Assessing cost-effectiveness of early intervention in Alzheimer's disease: An open-source modeling framework

New International Pharmaco-Economic Collaboration on Alzheimer's Disease (IPECAD) Open-Source Model Framework for the Health Technology Assessment of Early Alzheimer's Disease Treatment: Development and Use Cases

OBJECTIVES

Reimbursement decisions for new Alzheimer's disease (AD) treatments are informed by economic evaluations. An open-source model with intuitive structure for model cross-validation can support the transparency and credibility of such evaluations. We describe the new International Pharmaco-Economic Collaboration on Alzheimer's Disease (IPECAD) open-source model framework (version 2) for the health-economic evaluation of early AD treatment and use it for cross-validation and addressing uncertainty.

METHODS

A cohort state-transition model using a categorized composite domain (cognition and function) was developed by replicating an existing reference model and testing it for internal validity. Then, features of existing Institute for Clinical and Economic Review (ICER) and Alzheimer's Disease Archimedes Condition-Event Simulator (AD-ACE) models assessing lecanemab treatment were implemented for model cross-validation. Additional uncertainty scenarios were performed on choice of efficacy outcome from trial, natural disease progression, treatment effect waning and stopping rules, and other methodological choices. The model is available open-source as R code, spreadsheet, and web-based version via https://github.com/ronhandels/IPECAD.

RESULTS

In the IPECAD model incremental life-years, quality-adjusted life-years (QALY) gains and cost savings were 21% to 31% smaller compared with the ICER model and 36% to 56% smaller compared with the AD-ACE model. IPECAD model results were particularly sensitive to assumptions on treatment effect waning and stopping rules and choice of efficacy outcome from trial.

CONCLUSIONS

We demonstrated the ability of a new IPECAD open-source model framework for researchers and decision makers to cross-validate other (Health Technology Assessment submission) models and perform additional uncertainty analyses, setting an example for open science in AD decision modeling and supporting important reimbursement decisions.

Scenarios for the long-term efficacy of amyloid-targeting therapies in the context of the natural history of Alzheimer's disease

INTRODUCTION

Recent clinical trials of amyloid beta (Aβ)-targeting therapies in Alzheimer's disease (AD) have demonstrated a clinical benefit over 18 months, but their long-term impact on disease trajectory is not yet understood. We propose a framework for evaluating realistic long-term scenarios.

METHODS

Results from recent phase 3 trials of Aβ-targeting antibodies were integrated with an estimate of the long-term patient-level natural history trajectory of the Clinical Dementia Rating-Sum of Boxes (CDR-SB) score to explore realistic long-term efficacy scenarios.

RESULTS

Three distinct long-term efficacy scenarios were examined, ranging from conservative to optimistic. These extrapolations of positive phase 3 trials suggested treatments delayed onset of severe dementia by 0.3 to 0.6 years (conservative), 1.1 to 1.9 years (intermediate), and 2.0 to 4.2 years (optimistic).

DISCUSSION

Our study provides a common language for long-term impact of disease-modifying treatments. Our work calls for studies with longer follow-up and results from early intervention trials to provide a comprehensive assessment of these therapies' true long-term impact.

HIGHLIGHTS

We present long-term scenarios of the efficacy of AD therapies. In this framework, scenarios are defined relative to the natural history of AD. Long-term projections with different levels of optimism can be compared. It provides a common language for expressing beliefs about long-term efficacy.

Shared Manifold Regularized Joint Feature Selection for Joint Classification and Regression in Alzheimer's Disease Diagnosis

In Alzheimer's disease (AD) diagnosis, joint feature selection for predicting disease labels (classification) and estimating cognitive scores (regression) with neuroimaging data has received increasing attention. In this paper, we propose a model named Shared Manifold regularized Joint Feature Selection (SMJFS) that performs classification and regression in a unified framework for AD diagnosis. For classification, unlike the existing works that build least squares regression models which are insufficient in the ability of extracting discriminative information for classification, we design an objective function that integrates linear discriminant analysis and subspace sparsity regularization for acquiring an informative feature subset. Furthermore, the local data relationships are learned according to the samples' transformed distances to exploit the local data structure adaptively. For regression, in contrast to previous works that overlook the correlations among cognitive scores, we learn a latent score space to capture the correlations and employ the latent space to design a regression model with l2,1 -norm regularization, facilitating the feature selection in regression task. Moreover, the missing cognitive scores can be recovered in the latent space for increasing the number of available training samples. Meanwhile, to capture the correlations between the two tasks and describe the local relationships between samples, we construct an adaptive shared graph to guide the subspace learning in classification and the latent cognitive score learning in regression simultaneously. An efficient iterative optimization algorithm is proposed to solve the optimization problem. Extensive experiments on three datasets validate the discriminability of the features selected by SMJFS.

Digging into the intrinsic capacity concept: Can it be applied to Alzheimer's disease?

Historically, aging research has largely centered on disease pathology rather than promoting healthy aging. The World Health Organization's (WHO) policy framework (2015-2030) underscores the significance of fostering the contributions of older individuals to their families, communities, and economies. The WHO has introduced the concept of intrinsic capacity (IC) as a key metric for healthy aging, encompassing five primary domains: locomotion, vitality, sensory, cognitive, and psychological. Past AD research, constrained by methodological limitations, has focused on single outcome measures, sidelining the complexity of the disease. Our current scientific milieu, however, is primed to adopt the IC concept. This is due to three critical considerations: (I) the decline in IC is linked to neurocognitive disorders, including AD, (II) cognition, a key component of IC, is deeply affected in AD, and (III) the cognitive decline associated with AD involves multiple factors and pathophysiological pathways. Our study explores the application of the IC concept to AD patients, offering a comprehensive model that could revolutionize the disease's diagnosis and prognosis. There is a dearth of information on the biological characteristics of IC, which are a result of complex interactions within biological systems. Employing a systems biology approach, integrating omics technologies, could aid in unraveling these interactions and understanding IC from a holistic viewpoint. This comprehensive analysis of IC could be leveraged in clinical settings, equipping healthcare providers to assess AD patients' health status more effectively and devise personalized therapeutic interventions in accordance with the precision medicine paradigm. We aimed to determine whether the IC concept could be extended from older individuals to patients with AD, thereby presenting a model that could significantly enhance the diagnosis and prognosis of this disease.

