On the Use of Markov Models in Pharmacoeconomics: Pros and Cons and Implications for Policy Makers

Cost-effectiveness of incentives for physical activity in coronary heart disease in Germany: pre-trial health economic model of a complex intervention following the new MRC framework

Objectives

The German Incentives for Physical Activity in Cardiac Patients trial is a three-arm, randomised controlled trial for secondary prevention of coronary heart disease (CHD). Guidance for developing complex interventions recommends pre-trial health economic modelling. The aim of this study is to model the long-term cost-effectiveness of the incentive-based physical activity interventions in a population with CHD.

Methods

A decision-analytical Markov model was developed from a health services provider perspective, following a cohort aged 65 years with a previous myocardial infarction for 25 years. Monetary and social incentives were compared relative to no incentive. Intervention effects associated with physical activity were used to determine the costs, quality-adjusted life-years (QALYs) gained, incremental cost-effectiveness and cost-utility ratios. The probability of cost-effectiveness was calculated through sensitivity analyses.

Results

The incremental QALYs gained from the monetary and social incentives, relative to control, were respectively estimated at 0.01 (95% CI 0.00 to 0.01) and 0.04 (95% CI 0.02 to 0.05). Implementation of the monetary and social incentive interventions increased the costs by €874 (95% CI €744 to €1047) and €909 (95% CI €537 to €1625). Incremental cost-utility ratios were €25 912 (95% CI €15 056 to €50 210) and €118 958 (95% CI €82 930 to €196 121) per QALY gained for the social and monetary incentive intervention, respectively. With a willingness-to-pay threshold set at €43 000/QALY, equivalent to the per-capita gross domestic product in Germany, the probability that the social and monetary incentive intervention would be seen as cost-effective was 95% and 0%, respectively.

Conclusions

Exercise-based secondary prevention using inventive schemes may offer a cost-effective strategy to reduce the burden of CHD.

Patients with complete clinical response after neoadjuvant chemoradiotherapy for locally advanced esophageal cancer: A Markov decision analysis of esophagectomy versus active surveillance

OBJECTIVE

Chemoradiation followed by esophagectomy is a standard treatment option for patients with locally advanced esophageal cancer (LAEC). Esophagectomy is a high-risk procedure, and recent evidence suggests select patients may benefit from omitting or delaying surgery. This study aims to compare surgery versus active surveillance for LAEC patients with complete clinical response (cCR) after neoadjuvant chemoradiotherapy (nCRT).

METHODS

Decision analysis with Markov modeling was used. The base case was a 60-year-old man with T3N0M0 esophageal cancer with cCR after nCRT. The decision was modeled for a 5-year time horizon. Primary outcomes were life-years and quality-adjusted life-years (QALY). Probabilities and utilities were derived through the literature. Deterministic sensitivity analyses were performed using ranges from the literature with consideration for clinical plausibility.

RESULTS

Surgery was favored for survival with an expected life-years of 2.89 versus 2.64. After incorporating quality of life, active surveillance was favored, with an expected QALY of 1.70 versus 1.56. The model was sensitive to probability of recurrence on active surveillance (threshold value 0.598), probability of recurrence being resectable (0.318), and disutility of previous esophagectomy (-0.091). The model was not sensitive to perioperative morbidity and mortality.

CONCLUSIONS

Our study finds that surgery increases life expectancy but decreases QALY. Although the incremental change in QALY for either modality is insufficient to make broad clinical recommendations, our study demonstrates that either approach is acceptable. As probabilities of key factors are further defined in the literature, treatment decisions for patients with LAEC and a cCR after nCRT should consider histology, patient values, and quality of life.

Challenges with Estimating Long-Term Overall Survival in Extensive Stage Small-Cell Lung Cancer: A Validation-Based Case Study

Objective

The study aimed to explore methods and highlight the challenges of extrapolating the overall survival (OS) of immunotherapy-based treatment in first-line extensive stage small-cell lung cancer (ES-SCLC).

Methods

Standard parametric survival models, spline models, landmark models, mixture and non-mixture cure models, and Markov models were fitted to 2-year data of the CASPIAN Phase 3 randomised trial of PD-L1 inhibitor durvalumab added to platinum-based chemotherapy (NCT03043872). Extrapolations were compared with updated 3-year data from the same trial and the plausibility of long-term estimates assessed.

