utility scores were based on the results of the cross validation. The mean absolute error between predicted and actual utility scores was 0.07.Table 1:Summary measures for actual and predicted health utility scoresStatisticActualPredictedDifference*Mean ± standard deviation0.84 ± 0.160.84 ± 0.130.00 ± 0.09Median0.830.870.0195% confidence interval for the mean (based on 3000-replicate bootstrap)[0.82, 0.86][0.83, 0.86][−0.01, 0.01]*Predicted minus Actual, by patientThis analysis demonstrates that HRQOL data collected from NHL patients using the EORTC QLQ-C30, a multidimensional, non-preference-based instrument, can be converted into preference-based data suitable for use in cost-effectiveness analyses. Disclosures:Lathia:Amgen Canada: Research Funding. Mittmann:Amgen Canada: Research Funding.

The Use of Quality-Adjusted Life-Years in the Economic Evaluation of Health Technologies in Spain: A Review of the 1990–2009 Literature

Objective To appraise economic evaluations of health technologies that included quality-adjusted life-years (QALYs) as an outcome measure conducted over the past 20 years in Spain. Methods A systematic review of the literature was conducted. Economic evaluations that included QALYs as an outcome measure, conducted in Spain and published between January 1990 and December 2009 were identified. Primary and gray literature sources were reviewed. Results A total of 60 articles and 4 health technology assessment reports were included. Key findings were 1) the vast majority of articles (77.1%) referred to therapeutic interventions; 2) 63.2% dealt with pharmaceutical products and much fewer with preventive strategies, medical devices, or diagnostic interventions; 3) most evaluations referred to cardiovascular- (19.8%), respiratory- (16.3%), and cancer- (13.0%) related processes; 4) 80.3% were based on a theoretical model, most commonly Markov models (71.4%); 5) 67.3% adopted the National Health System perspective; 6) information on the methods used to describe the health states was given in 45.1% of studies; 7) 40.3% used the EuroQoL-5D to elicit preferences, whereas 66.1% gave no details on the methods applied to determine patients' choices; 8) it was possible to state who completed the questionnaires in only 17.7% of studies; 9) 77.1% of the interventions assessed were below the €30,000/QALY suggested affordable threshold in Spain. Conclusions An increasing number of economic evaluations using QALYs had been conducted. Most of them relied on theoretical models. Several methodological issues remain unsolved. Great disparity exists regarding the reporting of the methods used to determine health states and utility values.

QA3 DOES COST-EFFECTIVENESS ANALYSIS DISCRIMINATE AGAINST PATIENTS WITH SHORTER LIFE EXPECTANCY?

Does the use of quality-adjusted life-years (QALYs) in cost-effectiveness analyses (CEAs) of health care interventions necessarily discriminate against patients with short life expectancy compared with others? This paper reviews the arguments both that it does and that it does not, and demonstrates that whether the use of any time-dependent outcome measure in CEA will result in discrimination depends, in the context of any given choice between interventions, upon the choice of cost-effectiveness ‘threshold’ adopted by the decision maker, whether the incremental cost-effectiveness ratio (ICER) of the intervention for a subgroup of patients with relatively short life expectancy lies above the cost-effectiveness threshold, and whether the ICER for a subgroup of patients with longer life expectancy falls below the cost-effectiveness threshold. For discrimination to result against such patients requires that the long term ratio of costs to QALYs associated with the intervention be lower than the short term ratio of costs to QALYs. The implications for agencies which use CEA as part of their decision making are then discussed.

Bridging the gap between methods research and the needs of policy makers: A review of the research priorities of the National Institute for Health and Clinical Excellence

The aim of this study was to establish a list of priority topics for methods research to support decision making at the National Institute for Health and Clinical Excellence (NICE). Potential priorities for methods research topics were identified through a focused literature review, interviews, an email survey, a workshop and a Web-based feedback exercise. Participants were members of the NICE secretariat and its advisory bodies, representatives from academia, industry, and other organizations working closely with NICE. The Web exercise was open to anyone to complete but publicized among the above groups. A list of potential topics was collated. Priorities for further research differed according to the type of respondent and the extent to which they work directly with NICE. Priorities emerging from the group closest to NICE included: methodology for indirect and mixed treatment comparisons; synthesis of qualitative evidence; research relating to the use of quality-adjusted life-years (QALYs) in decision making; methods and empirical research for establishing the cost-effectiveness threshold; and determining how data on the uncertainty of effectiveness and cost-effectiveness data should be taken into account in the decision-making process. Priorities emerging from the broadest group of respondents (through the Web exercise) included: methods for extrapolating beyond evidence observed in trials, methods for capturing benefits not included in the QALY and methods to assess when technologies should be recommended in the context of further evidence gathering. Consideration needs to be given to the needs of those who use the outputs of research for decision making when determining priorities for future methods research.

A quantitative evaluation of the regulatory assessment of the benefits and risks of rofecoxib relative to naproxen: an application of the incremental net-benefit framework

To undertake a quantitative benefit-risk analysis of rofecoxib relative to naproxen using an incremental net-benefit (INB) analysis from the societal perspective, using the same data evaluated by the Health Canada and US FDA expert advisory panels. We developed a discrete event simulation model to calculate the INB of rofecoxib relative to naproxen in arthritis patients over a 1-year time horizon. All outcomes were weighted using societal utilities for each health state which facilitated the use of quality-adjusted life years (QALYs) as the outcome. Probability distributions were incorporated for each model parameter to facilitate a probabilistic analysis using second-order Monte Carlo simulation. In the base case analysis, the mean INB (SD) of rofecoxib relative to naproxen was 0.0002 (0.415) QALYs per patient over 12 months of treatment, or 0.2 QALYs per 1000 patients treated. The probabilistic sensitivity analysis resulted in a mean INB of 0.0022 QALYs (95%CI -0.0005, 0.0051). Overall, the INB associated with rofecoxib relative to naproxen was ≥0 in 94% of the iterations of the model. This analysis illustrates the application of the incremental net-benefit framework to quantitative benefit-risk evaluation, and suggests that the potential benefits of rofecoxib outweigh the potential harms relative to naproxen over 1 year from the societal perspective under the assumptions of this model.

Is The United States Ready For QALYs?

Quality-adjusted life-years (QALYs) are used in cost-effectiveness analyses to aid coverage and reimbursement decisions worldwide. QALYs provide a flexible and convenient metric for measuring and comparing health outcomes across diverse diseases and treatments. But their use has stirred controversy about how accurately they reflect preferences for health care and whether their use is fair. We review the debate and the use of QALYs in other countries and discuss prospects for using them in the U.S. health care system. Strict adherence to a QALY approach is likely to prove unacceptable in the United States, but a more flexible use of QALYs could be beneficial.

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