Cost-Effectiveness of a Hypothetical Gene Therapy for Alzheimer's Disease: A Markov Simulation Analysis

Background: Alzheimer's disease is a prevalent neurodegenerative condition causing significant health and economic burden. With limited therapeutic options, clinical trials have been investigating Alzheimer's disease treatment using more novel approaches, including gene therapy. However, there is limited evidence on the cost-effectiveness of such treatments. Objectives: This research aims to explore the cost-effectiveness of a hypothetical gene therapy for patients with Alzheimer's disease at varying degrees of severity. Methods: A Markov model with a 20-year time horizon was constructed for simulated cohorts with mild cognitive impairment due to Alzheimer's disease, assigned to receive either standard of care or a one-time gene therapy administration. Varying costs of care due to disease severity and treatment efficacy were utilized to determine the effect of those variables at different willingness-to-pay thresholds. Results: Under the initial assumption that the hypothetical gene therapy grants a 30% risk reduction in disease progression and entry into institutional care, the maximum cost-effective price for gene therapy is $141,126 per treatment using the threshold of $150,000 per quality-adjusted life year (QALY). By increasing the treatment effectiveness to 50%, cost-effective price nearly doubled at each willingness-to-pay threshold (e.g., $260,902 at the $150,000/QALY threshold). Conclusion: Despite being cost-effective at a very high price, the hypothetical gene therapy for AD would still need to be priced considerably lower than other approved gene therapies on the market. Thus, a comprehensive pharmacoeconomic assessment remains critical in pricing innovative therapy and determining coverage for patients in need.

Is Aducanumab treatment developed to prevent progression of Alzheimer's disease cost-effective in Turkey?

BACKGROUND

Alzheimer's Disease (AD), the most common type of dementia, is a chronic, progressive, and neurodegenerative brain discomfort that causes the be damage to brain cells. Although there is no definitive treatment for AD, various drug treatments are used to reduce and control the symptoms of the disease. Developed for the treatment of mild-stage Alzheimer's patients, Aducanumab is the only drug approved by the Food and Drug Administration (FDA) in the past two decades. However, the cost is very high and, in many countries, Aducanumab has not been approved due to insufficient clinical efficacy and lack of evidence yet. This study aims to analyze the cost-effectiveness of Aducanumab, which was developed for the treatment of mild-stage AD, from the patient's perspective.

METHODS

In the study, the Markov model was developed to determine the cost-effectiveness of Aducanumab compared to Standard of Care (SoC) therapy over a 5-year horizon. Cost and effectiveness data were taken from the literature. In the study, the discount rate was determined as 6%. The results were presented as the incremental cost-effectiveness ratio (ICER), which represents the cost per quality-adjusted life years (QALY). The results were retested with a one-way and probabilistic sensitivity analysis (PSA) due to possible uncertainties in the research parameters. The results were presented with the tornado diagram and the scatter plots.

RESULTS

With the Markov model, the total costs of Aducanumab and SoC treatments over a 5-year horizon were found to be 98.068 $ and 21.292 $, respectively. Aducanumab treatment had an incremental gain of 0.64 QALY and an incremental cost of 76.776 $ compared to the SoC treatment. The ICER value, which shows the additional cost per QALY of Aducanumab, was 119.408 $/QALY. As a result of the study, it was determined that Aducanumab was not cost-effective when compared to SoC treatment. Sensitivity analysis results showed stability against uncertainties. Aducanumab was confirmed not to be cost-effective with its current price and potential clinical benefit.

CONCLUSION

The result of the research is considered important in terms of providing evidence-based information on the cost-effectiveness of Aducanumab in Turkey. However, further, research is needed to evaluate Aducanumab's clinical efficacy and cost-effectiveness.

The value of maintaining cognition in patients with mild cognitive impairment: The innovation headroom and potential cost-effectiveness of roflumilast

INTRODUCTION

Early health-technology assessment can support discussing scarce resource allocation among stakeholders. We explored the value of maintaining cognition in patients with mild cognitive impairment (MCI) by estimating: (1) the innovation headroom and (2) the potential cost effectiveness of roflumilast treatment in this population.

METHODS

The innovation headroom was operationalized by a fictive 100% efficacious treatment effect, and the roflumilast effect on memory word learning test was assumed to be associated with 7% relative risk reduction of dementia onset. Both were compared to Dutch setting usual care using the adapted International Pharmaco-Economic Collaboration on Alzheimer's Disease (IPECAD) open-source model.

RESULTS

The total innovation headroom expressed as net health benefit was 4.2 (95% bootstrap interval: 2.9-5.7) quality-adjusted life years (QALYs). The potential cost effectiveness of roflumilast was k€34 per QALY.

DISCUSSION

The innovation headroom in MCI is substantial. Although the potential cost effectiveness of roflumilast treatment is uncertain, further research on its effect on dementia onset is likely valuable.

A Simple Cost-Effectiveness Model of Screening: An Open-Source Teaching and Research Tool Coded in R

Applied cost-effectiveness analysis models are an important tool for assessing health and economic effects of healthcare interventions but are not best suited for illustrating methods. Our objective is to provide a simple, open-source model for the simulation of disease-screening cost-effectiveness for teaching and research purposes. We introduce our model and provide an initial application to examine changes to the efficiency frontier as input parameters vary and to demonstrate face validity. We described a vectorised, discrete-event simulation of screening in R with an Excel interface to define parameters and inspect principal results. An R Shiny app permits dynamic interpretation of simulation outputs. An example with 8161 screening strategies illustrates the cost and effectiveness of varying the disease sojourn time, treatment effectiveness, and test performance characteristics and costs on screening policies. Many of our findings are intuitive and straightforward, such as a reduction in screening costs leading to decreased overall costs and improved cost-effectiveness. Others are less obvious and depend on whether we consider gross outcomes or those net to no screening. For instance, enhanced treatment of symptomatic disease increases gross effectiveness, but reduces the net effectiveness and cost-effectiveness of screening. A lengthening of the preclinical sojourn time has ambiguous effects relative to no screening, as cost-effectiveness improves for some strategies but deteriorates for others. Our simple model offers an accessible platform for methods research and teaching. We hope it will serve as a public good and promote an intuitive understanding of the cost-effectiveness of screening.

