Cost-effectiveness of alternative strategies for the initial medical management of non-ST elevation acute coronary syndrome: systematic review and decision-analytical modelling

Emerging Therapies for COVID-19: The Value of Information From More Clinical Trials

OBJECTIVES

The COVID-19 pandemic necessitates time-sensitive policy and implementation decisions regarding new therapies in the face of uncertainty. This study aimed to quantify consequences of approving therapies or pursuing further research: immediate approval, use only in research, approval with research (eg, emergency use authorization), or reject.

METHODS

Using a cohort state-transition model for hospitalized patients with COVID-19, we estimated quality-adjusted life-years (QALYs) and costs associated with the following interventions: hydroxychloroquine, remdesivir, casirivimab-imdevimab, dexamethasone, baricitinib-remdesivir, tocilizumab, lopinavir-ritonavir, interferon beta-1a, and usual care. We used the model outcomes to conduct cost-effectiveness and value of information analyses from a US healthcare perspective and a lifetime horizon.

RESULTS

Assuming a $100 000-per-QALY willingness-to-pay threshold, only remdesivir, casirivimab-imdevimab, dexamethasone, baricitinib-remdesivir, and tocilizumab were (cost-) effective (incremental net health benefit 0.252, 0.164, 0.545, 0.668, and 0.524 QALYs and incremental net monetary benefit $25 249, $16 375, $54 526, $66 826, and $52 378). Our value of information analyses suggest that most value can be obtained if these 5 therapies are approved for immediate use rather than requiring additional randomized controlled trials (RCTs) (net value $20.6 billion, $13.4 billion, $7.4 billion, $54.6 billion, and $7.1 billion), hydroxychloroquine (net value $198 million) is only used in further RCTs if seeking to demonstrate decremental cost-effectiveness and otherwise rejected, and interferon beta-1a and lopinavir-ritonavir are rejected (ie, neither approved nor additional RCTs).

CONCLUSIONS

Estimating the real-time value of collecting additional evidence during the pandemic can inform policy makers and clinicians about the optimal moment to implement therapies and whether to perform further research.

Antidepressant-like activity of venlafaxine and clonidine in mice exposed to single prolonged stress - A model of post-traumatic stress disorder. Pharmacodynamic and molecular docking studies

BACKGROUND

Post-traumatic stress disorder (PTSD) is a growing issue worldwide characterized by stress and anxiety in response to re-experiencing traumatic events which strongly impair patient's quality of life and social functions. Available antidepressant and anxiolytic drugs are not efficacious in the majority of treated individuals. This necessitates a significant medical demand to develop novel therapeutic strategies for PTSD.

EXPERIMENTAL APPROACH

Animal model of PTSD was induced using a mouse single prolonged stress protocol (mSPS). To assess the activity of venlafaxine and clonidine, the forced swim test (FST) was used repeatedly 24h, 3days, 8days, 15days and 25days after mSPS. To get insight into a possible mechanism of anti-PTSD action, molecular docking procedure was utilized for the most active drug. This in silico part comprised molecular docking of enantiomers of venlafaxine to human transporters for serotonin (hSERT), norepinephrine (hNET) and dopamine (hDAT).

KEY RESULTS

In mSPS-subjected mice FST revealed the effectiveness of venlafaxine, however in non SPS-subjected mice both venlafaxine and clonidine were active. Molecular docking studies indicated that the affinity of venlafaxine to monoamine transporters is growing in the following rank order: hDAT<hNET<hSERT. Both venlafaxine enantiomers present different selectivity and binding mode.

CONCLUSION AND IMPLICATIONS

Venlafaxine but not clonidine was effective in an animal model of PTSD. Its mechanism of action, i.e., SERT, NET and DAT inhibition indicates potential drug targets for PTSD treatment. We expect that these results will contribute to a broader application of VLX in PTSD patients.