Results

All models used provided a reasonable fit to the observed Kaplan-Meier (K-M) survival data. The model which provided the best fit to the updated CASPIAN data was the mixture cure model. In contrast, the landmark analysis provided the least accurate fit to model survival. Estimated mean OS differed substantially across models and ranged from (in years) 1.41 (landmark model) to 4.81 (mixture cure model) for durvalumab plus etoposide and platinum and from 1.01 (landmark model) to 2.00 (mixture cure model) for etoposide and platinum.

Conclusion

While most models may provide a good fit to K-M data, it is crucial to assess beyond the statistical goodness-of-fit and consider the clinical plausibility of the long-term predictions. The more complex cure models demonstrated the best predictive ability at 3 years, potentially providing a better representation of the underlying method of action of immunotherapy; however, consideration of the models' clinical plausibility and cure assumptions need further research and validation. Our findings underscore the significance of adopting a clinical perspective when selecting the most appropriate approach to model long-term survival, particularly when considering the use of more complex models.

Cost-consequence analysis of continuous denosumab therapy for osteoporosis treatment in South Korea

BACKGROUND

Insurance reimbursement provisions in South Korea limit osteoporosis medication availability for patients with T-scores exceeding - 2.5. This study aimed to evaluate the financial impact and fracture prevention of continuous denosumab therapy until a T-score>-2.0 (Dmab-C strategy), versus discontinuation of denosumab after reaching T-score>-2.5 (Dmab-D strategy) in osteoporosis patients.

METHODS

A cost-consequence analysis from a Korean healthcare system perspective was performed using a newly developed Markov model. The incidence of vertebral and non-vertebral fracture, fracture-related deaths, drug costs, and fracture-treatment costs were estimated and compared between Dmab-C and Dmab-D strategy over a lifetime in eligible patients aged 55 years.

RESULTS

Base-case analysis revealed that Dmab-C prevented 32.21 vertebral fracture (VF) and 12.43 non-VF events per 100 patients over a lifetime, while reducing 1.29 fracture-related deaths. Lifetime direct healthcare cost saving per patient was KRW 1,354,655 if Dmab-C replaces Dmab-D. When productivity losses were considered, Dmab-C saved KRW 29,025,949 per patient compared to Dmab-D. The additional treatment costs of Dmab-C could be offset by the higher subsequent treatment costs and fracture treatment costs of Dmab-D. The sensitivity analysis showed consistent patterns with results of the base-case analysis.

CONCLUSION

Continuous treatment using denosumab until osteoporosis patients achieve and maintain a T-score of -2.0 would provide greater clinical and economic benefits in terms of fracture prevention and reduced mortality risks compared to outcomes from discontinuing treatment at a T-score of -2.5 or above. This new treatment strategy would effectively lower the risk of fractures and fracture-related mortality, ultimately leading to lower medical expenses.

Cost-effectiveness and resource use analysis of patients with asthma before and after treatment with mepolizumab in a real-life setting

OBJECTIVE

To define the cost-effectiveness and health resource use of mepolizumab in a cohort of patients with severe eosinophilic asthma in real-life conditions in Spain.

METHODS

This was an observational, retrospective, single-center study. Patients included were diagnosed with severe eosinophilic asthma and treated with mepolizumab 100 mg subcutaneous (SC) 4-weekly for 12 months. Outcomes evaluated: incremental cost-effectiveness ratio (ICER), number of exacerbations, disease control with the Asthma Control Test (ACT), Asthma Quality of Life Questionnaire (AQLQ), and direct and indirect cost per patient.

RESULTS

12 months after mepolizumab initiation, a significant decrease in exacerbations was shown, from a mean (standard deviation [SD]) of 3.1 (2.6) to 0.7 (1.5), an increase from 4.9 (0.4) to 6.1 (0.5) in AQLQ, and from 14.9 (5.7) to 21.5 (3.9) in ACT scores. The number of cortico-dependent patients significantly decreased from 53.3% to 13.3% during this period. There was a significant decrease of 94% in the cost of hospitalization, from a mean (SD) of €4063.9 (5423.9) pretreatment to €238.6 (1306.9) post-treatment (p = 0.0003). Total costs decreased significantly from a median of €2,423.1 (1,512.8; 9,320.9) pretreatment to €1,177.5 (965.0; 1,737.8) post-treatment if mepolizumab was excluded. ICER per exacerbation avoided was €3606.9, per 3-point ACT score increase €3934.8, and per 0.5-point AQLQ score increase €3606.9.