Cost-effectiveness of a gene sequencing test for Alzheimer's disease in Ontario

Alzheimer's f disease (AD) affects approximately 250,000 Ontarians, a number that is expected to double by 2040. The Ontario Neurodegenerative Disease Research Initiative has developed an in-province genetic test (ONDRISeq), which currently runs in Ontario in an experimental capacity. The aim of this study is to estimate the costs and health outcomes associated with ONDRISeq to diagnose AD relative to out-of-country (OOC) testing (status quo). A cost-utility analysis was developed for a hypothetical cohort of 65-year-olds at risk of AD in Ontario over a 25-year time horizon. Costs and health outcomes (quality-adjusted life years (QALYs)) were assessed from a healthcare payer perspective. Cost-effectiveness was assessed with a $50,000 cost-effectiveness threshold. Probabilistic sensitivity analyses were conducted to evaluate parameter uncertainty. ONDRISeq saved $54 per patient relative to OOC testing and led to a small QALY gain in the base case (0.0014 per patient). Results were most sensitive to testing costs, uptake rates, and treatment efficacy. ONDRISeq represented better value for money relative to OOC testing throughout 75% of 10,000 probabilistic iterations. Using ONDRISeq is expected to provide health system cost savings. Switching to ONDRISeq for AD genetic testing in Ontario would be dependent on the ability to accommodate the expected testing volumes.

Effect of mortality in cost-effectiveness modeling of disease-modifying treatment for Alzheimer's disease

INTRODUCTION

We examined (1) the magnitude of mortality attributed to Alzheimer's disease (AD), and (2) the effect of mortality in cost-effectiveness modeling of hypothetical disease-modifying treatment (DMT) in AD.

METHOD

Data were derived from Swedish Dementia Registry (N = 39,308). Mortality was analyzed with survival analysis and multinomial logistic regression. A Markov microsimulation model was used to model the cost effectiveness of DMT using routine care as a comparator. Three scenarios were simulated: (1) indirect effect, (2) no effect on overall mortality, (3) indirect effect on AD-related mortality.

RESULTS

Overall mortality increased with cognitive decline, age, male sex, number of medications used, and lower body mass index. Nearly all cause-specific mortality was associated with cognitive decline. DMT increased survival by 0.35 years in scenario 1 and 0.14 years in scenario 3. DMT with no mortality effect is the least cost effective.

DISCUSSION

The results provide key mortality estimates and demonstrate influences on the cost effectiveness of DMT.

Highlights

We describe cause-specific mortality in relation to disease severity in Alzheimer's disease (AD).We model different assumptions of disease-modifying treatment (DMT) on AD survival.DMT was the least cost effective when assuming no effect on AD survival.Cost effectiveness is mainly influenced by the relative cost of staying in each disease state.

Circulating long non-coding RNAs as novel diagnostic biomarkers for Alzheimer's disease (AD): A systematic review and meta-analysis

BACKGROUND

Long non-coding RNAs (lncRNAs) have been reported to be involved in the pathogenesis of neurodegenerative diseases. It has also been hypothesized that plasma exosomal lncRNAs may be used as Alzheimer's disease (AD) biomarkers. In this systematic review, we compiled all studies on the subject to evaluate the accuracy of lncRNAs in identifying AD cases through meta-analysis.

METHODS

A PRISMA-compliant systematic search was conducted in PubMed/MEDLINE, EMBASE, and Web of Science databases for English publications till September 2022. We included all observational studies published which investigated the sensitivity and specificity of various lncRNAs in plasma samples of AD diagnosis. Our search strategy included lncRNA and all the related spelling and abbreviation variations combined with the keyword Alzheimer's disease. Methodological quality was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-II) tool. The meta-analysis was carried out using the area under the Receiver Operator Characteristic (ROC) curves (AUC) and sensitivity and specificity values to assess the accuracy of the identified lncRNAs in AD diagnosis. To account for the predicted heterogeneity of the study, a random-effects model was used. All the statistical analyses and visualizations were conducted using Stata 17.0 software.

RESULTS

A total of seven studies (AD patients = 553, healthy controls = 513) were included in the meta-analysis. Three lncRNAs were upregulated (RNA BACE-AS1, RNA NEAT1, RNA GAS5), and one lncRNA (MALAT1) was downregulated in plasma samples of AD patients. RNA 51A and RNA BC200 were reported to have variable expression patterns. A lncRNA (RNA 17A) was not significantly different between AD and control groups. The pooled sensitivity, specificity, and AUC values of lncRNAs in identifying AD were (0.74; 95% CI [0.63, 0.82], I2 = 79.2%), (0.88; 95% CI [0.75, 0.94], I2 = 88.9%), and 0.86; 95% CI [0.82, 0.88], respectively. In addition, the pooled diagnostic odds ratio (DOR) of the five individual lncRNAs in AD diagnosis was 20.

CONCLUSION

lncRNAs had high accuracy in identifying AD and must be seen as a promising diagnostic biomarker of the disease.

A Simulation Model to Evaluate the Potential Impact of Disease-Modifying Treatments on Burden of Illness in Alzheimer's Disease

INTRODUCTION

Alzheimer's disease (AD) is a progressive neurodegenerative disease that places a substantial burden on patients, caregivers, and society. The advent of disease-modifying treatments (DMTs) would represent a major advancement in the management of AD, particularly in early AD. It is important to understand the potential value of these therapies to individuals and society.

METHODS

A modeling framework was developed to estimate the potential clinical and economic burden of AD in the USA by simulating the impact, relative to that of usual care, of a DMT with hypothesized availability beginning from 2022. The model assessed AD epidemiology, disease progression, and burden of illness from 2020 to 2050. Model outcomes included the total number of Americans with mild cognitive impairment (MCI) due to AD and mild, moderate, or severe AD dementia in community or residential care settings and their associated care costs, including direct medical and non-medical costs for healthcare resource use and indirect costs for caregiving.

RESULTS

A hypothetical DMT was compared to the usual care under different effect scenarios based on delay in onset of AD (1, 3, and 5 years) and DMT uptake (25%, 50%, and 100%). A delay in the onset of AD by 5 years would reduce the prevalence of AD in 2050 by 6%, 12%, and 25%, resulting in savings of $0.783, $1.566, and $3.132 trillion from 2022 to 2050 for the 25%, 50%, and 100% uptake scenarios, respectively.

CONCLUSION

This analysis demonstrated that DMTs that provide even small delays in the onset of AD can lead to an increase in disease-free years and sizable savings in the cost of care, providing significant benefits to patients, caregivers, and society.