Extrapolating Survival from Randomized Trials Using External Data: A Review of Methods

This article describes methods used to estimate parameters governing long-term survival, or times to other events, for health economic models. Specifically, the focus is on methods that combine shorter-term individual-level survival data from randomized trials with longer-term external data, thus using the longer-term data to aid extrapolation of the short-term data. This requires assumptions about how trends in survival for each treatment arm will continue after the follow-up period of the trial. Furthermore, using external data requires assumptions about how survival differs between the populations represented by the trial and external data. Study reports from a national health technology assessment program in the United Kingdom were searched, and the findings were combined with “pearl-growing” searches of the academic literature. We categorized the methods that have been used according to the assumptions they made about how the hazards of death vary between the external and internal data and through time, and we discuss the appropriateness of the assumptions in different circumstances. Modeling choices, parameter estimation, and characterization of uncertainty are discussed, and some suggestions for future research priorities in this area are given.

A pharmacoeconomic approach to assessing the costs and benefits of air quality interventions that improve health: a case study

OBJECTIVE

This paper explores the use of pharmacoeconomic methods of valuation to health impacts resulting from exposure to poor air quality. In using such methods, interventions that reduce exposure to poor air quality can be directly compared, in terms of value for money (or cost-effectiveness), with competing demands for finite resources, including other public health interventions.

DESIGN

Using results estimated as part of a health impact assessment regarding a West Yorkshire Low Emission Zone strategy, this paper quantifies cost-saving and health-improving implications of transport policy through its impact on air quality.

DATA SOURCE

Estimates of health-related quality of life and the National Health Service (NHS)/Personal Social Services (PSS) costs for identified health events were based on data from Leeds and Bradford using peer-reviewed publications or Office for National Statistics releases.

POPULATION

Inhabitants of the area within the outer ring roads of Leeds and Bradford.

MAIN OUTCOMES MEASURES

NHS and PSS costs and quality-adjusted life years (QALYs).

RESULTS

Averting an all-cause mortality death generates 8.4 QALYs. Each coronary event avoided saves £28 000 in NHS/PSS costs and generates 1.1 QALYs. For every fewer case of childhood asthma, there will be NHS/PSS cost saving of £3000 and a health benefit of 0.9 QALYs. A single term, low birthweight birth avoided saves £2000 in NHS/PSS costs. Preventing a preterm birth saves £24 000 in NHS/PSS costs and generates 1.3 QALYs. A scenario modelled in the West Yorkshire Low Emission Zone Feasibility Study, where pre-EURO 4 buses and HGVs are upgraded to EURO 6 by 2016 generates an annual benefit of £2.08 million and a one-off benefit of £3.3 million compared with a net present value cost of implementation of £6.3 million.

CONCLUSIONS

Interventions to improve air quality and health should be evaluated and where improvement of population health is the primary objective, cost-effectiveness analysis using a NHS/PSS costs and QALYs framework is an appropriate methodology.

The prognostic utility of tests of platelet function for the detection of 'aspirin resistance' in patients with established cardiovascular or cerebrovascular disease: a systematic review and economic evaluation

BACKGROUND

The use of aspirin is well established for secondary prevention of cardiovascular disease. However, a proportion of patients suffer repeat cardiovascular events despite being prescribed aspirin treatment. It is uncertain whether or not this is due to an inherent inability of aspirin to sufficiently modify platelet activity. This report aims to investigate whether or not insufficient platelet function inhibition by aspirin ('aspirin resistance'), as defined using platelet function tests (PFTs), is linked to the occurrence of adverse clinical outcomes, and further, whether or not patients at risk of future adverse clinical events can be identified through PFTs.

OBJECTIVES

To review systematically the clinical effectiveness and cost-effectiveness evidence regarding the association between PFT designation of 'aspirin resistance' and the risk of adverse clinical outcome(s) in patients prescribed aspirin therapy. To undertake exploratory model-based cost-effectiveness analysis on the use of PFTs.

DATA SOURCES

Bibliographic databases (e.g. MEDLINE from inception and EMBASE from 1980), conference proceedings and ongoing trial registries up to April 2012.

METHODS

Standard systematic review methods were used for identifying clinical and cost studies. A risk-of-bias assessment tool was adapted from checklists for prognostic and diagnostic studies. (Un)adjusted odds and hazard ratios for the association between 'aspirin resistance', for different PFTs, and clinical outcomes are presented; however, heterogeneity between studies precluded pooling of results. A speculative economic model of a PFT and change of therapy strategy was developed.