CONCLUSIONS

Mepolizumab improves control of asthma and quality of life in patients with severe diseases in a cost-effectiveness range. The number of exacerbations decreased, and there was a clear reduction in primary care visits and hospitalizations. Further economic analyses of biological therapies for asthma are required.

Clinical and economic evaluations of natalizumab, rituximab, and ocrelizumab for the management of relapsing-remitting multiple sclerosis in Saudi Arabia

INTRODUCTION

The advent of new disease-modifying therapies (DMTs), such as monoclonal antibodies (mAbs), resulted in significant changes in the treatment guidelines for Multiple sclerosis (MS) and improvement in the clinical outcomes. However, mAbs, such as rituximab, natalizumab, and ocrelizumab, are expensive with variable effectiveness rates. Thus, the present study aimed to compare the direct medical cost and consequences (e.g., clinical relapse, disability progression, and new MRI lesions) between rituximab and natalizumab in managing relapsing-remitting multiple sclerosis (RRMS) in Saudi Arabia. Also, the study aimed to explore the cost and consequence of ocrelizumab in managing RRMS as a second-choice treatment.

METHODS

The electronic medical records (EMRs) of patients with RRMS were retrospectively reviewed to retrieve the patients' baseline characteristics and disease progression from two tertiary care centers in Riyadh, Saudi Arabia. Biologic-naïve patients treated with rituximab or natalizumab or those switched to ocrelizumab and treated for at least six months were included in the study. The effectiveness rate was defined as no evidence of disease activity (NEDA-3) (i.e., absence of new T2 or T1 gadolinium (Gd) lesions as demonstrated by the Magnetic Resonance Imaging (MRI), disability progression, and clinical relapses), while the direct medical costs were estimated based on the utilization of healthcare resources. In addition, bootstrapping with 10,000 replications and inverse probability weighting based on propensity score were conducted.

RESULTS

Ninety-three patients met the inclusion criteria and were included in the analysis (natalizumab (n = 50), rituximab (n = 26), ocrelizumab (n = 17)). Most of the patients were otherwise healthy (81.72%), under 35 years of age (76.34%), females (61.29%), and on the same mAb for more than one year (83.87%). The mean effectiveness rates for natalizumab, rituximab, and ocrelizumab were 72.00%, 76.92%, and 58.83%, respectively. Natalizumab mean incremental cost compared to rituximab was $35,383 (95% CI: $25,401.09- $49,717.92), and its mean effectiveness rate was 4.92% lower than rituximab (95% CI: -30-27.5) with 59.41% confidence level that rituximab will be dominant.

CONCLUSIONS

Rituximab seems to be more effective and is less costly than natalizumab in the management of RRMS. Ocrelizumab does not seem to slow the rates of disease progression among patients previously treated with natalizumab.

How to Predict Drug Expenditure: A Markov Model Approach with Risk Classes

BACKGROUND

Although pharmaceutical expenditures have been rising for decades, the question of their drivers remains unclear, and long-term projections of pharmaceutical spending are still scarce. We use a Markov approach considering different cost-risk groups to show the possible range of future drug spending in Germany and illustrate the influence of various determinants on pharmaceutical expenditure.

METHODS

We compute different medium and long-term projections of pharmaceutical expenditure in Germany up to 2060 and compare extrapolations with constant shares, time-to-death scenarios, and Markov modeling based on transition probabilities. Our modeling is based on data from a large statutory sickness fund covering around four million insureds. We divide the population into six risk groups according to their share of total pharmaceutical expenditures, determine their cost growth rates, survival and transition probabilities, and compute different scenarios related to changes in life expectancy or spending trends in different cost-risk groups.

RESULTS

If the spending trends in the high-cost groups continue, per-capita expenditure will increase by over 40% until 2040. By 2060, pharmaceutical expenditures could more than double, even if these groups would not benefit from rising life expectancy. By contrast, the isolated effect of demographic change would "only" lead to a long-term increase of around 15%.

CONCLUSION

The long-term development of pharmaceutical spending in Germany will depend mainly on future expenditure and life expectancy trends of particularly high-cost patients. Thus, appropriate pricing of new expensive pharmaceuticals is essential for the sustainability of the German healthcare system.