Clinical research in dementia: A perspective on implementing innovation

The increasing global prevalence of dementia demands concrete actions that are aimed strategically at optimizing processes that drive clinical innovation. The first step in this direction requires outlining hurdles in the transition from research to practice. The different parties needed to support translational processes have communication mismatches; methodological gaps hamper evidence-based decision-making; and data are insufficient to provide reliable estimates of long-term health benefits and costs in decisional models. Pilot projects are tackling some of these gaps, but appropriate methods often still need to be devised or adapted to the dementia field. A consistent implementation perspective along the whole translational continuum, explicitly defined and shared among the relevant stakeholders, should overcome the "research-versus-adoption" dichotomy, and tackle the implementation cliff early on. Concrete next steps may consist of providing tools that support the effective participation of heterogeneous stakeholders and agreeing on a definition of clinical significance that facilitates the selection of proper outcome measures.

Cost‐effectiveness models for Alzheimer's disease and related dementias: IPECAD modeling workshop cross‐comparison challenge

INTRODUCTION

The credibility of model-based economic evaluations of Alzheimer's disease (AD) interventions is central to appropriate decision-making in a policy context. We report on the International PharmacoEconomic Collaboration on Alzheimer's Disease (IPECAD) Modeling Workshop Challenge.

METHODS

Two common benchmark scenarios, for the hypothetical treatment of AD mild cognitive impairment (MCI) and mild dementia, were developed jointly by 29 participants. Model outcomes were summarized, and cross-comparisons were discussed during a structured workshop.

RESULTS

A broad concordance was established among participants. Mean 10-year restricted survival and time in MCI in the control group ranged across 10 MCI models from 6.7 to 9.5 years and 3.4 to 5.6 years, respectively; and across 4 mild dementia models from 5.4 to 7.9 years (survival) and 1.5 to 4.2 years (mild dementia).

DISCUSSION

The model comparison increased our understanding of methods, data used, and disease progression. We established a collaboration framework to assess cost-effectiveness outcomes, an important step toward transparent and credible AD models.

Costs of Persons with Dementia Living in Nursing Homes in The Netherlands

Background: Disease modifying treatments (DMTs) currently under development for Alzheimer’s disease, have the potential to prevent or postpone institutionalization and more expensive care and might delay institutionalization of persons with dementia. Objective: The current study estimates costs of living in a nursing home for persons with dementia in the Netherlands to help inform economic evaluations of future DMTs. Methods: Data were collected during semi-structured interviews with healthcare professionals and from the financial administration of a healthcare organization with several nursing homes. Personnel costs were calculated using a bottom-up approach by valuing the time estimates. Non-personnel costs were calculated using information from the financial administration of the healthcare organization. Results: Total personnel costs of a person with dementia per 24 hours, including both care staff and other healthcare providers, were € 151 for small-scale living wards and € 147 for independent living wards. Non-personnel costs were € 37 per day. Conclusion: This study provides Dutch estimates for total healthcare costs per day for institutionalized persons with dementia. These cost estimates can be used in cost-effectiveness analyses for future DMTs in dementia.

Prescribing Alzheimer's Disease treatments by provider type and geographic region: a comparison among physicians, nurse practitioners, and physician assistants

Background

The estimated increase in Alzheimer’s Disease (AD) caseload may present a logistical challenge to the US healthcare system. While nurse practitioners (NPs) and physician assistants (PAs) are increasingly delivering primary care to patients with chronic diseases, the nature of their prescribing of AD medications is largely unknown. The primary objective of this study was to compare the prescribing of AD medications across provider types (physician, NP, and PA) and geographic regions.

Methods

We conducted a retrospective cohort study using IBM MarketScan® commercial and Medicare supplemental claims to examine unique AD prescriptions prescribed between January 1, 2016, and December 31, 2019. Parallel analysis of prescriptions for another geriatric condition, osteoporosis (OP), was also conducted for comparison.

Results

A total of 103,067 AD prescriptions and 131,773 OP prescriptions were included in analyses. Physicians prescribed most AD prescriptions (95.65%), followed by NPs (3.37%) and PAs (0.98%). Small differences were identified among individual AD medications prescribed by physicians compared to NP/PAs. NPs/PAs prescribed a significantly higher proportion of AD prescriptions in rural as compared to urban areas (z = 0.023, 95%CI [0.018, 0.028]).

Conclusion

Minimal variation exists in AD prescribing among physicians, NPs, and PAs, but NPs/PAs prescribe more AD prescriptions in rural areas. NPs/PAs, especially in rural areas, may play critical roles in alleviating projected workforce constraints. Further research assessing AD care, health outcomes, and costs by provider type and region is necessary to better guide healthcare workforce planning for AD care.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03176-3.

Protective effects of camellia and olive oils against cognitive impairment via gut microbiota-brain communication in rats

Food intake influences neurofunction via the gut microbiota-brain axis. Monounsaturated fatty acid (MUFA) consumption is highly associated with neuroprotection; the mechanism behind the effects of olive oil and camellia oil on gut microbiota remains unclear. In this study, the objective was to compare the neuroprotective role of oleic acid-rich camellia oil and olive oil against AlCl₃-induced mild cognitive impairment (MCI) in rats. Morris water maze tests revealed that learning and memory capacities improved in AlCl₃-induced rats subjected to camellia oil administration better than olive oil treatment. Moreover, the results showed that the camellia oil- and olive oil-treated AlCl₃-induced rat groups had significantly reduced oxidative stress and inflammatory cytokines. Notably, Spearman correlation analysis indicated that the inflammatory cytokines negatively correlated with the microbial strains (Bacteroides pectinophilus_group and Blautia) in response to camellia oil administration. Furthermore, Ruminococcaceae_UCG014 abundance was significantly enhanced by camellia oil intake, which was highly positively associated with antioxidant activity expression. In conclusion, the novel data suggest that the outcomes of camellia oil consumption were superior to those of olive oil intake as camellia oil may have a beneficial effect on MCI protection and improvement through the gut microbiota-brain communication.