RESULTS

One hundred and eight relevant studies using a variety of PFTs, 58 in patients on aspirin monotherapy, were analysed in detail. Results indicated that some PFTs may have some prognostic utility, i.e. a trend for more clinical events to be associated with groups classified as 'aspirin resistant'. Methodological and clinical heterogeneity prevented a quantitative summary of prognostic effect. Study-level effect sizes were generally small and absolute outcome risk was not substantially different between 'aspirin resistant' and 'aspirin sensitive' designations. No studies on the cost-effectiveness of PFTs for 'aspirin resistance' were identified. Based on assumptions of PFTs being able to accurately identify patients at high risk of clinical events and such patients benefiting from treatment modification, the economic model found that a test-treat strategy was likely to be cost-effective. However, neither assumption is currently evidence based.

LIMITATIONS

Poor or incomplete reporting of studies suggests a potentially large volume of inaccessible data. Analyses were confined to studies on patients prescribed aspirin as sole antiplatelet therapy at the time of PFT. Clinical and methodological heterogeneity across studies precluded meta-analysis. Given the lack of robust data the economic modelling was speculative.

CONCLUSIONS

Although evidence indicates that some PFTs may have some prognostic value, methodological and clinical heterogeneity between studies and different approaches to analyses create confusion and inconsistency in prognostic results, and prevented a quantitative summary of their prognostic effect. Protocol-driven and adequately powered primary studies are needed, using standardised methods of measurements to evaluate the prognostic ability of each test in the same population(s), and ideally presenting individual patient data. For any PFT to inform individual risk prediction, it will likely need to be considered in combination with other prognostic factors, within a prognostic model.

STUDY REGISTRATION

This study is registered as PROSPERO 2012:CRD42012002151.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

USE OF VALUE OF INFORMATION IN UK HEALTH TECHNOLOGY ASSESSMENTS

Objectives: The aim of this study was to identify and critically appraise the use of Value of Information (VOI) analyses undertaken as part of health technology assessment (HTA) reports in England and Wales.

Methods: A systematic review of National Institute for Health Research (NIHR) funded HTA reports published between 2004 and 2013 identified the use of VOI methods and key analytical details in terms of: (i) types of VOI methodology used; (ii) parameters and key assumptions; and (iii) conclusions drawn in terms of the need for further research.

Results: A total of 512 HTA reports were published during the relevant timeframe. Of these, 203 reported systematic review and economic modeling studies and 25 of these had used VOI method(s). Over half of the twenty-five studies (n = 13) conducted both EVPI (Expected Value of Perfect Information) and EVPPI (Expected Value of Partial Perfect Information) analyses. Eight studies conducted EVPI analysis, three studies conducted EVPI, EVPPI, and EVSI (Expected Value of Sampling Information) analyses and one study conducted EVSI analysis only. The level of detail reporting the methods used to conduct the VOI analyses varied.

Conclusions: This review has shown that the frequency of the use of VOI methods is increasing at a slower pace compared with the published volume of HTA reports. This review also suggests that analysts reporting VOI method(s) in HTA reports should aim to describe the method(s) in sufficient detail to enable and encourage decision-makers guiding research prioritization decisions to use the potentially valuable outputs from quantitative VOI analyses.

A practical guide to value of information analysis

Value of information analysis is a quantitative method to estimate the return on investment in proposed research projects. It can be used in a number of ways. Funders of research may find it useful to rank projects in terms of the expected return on investment from a variety of competing projects. Alternatively, trialists can use the principles to identify the efficient sample size of a proposed study as an alternative to traditional power calculations, and finally, a value of information analysis can be conducted alongside an economic evaluation as a quantitative adjunct to the 'future research' or 'next steps' section of a study write up. The purpose of this paper is to present a brief introduction to the methods, a step-by-step guide to calculation and a discussion of issues that arise in their application to healthcare decision making. Worked examples are provided in the accompanying online appendices as Microsoft Excel spreadsheets.

Satisfying the needs of Japanese cancer patients: A comparative study of detailed and standard informed consent documents

Background

Simplified informed consent forms have been successful in improving patient satisfaction and decreasing patient anxiety. However, unsolved problems remain about whether these documents improve comprehension and satisfaction of patients with standard literacy skills.

Purposes

To investigate whether a detailed consent form explaining the key elements of informed consent, in comparison to a standard consent form, would increase the comprehension and satisfaction of adult cancer patients.