Economic Evaluation of Oral Cancer Screening Programs: Review of Outcomes and Study Designs

A lack of guidance on economic evaluations for oral cancer screening programs forms a challenge for policymakers and researchers to fill the knowledge gap on their cost-effectiveness. This systematic review thus aims to compare the outcomes and design of such evaluations. A search for economic evaluations of oral cancer screening was performed on Medline, CINAHL, Cochrane, PubMed, health technology assessment databases, and EBSCO Open Dissertations. The quality of studies was appraised using QHES and the Philips Checklist. Data abstraction was based on reported outcomes and study design characteristics. Of the 362 studies identified, 28 were evaluated for eligibility. The final six studies reviewed consisted of modeling approaches (n = 4), a randomized controlled trial (n = 1), and a retrospective observational study (n = 1). Screening initiatives were mostly shown to be cost-effective compared to non-screening. However, inter-study comparisons remained ambiguous due to large variations. The observational and randomized controlled trials provided considerably accurate evidence of implementation costs and outcomes. Modeling approaches, conversely, appeared more feasible for the estimation of long-term consequences and the exploration of strategy options. The current evidence of the cost-effectiveness of oral cancer screening remains heterogeneous and inadequate to support its institutionalization. Nevertheless, evaluations incorporating modeling methods may provide a practical and robust solution.

Optimising the current model of care for knee osteoarthritis with the implementation of guideline recommended non-surgical treatments: a model-based health economic evaluation

AIMS OF THE STUDY

Structured exercise, education, weight management and painkiller prescription are guideline recommended non-surgical treatments for patients suffering from knee osteoarthritis. Despite its endorsement, uptake of guideline recommended non-surgical treatments remains low. It is unknown whether the implementation of these treatments into the current model of care for knee osteoarthritis would be cost-effective from a Swiss statutory healthcare perspective. We therefore aimed to (1) assess the incremental cost-effectiveness ratio of an optimised model of care incorporating guideline recommended non-surgical treatments in adults with knee osteoarthritis and (2) the effect of total knee replacement (TKR) delay with guideline recommended non-surgical treatments on the cost-effectiveness of the overall model of care.

METHODS

A Markov model from the Swiss statutory healthcare perspective was used to compare an optimised model of care incorporating guideline recommended non-surgical treatments versus the current model of care without standardised guideline recommended non-surgical treatments. Costs were derived from two Swiss health insurers, a national database, and a reimbursement catalogue. Utility values and transition probabilities were extracted from clinical trials and national population data. The main outcome was the incremental cost-effectiveness ratio for three scenarios: "base case" (current model of care vs optimised model of care with no delay of total knee replacement), "two-year delay" (current model of care vs optimised model of care + two-year delay of total knee replacement) and "five-year delay" (current model of care vs optimised model of care + five-year delay of total knee replacement). Costs and utilities were discounted at 3% per year and a time horizon of 70 years was chosen. Probabilistic sensitivity analyses were conducted.

RESULTS

The "base case" scenario led to 0.155 additional quality-adjusted life years (QALYs) per person at an additional cost per person of CHF 341 (ICER = CHF 2,203 / QALY gained). The "two-year delay" scenario led to 0.134 additional QALYs and CHF -14 cost per person. The "five-year delay" scenario led to 0.118 additional QALYs and CHF -501 cost per person. Delay of total knee replacement by two and five years led to an 18% and 36% reduction of revision surgeries, respectively, and had a cost-saving effect.

CONCLUSION

According to this Markov model, the optimisation of the current model of care by implementing guideline recommended non-surgical treatments would likely be cost-effective from a statutory healthcare perspective. If implementing guideline recommended non-surgical treatments delays total knee replacement by two or five years, the amount of revision surgeries may be reduced.

Ultrasound examination, MRI, or ROMA for discriminating between inconclusive adnexal masses as determined by IOTA Simple Rules: a prospective study

OBJECTIVE

To determine the best second-step approach for discriminating benign from malignant adnexal masses classified as inconclusive by International Ovarian Tumour Analysis Simple Rules (IOTA-SR).

METHODS

Single-center prospective study comprising a consecutive series of patients diagnosed as having an adnexal mass classified as inconclusive according to IOTA-SR. All women underwent Risk of Ovarian Malignancy Algorithm (ROMA) analysis, MRI interpreted by a radiologist, and ultrasound examination by a gynecological sonologist. Cases were clinically managed according to the result of the ultrasound expert examination by either serial follow-up for at least 1 year or surgery. Reference standard was histology (patient was submitted to surgery if any of the tests was suspicious) or follow-up (masses with no signs of malignancy after 12 months were considered benign). Diagnostic performance of all three approaches was calculated and compared. Direct cost analysis of the test used was also performed.