Assessments of the Value of New Interventions Should Include Health Equity Impact

A formal evaluation of the health equity impact of a new intervention is hardly ever performed as part of a health technology assessment to understand its value. This should change, in our view. An evidence-based quantitative assessment of the health equity impact can help decision makers develop coverage policies, programme designs, and quality initiatives focused on optimizing both total health and health equity given the treatment options available. We outline the conceptual basis of how a new intervention can impact health equity and adopt distributional cost-effectiveness analysis based on decision-analytic models to assess this quantitatively, using a newly US FDA-approved drug for Alzheimer's disease (aducanumab) as an example. We argue that gaps in the evidence base for the new intervention, for example, due to limited clinical research participation among racial and ethnic minority groups, do not preclude such an evaluation. Understanding these uncertainties has implications for fair pricing, decision making, and future research. If we are serious about population-level decision making that not only is focused on improving total health but also aims to improve health equity, we should consider routinely assessing the health equity impact of new interventions.

Cost-effectiveness of Aducanumab and Donanemab for Early Alzheimer Disease in the US

Importance

Several anti-amyloid monoclonal antibodies have been developed for slowing the progression of Alzheimer disease (AD). Among the furthest developed are aducanumab, which received accelerated approval from the US Food and Drug Administration in 2021, and donanemab, which is currently undergoing phase 3 trials. The cost-effectiveness of these treatments has not been established.

Objectives

To estimate the cost-effectiveness of aducanumab and donanemab relative to standard care for early AD in the US.

Design, Setting, and Participants

A decision analytic model was used to estimate the lifetime health and economic outcomes of adults with early AD, from US healthcare sector and societal perspectives. Simulated patients had a mean (SD) age of 75.2 (5.5) years; 65% had mild cognitive impairment and 35% had mild dementia. Analyses were conducted from April 6, 2021, to January 20, 2022.

Interventions

Standard care, aducanumab (selected inputs including disease progression hazard ratio [HR] of 0.89 [95% CI, 0.63-1.15], annual price of $28 000, and twice-yearly monitoring with magnetic resonance imaging [MRI] of the brain), or donanemab (selected inputs including disease progression HR of 0.68 [95% CI, 0.44-0.99], annual price of $28 000, and twice-yearly monitoring with MRI of the brain and amyloid positron emission tomography [PET] monitoring). Donanemab was switched to placebo after substantial amyloid reduction on PET imaging, which occurred in 27% of patients at 6 months and 55% of patients at 12 months.

Main Outcomes and Measures

Quality-adjusted life-years (QALYs); costs, in 2020 US dollars; incremental cost-effectiveness ratios (ICERs); and value-based prices, defined as the maximum price at which a treatment would be cost-effective given a cost-effectiveness threshold of ICER of $150 000/QALY.

Results

Lifetime QALYs increased by 0.133 with aducanumab and 0.408 with donanemab. Total health care sector and societal costs increased by $130 100 and $127 800, respectively, with aducanumab and by $78 700 and $71 600, respectively, with donanemab, driven largely by drug costs ($119 000 for aducanumab and $44 600 for donanemab). Health care sector and societal ICERs relative to standard care were $981 000/QALY and $964 000/QALY, respectively, for aducanumab and $193 000/QALY and $176 000/QALY, respectively, for donanemab. In sensitivity analysis, aducanumab's value-based price remained less than $50 000/y, even when assuming a 90% reduction in disease progression. Donanemab's value-based price surpassed $50 000/y once its efficacy exceeded 50%.

Conclusions and Relevance

These findings suggest that at current expected prices, neither aducanumab nor donanemab would be cost-effective for early AD in the US. Donanemab's dosing scheme, in which patients suspend treatment on achieving substantial amyloid reductions, may provide a rubric by which sufficiently effective anti-amyloid antibody treatments could be cost-effective even when priced comparably to other biologics.

Cost-effectiveness of aducanumab to prevent Alzheimer's disease progression at current list price

Introduction

An estimated 6 million Americans have Alzheimer's disease (AD). Aducanumab was recently approved by the Food and Drug Administration despite the lack of clinical effectiveness data.

Methods

We developed a Markov state transition model of AD to estimate the cost effectiveness of aducanumab compared to standard of care (SOC) over a 5-year time horizon for a cohort of persons aged 65 with mild AD. Outcomes included quality adjusted life years (QALYs), discounted costs, and incremental cost-effectiveness ratios (ICERs). We performed sensitivity analyses to address uncertainty.

Results

Over 5 years, the incremental cost of aducanumab compared to SOC was $179,890. Aducanumab resulted in 0.47 QALYs gained compared to SOC. The ICER for aducanumab compared to SOC was $383,080/QALY. In threshold analysis, aducanumab became cost-effective at $22,820/year.

Discussion

Aducanumab is not cost-effective at the estimated price of $56,000 even under ideal circumstances in which it completely halts AD progression.

Medical and nursing home costs: From cognitively unimpaired through dementia

INTRODUCTION

Efforts to model the cost-effectiveness of managing/modifying cognitive impairment lack reliable, objective, baseline medical, and nursing-home (NH) costs.

METHODS

A stratified-random sample of Olmsted County, MN, residents ages 70-89 years (N = 3545), well-characterized as cognitively unimpaired, mild cognitive impairment (MCI), or dementia, were followed forward ≤1 year in provider-linked billing data and the Centers for Medicare & Medicaid Services NH assessments. Direct medical/nursing home/medical + NH costs were estimated. Costs were stratified by vital status and NH-use intensity (NH days/follow-up days [0%, 1% to 24%, 25% to 99%, and 100%]). Between-category mean-annual cost differences were adjusted for patient characteristics and follow-up days.

RESULTS

Costs/follow-up day distributions differed significantly across cognitive categories. Mean costs/follow-up days were 2.5 to 18 times higher for decedents versus survivors. Among all persons with MCI, <9% with any NH use accounted for 18% of all total annual medical + NH costs. Adjusted-between-category comparisons revealed significantly higher medical and medical + NH costs for MCI versus cognitively unimpaired.

DISCUSSION

Cost-effectiveness for managing/modifying both MCI and dementia should consider end-of-life costs and NH-use intensity. Results can help inform cost-effectiveness models, predict future-care needs, and aid decision-making by individuals/providers/payers/policymakers.

Predicted Cognitive Conversion in Guiding Early Decision-Tailoring on Patients With Cognitive Impairment

BACKGROUND

Cognitive decline is the most dominant and patient-oriented symptom during the development of Alzheimer's disease (AD) and mild cognitive impairment (MCI). This study was designed to test the feasibility of hybrid convolutional neural networks and long-short-term memory (CNN-LSTM) modeling driven early decision-tailoring with the predicted long-term cognitive conversion in AD and MCI.