Methods

Patients who were eligible for the National Surgical Adjuvant Study of Breast Cancer (protocol 01(N-SAS/BC-01)) were randomly selected to receive one of the following four versions: detailed document with graphics, detailed document without graphics, standard document with graphics, and standard document without graphics. The forms were written in plain language from the patients’ point of view. A total of 85 patients were administered questionnaires via interview to assess levels of comprehension, satisfaction, and anxiety.

Results

Patients demonstrated a strong understanding of information regarding treatment and research. Patient comprehension did not differ significantly between the detailed document arms and the standard document arms. Patient satisfaction level increased according to the amount of information presented in the consent form; most patients preferred the detailed document with graphics. Anxiety and accrual rates in the parent study were not affected by informed consent procedures.

Limitations

Findings were limited to adults who had standard literacy skills and may not be generalizable to a population with lower literacy.

Conclusion

Informed consent can be a significant experience for a population with standard literacy skills, as long as the document is easily comprehensible. Such information should be provided in a format that corresponds with patient needs, education levels, and preferences.

A systematic and critical review of the evolving methods and applications of value of information in academia and practice

OBJECTIVE

This article provides a systematic and critical review of the evolving methods and applications of value of information (VOI) in academia and practice and discusses where future research needs to be directed.

METHODS

Published VOI studies were identified by conducting a computerized search on Scopus and ISI Web of Science from 1980 until December 2011 using pre-specified search terms. Only full-text papers that outlined and discussed VOI methods for medical decision making, and studies that applied VOI and explicitly discussed the results with a view to informing healthcare decision makers, were included. The included papers were divided into methodological and applied papers, based on the aim of the study.

RESULTS

A total of 118 papers were included of which 50 % (n = 59) are methodological. A rapidly accumulating literature base on VOI from 1999 onwards for methodological papers and from 2005 onwards for applied papers is observed. Expected value of sample information (EVSI) is the preferred method of VOI to inform decision making regarding specific future studies, but real-life applications of EVSI remain scarce. Methodological challenges to VOI are numerous and include the high computational demands, dealing with non-linear models and interdependency between parameters, estimations of effective time horizons and patient populations, and structural uncertainties.

CONCLUSION

VOI analysis receives increasing attention in both the methodological and the applied literature bases, but challenges to applying VOI in real-life decision making remain. For many technical and methodological challenges to VOI analytic solutions have been proposed in the literature, including leaner methods for VOI. Further research should also focus on the needs of decision makers regarding VOI.

Relative cost effectiveness of the SPHERE intervention in selected patient subgroups with existing coronary heart disease

Heterogeneity exists within the patient population with coronary heart disease and the cost effectiveness of treatment may vary across subgroups within the overall population. This study compares the cost effectiveness of a secondary prevention intervention for a combined patient population relative to three selected subgroups: patients aged over 70 years; patients with a diagnosis other than angina only (that is, patients with a history of myocardial infarction, coronary artery bypass graft and/or percutaneous transluminal coronary angioplasty); and patients with diabetes. The results for the general population have been published elsewhere, but ongoing budget constraints require consideration of the appropriateness of targeting resources to patient subgroups. We adopt a probabilistic model to combine within trial and beyond trial impacts of treatment to estimate the lifetime health care costs and quality-adjusted life years of two primary care-based secondary prevention strategies: SPHERE Intervention--tailored practice and patient care plans and Control--standardised usual care. In all cases, the intervention was associated with mean cost savings and mean QALYs gains, when compared to the control, though statistical significance was never achieved. However, the probability of the intervention being cost effective was higher than 85% in all analyses across a range of potential cost-effectiveness threshold values. There is no compelling statistical evidence to support the targeting of specific subgroups across the general population. However, if affordability constraints are binding, the results do allow a tentative ranking of priorities based on the probabilistic subgroup analysis.

Using models to predict the future: what to do when the data run out?

Although clinical trials often provide "best evidence" comparing the effectiveness of alternative management strategies, such evidence can be limited in duration or in the results reported, causing clinicians and policy analysts to wonder "what if?" Models of the clinical prognosis-often spanning patients' lifetimes (the "long haul")-are perhaps weaker evidence, but can help answer questions about the management of individual patients and place that best evidence into the context of clinical reality.