RESULTS

Eighty-two adnexal masses in 80 women (median age 47.6 years, range 16 to 73 years) were included. Seventeen patients (17 masses) were managed expectantly (none had diagnosis of ovarian cancer after at least 12 months of follow-up) and 63 patients (65 masses) underwent surgery and tumor removal (40 benign and 25 malignant tumors). Sensitivity and specificity for ultrasound, MRI, and ROMA were 96% and 93%, 100% and 81%, and 24% and 93%, respectively. The specificity of ultrasound was better than that for MRI (p=0.021), and the sensitivity of ultrasound was better than that for ROMA (p<0.001), sensitivity was better for MRI than for ROMA (p<0.001) and the specificity of ROMA was better than that for MRI (p<0.001). Ultrasound evaluation was the most effective and least costly method as compared with MRI and ROMA.

CONCLUSION

In this study, ultrasound examination was the best second-step approach in inconclusive adnexal masses as determined by IOTA-SR, but the findings require confirmation in multicenter prospective trials.

Cost effectiveness analyses of pharmacological treatments in heart failure

In a rapidly growing and aging population, heart failure (HF) has become recognised as a public health concern that imposes high economic and societal costs worldwide. HF management stems from the use of highly cost-effective angiotensin converting enzyme inhibitors (ACEi) and β-blockers to the use of newer drugs such as sodium-glucose cotransporter-2 inhibitors (SGLT2i), ivabradine, and vericiguat. Modelling studies of pharmacological treatments that report on cost effectiveness in HF is important in order to guide clinical decision making. Multiple cost-effectiveness analysis of dapagliflozin for heart failure with reduced ejection fraction (HFrEF) suggests that it is not only cost-effective and has the potential to improve long-term clinical outcomes, but is also likely to meet conventional cost-effectiveness thresholds in many countries. Similar promising results have also been shown for vericiguat while a cost effectiveness analysis (CEA) of empagliflozin has shown cost effectiveness in HF patients with Type 2 diabetes. Despite the recent FDA approval of dapagliflozin and empagliflozin in HF, it might take time for these SGLT2i to be widely used in real-world practice. A recent economic evaluation of vericiguat found it to be cost effective at a higher cost per QALY threshold than SGLT2i. However, there is a lack of clinical or real-world data regarding whether vericiguat would be prescribed on top of newer treatments or in lieu of them. Sacubitril/valsartan has been commonly compared to enalapril in cost effectiveness analysis and has been found to be similar to that of SGLT2i but was not considered a cost-effective treatment for heart failure with reduced ejection fraction in Thailand and Singapore with the current economic evaluation evidences. In order for more precise analysis on cost effectiveness analysis, it is necessary to take into account the income level of various countries as it is certainly easier to allocate more financial resources for the intervention, with greater effectiveness, in high- and middle-income countries than in low-income countries. This review aims to evaluate evidence and cost effectiveness studies in more recent HF drugs i.e., SGLT2i, ARNi, ivabradine, vericiguat and omecamtiv, and gaps in current literature on pharmacoeconomic studies in HF.

Cost-effectiveness analysis of house dust mite allergen immunotherapy in children with allergic asthma

BACKGROUND

Cost-effectiveness studies evaluating allergen immunotherapy (AIT) in children are limited but needed to drive clinical and policy-making decisions such as reimbursement of new interventions. In this study, we compared the cost effectiveness of subcutaneous (SCIT) and sublingual immunotherapy (SLIT) tablets to the standard of care (SOC) treatment in children with house dust mite-driven (HDM) allergic asthma.

METHODS

We developed a hypothetical Markov model based on the Global Initiative for Asthma (GINA) severity steps to compare the three strategies over a 10-year horizon divided by cycles of 6 months. SOC was used as a reference to calculate the incremental cost-effectiveness ratio (ICER). Deterministic and probabilistic sensitivity analyses were used to assess models' uncertainty. Other scenarios were evaluated to strengthen the presentation of results.