METHODS

Characteristics of patients with AD or MCI covering demographic features, clinical features, and time-dependent neuropsychological-related features were fused into the hybrid CNN-LSTM modeling to predict cognitive conversion based on a 4-point change in the AD assessment scale-cognition score. Treatment reassignment rates were estimated based on the actual and predicted cognitive conversion at 3 and 6 months according to the prespecified principle; that is if the ADAS-cog score of the patient declines less than 4 points or increases at either follow-up time point, the medical treatment recommended upon their diagnosis would be considered insufficient. Therefore, it is recommended to upgrade the medical treatment upon diagnosis. Actual and predicted treatment reassignment rates were compared in the general population and subpopulations categorized by age, gender, symptom severity, and the intervention subtypes.

RESULTS

A total of 224 patients were included in the analysis. The hybrid CNN-LSTM model achieved the mean AUC of 0.735 (95% CI: 0.701-0.769) at 3 months and 0.853 (95% CI: 0.814-0.892) at 6 months in predicting cognitive conversion status. The AUC at 6 months was significantly impacted when data collected at 3 months were withdrawn. The predicted cognitive conversion suggested a revision of medical treatment in 46.43% (104/224) of patients at 3 months and 54.02% (121/224) at 6 months as compared with 62.05% (139/224) at 3 months (p = 0.001) and 62.50% (140/224) at 6 months (p = 0.069) according to their actual cognitive conversion. No significant differences were detected between treatment reassignment rates estimated based on actual and predicted cognitive conversion in all directions at 6 months.

CONCLUSION

Using the synergistic advances of deep learning modeling and featured longitudinal information, our hypothesis was preliminarily verified with the comparable predictive performance in cognitive conversion. Results provided the possibility of reassigned recommended treatment for those who may suffer from cognitive decline in the future. Considering the limited diversity of treatment strategies applied in this study, the real-world medical situation should be further simulated.

Performing Cost-Effectiveness Analyses to Support Policy Making: Key Lessons From the Assessment of Aducanumab

The purpose of this paper is to describe the process and the methods of cost-effectiveness analysis for clinicians interested in joining or leading aspects of this branch of evidence-based research. Cost-effectiveness is a useful tool for policymakers and is considered a starting point for discussions of fair pricing. Clinicians are important members of teams conducting cost-effectiveness analyses, particularly as it relates to integrating their clinical expertise into the decisions around the design and conduct of the analysis. Their input is essential in assuring that models adequately reflect clinical practice and are informed by expert judgments of how existing data can best be interpreted to build a comprehensive analysis of the clinical and economic outcomes of different treatment options. We illustrate specific contributions that clinicians are well positioned to make in these teams using a recent cost-effectiveness analysis of aducanumab that was conducted to support fair drug pricing. While discussing these contributions, we explain key components of a cost-effectiveness analysis, such as time horizon, health states, and perspective, to support the understanding of the methods of cost-effectiveness by the clinical researchers and to promote a common dialogue among these multidisciplinary teams.

Predicted Lifetime Health Outcomes for Aducanumab in Patients with Early Alzheimer's Disease

INTRODUCTION

Alzheimer's disease (AD) is a chronic and progressive neurodegenerative disease that places a substantial burden on patients and caregivers. Aducanumab is the first AD therapy approved by the US Food and Drug Administration to reduce a defining pathophysiological feature of the disease, brain amyloid plaques. In the phase 3 clinical trial EMERGE (NCT02484547), aducanumab reduced clinical decline in patients with mild cognitive impairment (MCI) due to AD and mild AD dementia and confirmed amyloid pathology.

METHODS

We used a Markov modeling approach to predict the long-term clinical benefits of aducanumab for patients with early AD based on EMERGE efficacy data. In the model, patients could transition between AD severity levels (MCI due to AD; mild, moderate, and severe AD dementia) and care settings (community vs. institution) or transition to death. The intervention was aducanumab added to standard of care (SOC), and the comparator was SOC alone. Data sources for base-case and scenario analyses included EMERGE, published National Alzheimer's Coordinating Center analyses, and other published literature.

RESULTS

Per patient over a lifetime horizon, aducanumab treatment corresponded to 0.65 incremental patient quality-adjusted life-years (QALYs) and 0.09 fewer caregiver QALYs lost compared with patients treated with SOC. Aducanumab treatment translated to a lower lifetime probability of transitioning to AD dementia, a lower lifetime probability of transitioning to institutionalization (25.2% vs. 29.4%), delays in the median time to transition to AD dementia (7.50 vs. 4.92 years from MCI to moderate AD dementia or worse), and an incremental median time in the community of 1.32 years compared with SOC.

CONCLUSION

The model predicted long-term benefits of aducanumab treatment in patients with MCI due to AD and mild AD dementia and their caregivers. The predicted outcomes provide a foundation for healthcare decision-makers and policymakers to understand the potential clinical and socioeconomic value of aducanumab.

Exercise interventions in Alzheimer's disease: A systematic review and meta-analysis of randomized controlled trials

AIMS

To assess the potential multi-domain benefits of exercise interventions on patients with Alzheimer's disease (AD), as well as to determine the specific effects of different exercise modalities (aerobic, strength, or combined training).

METHODS

A systematic search was conducted in PubMed and Web of Science until March 2021 for randomized controlled trials assessing the effect of exercise interventions (compared with no exercise) on patients with AD. Outcomes included cognitive function (mini-mental state examination [MMSE] test), physical function (e.g., 6-minute walking test [6MWT]), functional independence (Barthel index), and neuropsychiatric symptoms (Neuropsychiatric Inventory [NPI]). A random-effects meta-analysis was conducted.

RESULTS

28 studies (total n = 1337 participants, average age 79-90 years) were included in the systematic review, of which 21 could be meta-analyzed. Although considerable heterogeneity was found, exercise interventions induced several significant benefits, including in Barthel index (n = 147 patients, mean difference [MD]=8.36 points, 95% confidence interval [CI]=0.63-16.09), 6MWT (n = 369, MD=84 m, 95% CI=44-133)), and NPI (n = 263, MD=-4.4 points, 95% CI=-8.42 to -0.38). Benefits were also found in the MMSE test, albeit significance was only reached for aerobic exercise (n = 187, MD=2.31 points, 95% CI 0.45-4.27).

CONCLUSIONS

Exercise interventions appear to exert multi-domain benefits in patients with AD.