The cost-effectiveness of the SPHERE intervention for the secondary prevention of coronary heart disease

Objectives: The Secondary Prevention of Heart disEase in geneRal practicE (SPHERE) trial has recently reported. This study examines the cost-effectiveness of the SPHERE intervention in both healthcare systems on the island of Ireland.

Methods: Incremental cost-effectiveness analysis. A probabilistic model was developed to combine within-trial and beyond-trial impacts of treatment to estimate the lifetime costs and benefits of two secondary prevention strategies: Intervention - tailored practice and patient care plans; and Control - standardized usual care.

Results: The intervention strategy resulted in mean cost savings per patient of €512.77 (95 percent confidence interval [CI], −1086.46–91.98) and an increase in mean quality-adjusted life-years (QALYs) per patient of 0.0051 (95 percent CI, −0.0101–0.0200), when compared with the control strategy. The probability of the intervention being cost-effective was 94 percent if decision makers are willing to pay €45,000 per additional QALY.

Conclusions: Decision makers in both settings must determine whether the level of evidence presented is sufficient to justify the adoption of the SPHERE intervention in clinical practice.

Assessing the cost effectiveness of using prognostic biomarkers with decision models: case study in prioritising patients waiting for coronary artery surgery

OBJECTIVE

To determine the effectiveness and cost effectiveness of using information from circulating biomarkers to inform the prioritisation process of patients with stable angina awaiting coronary artery bypass graft surgery.

DESIGN

Decision analytical model comparing four prioritisation strategies without biomarkers (no formal prioritisation, two urgency scores, and a risk score) and three strategies based on a risk score using biomarkers: a routinely assessed biomarker (estimated glomerular filtration rate), a novel biomarker (C reactive protein), or both. The order in which to perform coronary artery bypass grafting in a cohort of patients was determined by each prioritisation strategy, and mean lifetime costs and quality adjusted life years (QALYs) were compared.

DATA SOURCES

Swedish Coronary Angiography and Angioplasty Registry (9935 patients with stable angina awaiting coronary artery bypass grafting and then followed up for cardiovascular events after the procedure for 3.8 years), and meta-analyses of prognostic effects (relative risks) of biomarkers.

RESULTS

The observed risk of cardiovascular events while on the waiting list for coronary artery bypass grafting was 3 per 10,000 patients per day within the first 90 days (184 events in 9935 patients). Using a cost effectiveness threshold of pound20,000- pound30,000 (euro22,000-euro33,000; $32,000-$48,000) per additional QALY, a prioritisation strategy using a risk score with estimated glomerular filtration rate was the most cost effective strategy (cost per additional QALY was < pound410 compared with the Ontario urgency score). The impact on population health of implementing this strategy was 800 QALYs per 100,000 patients at an additional cost of pound 245,000 to the National Health Service. The prioritisation strategy using a risk score with C reactive protein was associated with lower QALYs and higher costs compared with a risk score using estimated glomerular filtration rate.

CONCLUSION

Evaluating the cost effectiveness of prognostic biomarkers is important even when effects at an individual level are small. Formal prioritisation of patients awaiting coronary artery bypass grafting using a routinely assessed biomarker (estimated glomerular filtration rate) along with simple, routinely collected clinical information was cost effective. Prioritisation strategies based on the prognostic information conferred by C reactive protein, which is not currently measured in this context, or a combination of C reactive protein and estimated glomerular filtration rate, is unlikely to be cost effective. The widespread practice of using only implicit or informal means of clinically ordering the waiting list may be harmful and should be replaced with formal prioritisation approaches.

Characterizing structural uncertainty in decision analytic models: a review and application of methods

BACKGROUND

The characterization of uncertainty is critical in cost-effectiveness analysis, particularly when considering whether additional evidence is needed. In addition to parameter and methodological uncertainty, there are other sources of uncertainty which include simplifications and scientific judgments that have to be made when constructing and interpreting a model of any sort. These have been classified in a number of different ways but can be referred to collectively as structural uncertainties.

MATERIALS AND METHODS

Separate reviews were undertaken to identify what forms these other sources of uncertainty take and what other forms of potential methods to explicitly characterize these types of uncertainties in decision analytic models. These methods were demonstrated through application to four decision models each representing one of the four types of uncertainty.