RESULTS

The ICER for SCIT and SLIT tablets was 1281€ and 7717€, respectively. The cost-effectiveness threshold for Portugal was 18,482.80€; both treatment approaches were below this limit. The major contributors to these results were the AIT effects on reducing moderate and severe exacerbations and asthma controller medication. In the sensitivity analysis, SCIT revealed a higher probability of cost-effectiveness than SLIT. When including allergic rhinitis as comorbidity, ICER values reduced markedly, especially for SCIT intervention.

CONCLUSIONS

AIT was cost effective in children with HDM-driven allergic asthma, especially when given by the subcutaneous route. The high probability of cost effectiveness, especially for SCIT, may drive future policy decisions and AIT-prescribing habits. AIT adherence greatly influenced the results highlighting the value of implementing strategies to promote adherence rates.

Cost-Utility Analysis of Pharmacogenetic Testing Based on CYP2C19 or CYP2D6 in Major Depressive Disorder: Assessing the Drivers of Different Cost-Effectiveness Levels from an Italian Societal Perspective

Background and Objectives

Major depressive disorder (MDD) is a common and severe psychiatric disorder that has enormous economical and societal costs. As pharmacogenetics is one of the key tools of precision psychiatry, we analyze the cost–utility of test screening of CYP2C19 and CYP2D6 for patients suffering from major depressive disorder (MDD) and try to understand the main drivers that influence the cost–utility.

Methods

We developed two pharmacoeconomic nonhomogeneous Markov models to test the cost–utility, from an Italian societal perspective, of pharmacogenetic testing genetic to characterize the metabolizing profiles of cytochrome P450 (CYP) 2C19 and CYP2D6 in a hypothetical case study of patients suffering from major depressive disorder (MDD). The model considers different scenarios of adjustment of antidepressant treatment according to the patient’s metabolizing profile or treatment over a period of 18 weeks. The uncertainty of model parameters is tested through both a probabilistic sensitivity analysis and a one-way deterministic sensitivity analysis, and these results are used in a post-hoc analysis to understand the main drivers of three alternative cost-effectiveness levels (“poor,” “standard,” and “high”). These drivers are first evaluated from an exploratory multidimensional perspective and next from a predictive perspective as the probability that a patient belongs to a specific cost-effectiveness level is estimated on the basis of a restricted set of parameters used in the original pharmacoeconomic model.

Results

The models for CYP2C19 and CYP2D6 indicate that screening has an incremental cost-effectiveness ratio of 60,000€ and 47,000€ per quality-adjusted life year (QALY), respectively. The probabilistic sensitivity analysis shows that the treatments are cost-effective for a 75,000€ willingness to pay (WTP) threshold in 58% and 63% of the Monte Carlo replications, respectively. The post-hoc analysis highlights the factors that allow us to clearly discriminates poor cost-effectiveness from high cost-effectiveness scenarios and demonstrates that it is possible to predict with reasonable accuracy the cost-effectiveness of a genetic test and the associated therapeutic pattern.

Conclusions

Our findings suggest that screenings for both CYP2C19 and CYP2D6 enzymes for patients with MDD are cost-effective for a WTP threshold of 75,000€ per QALY, and provide relevant suggestions about the most important aspects to be further explored in clinical studies aimed at addressing the cost-effectiveness of genetic testing for patients diagnosed with MDD.

Systematic review and critical methodological appraisal of community-based falls prevention economic models

BACKGROUND

Falls impose significant health and economic burdens on community-dwelling older persons. Decision modelling can inform commissioning of alternative falls prevention strategies. Several methodological challenges arise when modelling public health interventions including community-based falls prevention. This study aims to conduct a systematic review (SR) to: systematically identify community-based falls prevention economic models; synthesise and critically appraise how the models handled key methodological challenges associated with public health modelling; and suggest areas for further methodological research.

METHODS

The SR followed the 2021 PRISMA reporting guideline and covered the period 2003-2020 and 12 academic databases and grey literature. The extracted methodological features of included models were synthesised by their relevance to the following challenges: (1) capturing non-health outcomes and societal intervention costs; (2) considering heterogeneity and dynamic complexity; (3) considering theories of human behaviour and implementation; and (4) considering equity issues. The critical appraisal assessed the prevalence of each feature across models, then appraised the methods used to incorporate the feature. The methodological strengths and limitations stated by the modellers were used as indicators of desirable modelling practice and scope for improvement, respectively. The methods were also compared against those suggested in the broader empirical and methodological literature. Areas of further methodological research were suggested based on appraisal results.