Heterogeneity in Reports of Dementia Disease Duration and Severity: A Review of the Literature

BACKGROUND

The burden of dementia is changing due to population aging and changes in incidence and risk factor profiles. Reliable projections of future disease burden require accurate estimates of disease duration across different stages of dementia severity.

OBJECTIVE

To provide an overview of current evidence on severity stage and disease duration in patients with dementia.

METHODS

We reviewed the literature on duration of mild cognitive impairment (MCI), dementia, and various dementia severity stages. Data on study setting, country, sample size, severity stages, dementia type, and definition of disease duration was collected. Weighted averages and Q-statistics were calculated within severity stages and duration definitions.

RESULTS

Of 732 screened articles, 15 reported the duration of one or more severity stages and only half of those reported severity stage onset to conversion to the following stage. In those studies, MCI, very mild dementia, and mild dementia stages lasted 3-4 years and moderate and severe dementia stages lasted 1-2 years. Information on the disease duration was reported in 93 (13%) of screened articles and varied from 1 to 17 years. Reporting of dementia severity stage and disease duration in the literature was highly heterogeneous, which was accounted for only in part by dementia type, study setting, or continent of data collection.

CONCLUSION

The duration of dementia disease stages shortens with advancing stage. However, reliable modelling of future dementia burden and informing of intervention strategies will require more consistently reported duration estimates from studies that follow individuals longitudinally throughout their entire disease course.

Contextual Considerations and Recommendations for Estimating the Value of Alzheimer's Disease Therapies

The pipeline for new treatments for Alzheimer's disease (AD) in the USA contains over 100 different agents, 80% of which can be categorized as disease-modifying therapies. The regulatory approval of the disease-modifying agent aducanumab has brought more attention to the complexity of the diagnosis, evaluation, and treatment of AD and the difficult decisions payers and policy makers will face over the next few years as innovation continues in this space. The value of AD treatment can vary widely according to the perspective of the analysis, sources of data, and methodological approach for the value assessment. This article focuses on AD-specific data gaps and measurement challenges and provides guidance for evidence generation to facilitate better value assessments for future AD treatments.

Evaluation of the Cost-effectiveness of Drug Treatment for Alzheimer Disease in a Simulation Model That Includes Caregiver and Societal Factors

Importance

The possibility of widespread use of a novel effective therapy for Alzheimer disease (AD) will present important clinical, policy, and financial challenges.

Objective

To describe how including different patient, caregiver, and societal treatment-related factors affects estimates of the cost-effectiveness of a hypothetical disease-modifying AD treatment.

Design, Setting, and Participants

In this economic evaluation, the Alzheimer Disease Archimedes Condition Event Simulator was used to simulate the prognosis of a hypothetical cohort of patients selected from the Alzheimer Disease Neuroimaging Initiative database who received the diagnosis of mild cognitive impairment (MCI). Scenario analyses that varied costs and quality of life inputs relevant to patients and caregivers were conducted. The analysis was designed and conducted from June 15, 2019, to September 30, 2020.

Exposures

A hypothetical drug that would delay progression to dementia in individuals with MCI compared with usual care.

Main Outcomes and Measures

Incremental cost-effectiveness ratio (ICER), measured by cost per quality-adjusted life-year (QALY) gained.

Results

The model included a simulated cohort of patients who scored between 24 and 30 on the Mini-Mental State Examination and had a global Clinical Dementia Rating scale of 0.5, with a required memory box score of 0.5 or higher, at baseline. Using a health care sector perspective, which included only individual patient health care costs, the ICER for the hypothetical treatment was $192 000 per QALY gained. The result decreased to $183 000 per QALY gained in a traditional societal perspective analysis with the inclusion of patient non-health care costs. The inclusion of estimated caregiver health care costs produced almost no change in the ICER, but the inclusion of QALYs gained by caregivers led to a substantial reduction in the ICER for the hypothetical treatment, to $107 000 per QALY gained in the health sector perspective. In the societal perspective scenario, with the broadest inclusion of patient and caregiver factors, the ICER decreased to $74 000 per added QALY.

Conclusions and Relevance

The findings of this economic evaluation suggest that policy makers should be aware that efforts to estimate and include the effects of AD treatments outside those on patients themselves can affect the results of the cost-effectiveness analyses that often underpin assessments of the value of new treatments. Further research and debate on including these factors in assessments that will inform discussions on fair pricing for new treatments are needed.

Eldercare services for people with and without a dementia diagnosis: an analysis of Swedish registry data

Background

The growing number of people living with dementia (PlwD) implies an increase in the demand for eldercare services in Sweden like in many other countries. Few studies have analyzed the use of eldercare services for PlwD. The aim of the present study is to investigate the association between demographic factors (age, sex, cohabiting status) and the use of municipal eldercare services (including both home care and residential care) for older adults with dementia compared to older adults without dementia in Sweden.

Methods

This study used several nationwide Swedish registers targeting all individuals aged 65 and above living in Sweden in 2014 and still alive 31st of March 2015 (n = 2,004,409). The primary outcomes variables were different types of eldercare service, and all participants were clustered based on age, sex, cohabiting status, and dementia diagnosis. In addition to descriptive statistics, we performed multivariate logistic regression models for binary outcomes and linear regression models for continuous outcomes.

Results

Results showed that (1) older age is a significantly strong predictor for the use of eldercare services, although PlwD start using eldercare at an earlier age compared with people without dementia; (2) women tend to receive more eldercare services than men, especially in older age, although men with dementia who live alone are more likely than women living alone to receive eldercare; (3) having a dementia diagnosis is a strong predictor for receiving eldercare. However, it was also found that a substantial proportion of men and women with dementia did not receive any eldercare services.

Conclusions

We found that people with a dementia diagnosis use more as well as start to use eldercare services at an earlier age than people without dementia. However, further research is needed to investigate why a substantial part of people with a dementia diagnosis does not have any eldercare at all and what the policy implications of this might be.

Clinical Outcome Measure Crosswalks in Alzheimer's Disease: A Systematic Review

BACKGROUND

A key challenge in studies that model outcomes, disease progression, and cost-effectiveness of existing and emerging dementia treatments is the lack of conversion criteria to translate, or 'crosswalk', scores on multiple measurement scales. Clinical status in dementia is commonly characterized in the cognitive, functional, and behavioral domains.

OBJECTIVE

We conducted a systematic review of peer-reviewed dementia measure crosswalks in the three domains.