RESULTS

These sources of uncertainty fall into four general themes: 1) inclusion of relevant comparators; 2) inclusion of relevant events; 3) alternative statistical estimation methods; and 4) clinical uncertainty.Two methods to explicitly characterize such uncertainties were identified: model selection and model averaging. In addition, an alternative approach, adding uncertain parameters to represent the source of uncertainty was also considered.The applications demonstrate that cost-effectiveness may be sensitive to these uncertainties and the methods used to characterize them. The value of research was particularly sensitive to these uncertainties and the methods used to characterize it. It is therefore important, for decision-making purposes, to incorporate such uncertainties into the modeling process.

CONCLUSION

Only parameterizing the uncertainty directly in the model can inform the decision to conduct further research to resolve this source of uncertainty.

Using triple antiplatelet therapy in patients with non-ST elevation acute coronary syndrome managed invasively: a cost-effectiveness analysis

OBJECTIVES

To assess the incremental cost-effectiveness ratio (ICER) of glycoprotein IIb/IIIa (GPIIb/IIIa) inhibitors in patients with non-ST elevation acute coronary syndrome (NSTE-ACS) pretreated with aspirin and clopidogrel undergoing an early invasive treatment strategy.

METHODS

Cost-effectiveness analysis and cost-utility analysis were performed from a health-care system perspective, based on a Markov model with a time horizon of the patient life span. The risk of death and ischemic events was assessed using the Thrombolysis in Myocardial Infarction (TIMI) risk score. We compared three strategies: 1) routine upstream use of a GPIIb/IIIa inhibitor to all patients before angiography, 2) deferred selective use of abciximab in the catheterization laboratory just before angioplasty, and 3) double antiplatelet therapy without GPIIb/IIIa inhibitors. Both univariate sensitivity analysis and second-order probabilistic microsimulation were performed.

RESULTS

In the base case (65 years old, TIMI score 3), strategy A was the most effective, with an ICER of 15,150 euros per quality-adjusted life-year gained. Strategy B was dominated by a combination of strategies A and C. The ICER was very sensitive to the age and baseline risk of the patient. According to the widely accepted cost-effectiveness thresholds, strategy A would be cost-effective only in patients with an intermediate to high TIMI score, especially within the younger age groups. The probability that strategy A was cost-effective under the base case was 91.2%.

CONCLUSIONS

The use of GPIIb/IIIa inhibitors upstream in high-risk NSTE-ACS patients (TIMI score > or = 3) pretreated with aspirin and clopidogrel is cost-effective, particularly in the younger age groups.

Cost-effectiveness of clopidogrel: seeing through the smoke

BACKGROUND

The authors reviewed various recommendations and practices for cost-effectiveness analysis. They also performed a PubMed search for clopidogrel and cost-effectiveness from 2004 to early 2008 to obtain original analyses published in English to look for possible associations of assumptions and conclusions with reported pharmaceutical support.

RESULTS

. Inclusion of incident cases and truncation at a sensible follow-up time more appropriately reflect the burden to be assumed by third-party payers. Extending the time horizon too far runs the risk of decreasing any relation with future reality. Parsimony cannot justify simplifications that omit relevant issues such as noncoronary costs, which worsen the calculated cost-effectiveness ratio of clopidogrel by 5% to 27%. The choice of the population to be analyzed has a major effect on cost-effectiveness: pharmaceutically sponsored studies published between 2004 and early 2008 focused on high-risk patients and have routinely shown more favorable cost-effectiveness ratios for clopidogrel than studies without pharmaceutical support.

CONCLUSION

. Any entity hoping to make the cost-effectiveness ratio of clopidogrel look more favorable would prefer the isolated, cohort approach and limit the analysis to high-risk patients most likely to benefit from it. This approach ignores the reality of medical policies and does not address the most relevant questions regarding the optimum use of clopidogrel.

Priority setting for research in health care: an application of value of information analysis to glycoprotein IIb/Illa antagonists in non-ST elevation acute coronary syndrome

The purpose of this study is to explain the rationale for the value of information approach to priority setting for research and to describe the methods intuitively for those familiar with basic decision analytical modeling. A policy-relevant case study is used to show the feasibility of the method and to illustrate the type of output that is generated and how these might be used to frame research recommendations. The case study relates to the use of glycoprotein Ilb/Illa antagonists for the treatment of patients with non-ST elevation acute coronary syndrome. This is an area that recently has been appraised by the National Institute for Health and Clinical Excellence.