RESULTS

46 models were identified. Comprehensive incorporation of non-health outcomes and societal intervention costs was infrequent. The assessments of heterogeneity and dynamic complexity were limited; subgroup delineation was confined primarily to demographics and binary disease/physical status. Few models incorporated heterogeneity in intervention implementation level, efficacy and cost. Few dynamic variables other than age and falls history were incorporated to characterise the trajectories of falls risk and general health/frailty. Intervention sustainability was frequently based on assumptions; few models estimated the economic/health returns from improved implementation. Seven models incorporated ethnicity- and severity-based subgroups but did not estimate the equity-efficiency trade-offs. Sixteen methodological research suggestions were made.

CONCLUSION

Existing community-based falls prevention models contain methodological limitations spanning four challenge areas relevant for public health modelling. There is scope for further methodological research to inform the development of falls prevention and other public health models.

Estimating naloxone need in the USA across fentanyl, heroin, and prescription opioid epidemics: a modelling study

BACKGROUND

The US overdose crisis is driven by fentanyl, heroin, and prescription opioids. One evidence-based policy response has been to broaden naloxone distribution, but how much naloxone a community would need to reduce the incidence of fatal overdose is unclear. We aimed to estimate state-level US naloxone need in 2017 across three main naloxone access points (community-based programmes, provider prescription, and pharmacy-initiated distribution) and by dominant opioid epidemic type (fentanyl, heroin, and prescription opioid).

METHODS

In this modelling study, we developed, parameterised, and applied a mechanistic model of risk of opioid overdose and used it to estimate the expected reduction in opioid overdose mortality after deployment of a given number of two-dose naloxone kits. We performed a literature review and used a modified-Delphi panel to inform parameter definitions. We refined an established model of the population at risk of overdose by incorporating changes in the toxicity of the illicit drug supply and in the naloxone access point, then calibrated the model to 2017 using data obtained from proprietary data sources, state health departments, and national surveys for 12 US states that were representative of each epidemic type. We used counterfactual modelling to project the effect of increased naloxone distribution on the estimated number of opioid overdose deaths averted with naloxone and the number of naloxone kits needed to be available for at least 80% of witnessed opioid overdoses, by US state and access point.

FINDINGS

Need for naloxone differed by epidemic type, with fentanyl epidemics having the consistently highest probability of naloxone use during witnessed overdose events (range 58-76% across the three modelled states in this category) and prescription opioid-dominated epidemics having the lowest (range 0-20%). Overall, in 2017, community-based and pharmacy-initiated naloxone access points had higher probability of naloxone use in witnessed overdose and higher numbers of deaths averted per 100 000 people in state-specific results with these two access points than with provider-prescribed access only. To achieve a target of naloxone use in 80% of witnessed overdoses, need varied from no additional kits (estimated as sufficient) to 1270 kits needed per 100 000 population across the 12 modelled states annually. In 2017, only Arizona had sufficient kits to meet this target.

INTERPRETATION

Opioid epidemic type and how naloxone is accessed have large effects on the number of naloxone kits that need to be distributed, the probability of naloxone use, and the number of deaths due to overdose averted. The extent of naloxone distribution, especially through community-based programmes and pharmacy-initiated access points, warrants substantial expansion in nearly every US state.

FUNDING

National Institute of Health, National Institute on Drug Abuse.

Solving the Evidence Interpretability Crisis in Health Technology Assessment: A Role for Mechanistic Models?

Health technology assessment (HTA) aims to be a systematic, transparent, unbiased synthesis of clinical efficacy, safety, and value of medical products (MPs) to help policymakers, payers, clinicians, and industry to make informed decisions. The evidence available for HTA has gaps—impeding timely prediction of the individual long-term effect in real clinical practice. Also, appraisal of an MP needs cross-stakeholder communication and engagement. Both aspects may benefit from extended use of modeling and simulation. Modeling is used in HTA for data-synthesis and health-economic projections. In parallel, regulatory consideration of model informed drug development (MIDD) has brought attention to mechanistic modeling techniques that could in fact be relevant for HTA. The ability to extrapolate and generate personalized predictions renders the mechanistic MIDD approaches suitable to support translation between clinical trial data into real-world evidence. In this perspective, we therefore discuss concrete examples of how mechanistic models could address HTA-related questions. We shed light on different stakeholder's contributions and needs in the appraisal phase and suggest how mechanistic modeling strategies and reporting can contribute to this effort. There are still barriers dissecting the HTA space and the clinical development space with regard to modeling: lack of an adapted model validation framework for decision-making process, inconsistent and unclear support by stakeholders, limited generalizable use cases, and absence of appropriate incentives. To address this challenge, we suggest to intensify the collaboration between competent authorities, drug developers and modelers with the aim to implement mechanistic models central in the evidence generation, synthesis, and appraisal of HTA so that the totality of mechanistic and clinical evidence can be leveraged by all relevant stakeholders.