METHODS

We systematically reviewed published literature for crosswalks between scales used to measure cognitive, functional, or behavioral outcomes in Alzheimer's and related dementias. The search was conducted in PubMed, and additional crosswalks were identified through snowballing and expert input from dementia modelers.

RESULTS

Of the reviewed articles, 2,334 were identified through a PubMed search, 842 articles were sourced from backward and forward citation snowballing, and 8 additional articles were recommended through expert input. 31 papers were eligible for inclusion, listing 74 unique crosswalks. Of those, 62 (83.8%) were between endpoints of the cognitive domain and 12 (16.2%) were either between endpoints of the functional domain or were hybrid in nature. Among crosswalks exclusively in the cognitive domain, a majority involved the Mini-Mental State Examination (MMSE) (37 crosswalks) or the Montreal Cognitive Assessment (MoCA) and its variants (25 crosswalks). MMSE was directly compared to MoCA or MoCA variants in 16 crosswalks.

CONCLUSION

Existing crosswalks between measures of dementia focus largely on a limited selection of outcome measures, particularly MMSE and MoCA. Few crosswalks exist in the functional domain, and no crosswalks were identified for solely behavioral measures.

Health utility in preclinical and prodromal Alzheimer's disease for establishing the value of new disease-modifying treatments-EQ-5D data from the Swedish BioFINDER study

Quality of life and health utility are important outcomes for patients with Alzheimer's disease (AD) and central for demonstrating the value of new treatments. Estimates in biomarker-confirmed AD populations are missing, potentially delaying payer approval of treatment. We examined whether health utility, assessed with the EuroQoL-5 3-level version (EQ-5D-3L), differed between individuals with a positive or negative amyloid beta (Aβ) biomarker in patients with mild cognitive impairment (MCI) and cognitively unimpaired (CU) participants from the Swedish BioFINDER study (n = 578). Participants with prodromal AD (Aβ-positive MCI) reported better health utility (n = 79, mean = 0.81, 95% confidence interval [CI] 0.77-0.85) than Aβ-negative MCI (mean = 0.71, 95% CI 0.64-0.78), but worse than controls (Aβ-negative CU, mean = 0.87, 95% CI 0.86-0.89). Health utility in preclinical AD (Aβ-positive CU; mean = 0.86, 95% CI 0.83-0.89) was similar to controls. This relatively good health utility in prodromal AD suggests a larger value of delaying progression to dementia than previously anticipated and a great value of delaying clinical progression in preclinical AD.

Projection of budgetary savings to US state Medicaid programs from reduced nursing home use due to an Alzheimer's disease treatment

INTRODUCTION

The approval of a disease-modifying Alzheimer's disease (AD) treatment could provide relief to US state budgets that were hit hard by the COVID-19 pandemic, as mostly Medicare would cover treatment cost, whereas Medicaid would see savings from reduced nursing home use.

METHODS

We project savings from 2021 to 2040 with a simulation model from the perspective of state Medicaid programs.

RESULTS

Assuming a 40% and 22% relative reduction of disease progression rates with treatment, Medicaid would avoid payments of $186.2 and $93.5 billion for around 1.11 and 0.57 million nursing home patient-years, respectively. The savings correspond to a 5.06% and 2.49%, respectively, relative reduction of Medicaid spending on nursing home care. Higher per capita savings were projected for older states, those with higher Medicaid payment rates, those with more nursing home residents covered by Medicaid, and those with a lower federal contribution.

DISCUSSION

States stand to realize substantial savings from a potential AD treatment. A state's health system preparedness to handle the large number of patients will influence the actual magnitude of the savings and how fast they will accrue.

Economic evaluation of supplementing the diet with Souvenaid in patients with prodromal Alzheimer's disease

Background

The LipiDiDiet trial showed that Souvenaid, a medical food, might delay progression to dementia in prodromal Alzheimer’s disease (AD). The objective of this study was to assess the cost-utility of Souvenaid compared to placebo in patients with prodromal AD under the conditions applied in that trial.

Methods

A discrete event simulation model was developed based on the LipiDiDiet trial and a literature review to assess the cost-utility of Souvenaid from a societal perspective considering direct and indirect costs. For both intervention and control groups, patient trajectories in terms of functional decline on the Clinical Dementia Rating Sum of Boxes (CDR-SB) scale in LipiDiDiet were reproduced statistically with mixed models by assigning time until events to simulated patients. From the societal perspective, four scenarios were analysed by combining different options for treatment duration and diagnostic test cost. Univariate sensitivity analysis assessed parameter uncertainties.

Results

Validation results at year 2 of disease progression fit with CDR-SB progression in LipiDiDiet. The incremental cost-utility ratio (ICUR) in the baseline case was €22,743/quality-adjusted life year (QALY). All scenarios rendered an ICUR lower than €25,000/QALY (the societal threshold). Moreover, the treatment option was cost-saving and increased health benefits when diagnostic costs were not considered and treatment was only administered during the prodromal stage.

Conclusions

Treating prodromal AD with Souvenaid is a cost-effective intervention in all scenarios analysed. The LipiDiDiet trial showed a modest improvement in disease course but as the social costs of AD are very high, the intervention was efficient. Assessing small benefits at specific stages of AD is relevant because it is reasonable to expect that no effective, safe and affordable disease-modifying therapies will become available in the short to medium term.

How Much Value Would a Treatment for Alzheimer's Disease Offer? Cost-Effectiveness Thresholds for Pricing a Disease-Modifying Therapy

BACKGROUND

Recent trials suggest that disease-modifying therapy (DMT) for Alzheimer's disease may become available soon. With the expected high price and a large patient pool, the budget impact will be substantial.

OBJECTIVE

We explore combinations of effectiveness and price under which a DMT is cost-effective.

METHODS

We used an open-source model to conduct two-way scenario analyses for both payer and societal perspectives, varying price, and treatment effect size simultaneously. The analysis generates costeffectiveness threshold prices over a potential range of DMT effectiveness in patients aged 65+ with mild cognitive impairment due to Alzheimer's disease in the US.

RESULTS

Under the willingness-to-pay a threshold of $150,000 per quality-adjusted life year and assuming 30% risk reduction relative to the standard of care, the maximum cost-effective price of a DMT per patient per year is ~$22,000 and ~$15,000 from societal and payer perspectives, respectively.

CONCLUSION

Joint variation of price and treatment effect size can help assess the cost-effectiveness of a potential Alzheimer's disease treatment.