Cost-effectiveness analysis of apixaban versus vitamin K antagonists for antithrombotic therapy in patients with atrial fibrillation after acute coronary syndrome or percutaneous coronary intervention in Spain

BACKGROUND/OBJECTIVE

AUGUSTUS trial demonstrated that, for patients with atrial fibrillation (AF) having acute coronary syndrome (ACS) or undergoing percutaneous coronary intervention (PCI), an antithrombotic regimen with apixaban and P2Y12 resulted in less bleeding, fewer hospitalizations, and similar ischemic events than regimens including a vitamin K antagonist (VKA), aspirin, or both. This study objective was to evaluate long-term health and economic outcomes and the cost-effectiveness of apixaban over VKA, as a treatment option for patients with AF having ACS/PCI.

METHODS

A lifetime Markov cohort model was developed comparing apixaban versus VKA across multiple treatment strategies (triple [with P2Y12 + aspirin] or dual [with P2Y12] therapy followed by monotherapy [apixaban or VKA]; triple followed by dual and then monotherapy; dual followed by monotherapy). The model adopted the Spanish healthcare perspective, with a 3-month cycle length and costs and health outcomes discounted at 3%.

RESULTS

Treatment with apixaban resulted in total cost savings of €883 and higher life years (LYs) and quality-adjusted LYs (QALYs) per patient than VKA (net difference, LYs: 0.13; QALYs: 0.11). Bleeding and ischemic events (per 100 patients) were lower with apixaban than VKA (net difference, -13.9 and -1.8, respectively). Incremental net monetary benefit for apixaban was €3,041, using a willingness-to-pay threshold of €20,000 per QALY. In probabilistic sensitivity analysis, apixaban was dominant in the majority of simulations (92.6%), providing additional QALYs at lower costs than VKA.

CONCLUSIONS

Apixaban was a dominant treatment strategy than VKA from both the Spanish payer's and societal perspectives, regardless of treatment strategy considered.

Cost utility analysis of Remdesivir and Dexamethasone treatment for hospitalised COVID-19 patients - a hypothetical study

Background

Sars-Cov-2 is a novel corona virus associated with significant morbidity and mortality. Remdesivir and Dexamethasone are two treatments that have shown to be effective against the Sars-Cov-2 associated disease. However, a cost-effectiveness analysis of the two treatments is still lacking.

Objective

The cost-utility of Remdesivir, Dexamethasone and a simultaneous use of the two drugs with respect to standard of care for treatment Covid-19 hospitalized patients is evaluated, together with the effect of Remdesivir compared to the base model but based on alernative assumptions.

Methods

A decision tree for an hypothetical cohort of Covid-19 hospitalized patients, from an health care perspective and a one year horizon is specified. Efficacy data are retrieved from a literature review of clinical trials, whilst costs and utility are obtained from other published studies.

Results

Remdesivir, if health care costs are related to the days of hospitalization, is a cost saving strategy. Dexamethasone is cost effective with an ICER of <DOLLAR/>5208/QALY, and the concurrent use of Remdesivir and Dexamethasone is the most favorable strategy for higher level of willingness to pay thresholds. Moreover, if Remdesivir has a positive effect on mortality the utility is three times higher respect to base case. Whereas, if health care costs are not related to the length of patient hospitalization Remdesivir has an ICER respect to standard of care of <DOLLAR/>384412.8/QALY gained, which is not cost effective. We also find that Dexaamethasone is cost effective respect to standard care if we compute the cost for live saved with an ICER of <DOLLAR/>313.79 for life saved. The uncertainty of the model parameters is also tested through both a one-way deterministic sensitivity analysis and a probabilistic sensitivity analysis.

Conclusion

We find that the use of Remdesivir and/or Dexamethasone is effective from an economic standpoint.