Decision analytic models for Alzheimer's disease: state of the art and future directions

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.

Model-Based Economic Evaluations of Interventions for Dementia: An Updated Systematic Review and Quality Assessment

BACKGROUND

There has been an increase in model-based economic evaluations of interventions for dementia. The most recent systematic review of economic evaluations for dementia highlighted weaknesses in studies, including lack of justification for model assumptions and data inputs.

OBJECTIVE

This study aimed to update the last published systematic review of model-based economic evaluations of interventions for dementia, including Alzheimer's disease, with a focus on any methodological improvements and quality assessment of the studies.

METHODS

Systematic searches in eight databases, including PubMed, Cochrane, Embase, CINAHL, PsycINFO, EconLit, international HTA database, and the Tufts Cost-Effectiveness Analysis Registry were undertaken from February 2018 until August 2022. The quality of the included studies was assessed using the Philips checklist and the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 checklist. The findings were summarized through narrative analysis.

RESULTS

This review included 23 studies, comprising cost-utility analyses (87%), cost-benefit analyses (9%) and cost-effectiveness analyses (4%). The studies covered various interventions, including pharmacological (n = 10, 43%), non-pharmacological (n = 4, 17%), prevention (n = 4, 17%), diagnostic (n = 4, 17%) and integrated (n = 1, 4%) [diagnostics-pharmacologic] strategies. Markov transition models were commonly employed (65%), followed by decision trees (13%) and discrete-event simulation (9%). Several interventions from all categories were reported as being cost effective. The quality of reporting was suboptimal for the Methods and Results sections in almost all studies, although the majority of studies adequately addressed the decision problem, scope, and model-type selection in their economic evaluations. Regarding the quality of methodology, only a minority of studies addressed competing theories or clearly explained the rationale for model structure. Furthermore, few studies systematically identified key parameters or assessed data quality, and uncertainty was mostly addressed partially.

CONCLUSIONS

This review informs future research and resource allocation by providing insights into model-based economic evaluations for dementia interventions and highlighting areas for improvement.

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.

Components, impacts and costs of dementia home support: a research programme including the DESCANT RCT

Background

Over half of people with dementia live at home. We know little about what home support could be clinically effective or cost-effective in enabling them to live well.

Objectives

We aimed to (1) review evidence for components of home support, identify their presence in the literature and in services in England, and develop an appropriate economic model; (2) develop and test a practical memory support package in early-stage dementia, test the clinical effectiveness and cost-effectiveness of routine home support in later-stage dementia and design a toolkit based on this evidence; and (3) elicit the preferences of staff, carers and people with dementia for home support inputs and packages, and evaluate the cost-effectiveness of these approaches in early- and later-stage dementia.

Design

We undertook (1) an evidence synthesis, national surveys on the NHS and social care and an economic review; (2) a multicentre pragmatic randomised trial [Dementia Early Stage Cognitive Aids New Trial (DESCANT)] to estimate the clinical effectiveness and cost-effectiveness of providing memory aids and guidance to people with early-stage dementia (the DESCANT intervention), alongside process evaluation and qualitative analysis, an observational study of existing care packages in later-stage dementia along with qualitative analysis, and toolkit development to summarise this evidence; and (3) consultation with experts, staff and carers to explore the balance between informal and paid home support using case vignettes, discrete choice experiments to explore the preferences of people with dementia and carers between home support packages in early- and later-stage dementia, and cost–utility analysis building on trial and observational study.

Setting

The national surveys described Community Mental Health Teams, memory clinics and social care services across England. Recruitment to the trial was through memory services in nine NHS trusts in England and one health board in Wales. Recruitment to the observational study was through social services in 17 local authorities in England. Recruitment for the vignette and preference studies was through memory services, community centres and carers’ organisations.

Participants

People aged > 50 years with dementia within 1 year of first attendance at a memory clinic were eligible for the trial. People aged > 60 years with later-stage dementia within 3 months of a review of care needs were eligible for the observational study. We recruited staff, carers and people with dementia for the vignette and preference studies. All participants had to give written informed consent.

Main outcome measures

The trial and observational study used the Bristol Activities of Daily Living Scale as the primary outcome and also measured quality of life, capability, cognition, general psychological health and carers’ sense of competence.

Methods

Owing to the heterogeneity of interventions, methods and outcome measures, our evidence and economic reviews both used narrative synthesis. The main source of economic studies was the NHS Economic Evaluation Database. We analysed the trial and observational study by linear mixed models. We analysed the trial by ‘treatment allocated’ and used propensity scores to minimise confounding in the observational study.

Results

Our reviews and surveys identified several home support approaches of potential benefit. In early-stage dementia, the DESCANT trial had 468 randomised participants (234 intervention participants and 234 control participants), with 347 participants analysed. We found no significant effect at the primary end point of 6 months of the DESCANT intervention on any of several participant outcome measures. The primary outcome was the Bristol Activities of Daily Living Scale, for which scores range from 0 to 60, with higher scores showing greater dependence. After adjustment for differences at baseline, the mean difference was 0.38, slightly but not significantly favouring the comparator group receiving treatment as usual. The 95% confidence interval ran from –0.89 to 1.65 (p = 0.56). There was no evidence that more intensive care packages in later-stage dementia were more effective than basic care. However, formal home care appeared to help keep people at home. Staff recommended informal care that cost 88% of formal care, but for informal carers this ratio was only 62%. People with dementia preferred social and recreational activities, and carers preferred respite care and regular home care. The DESCANT intervention is probably not cost-effective in early-stage dementia, and intensive care packages are probably not cost-effective in later-stage dementia. From the perspective of the third sector, intermediate intensity packages were cheaper but less effective. Certain elements may be driving these results, notably reduced use of carers’ groups.

Limitations

Our chosen outcome measures may not reflect subtle outcomes valued by people with dementia.

Conclusions

Several approaches preferred by people with dementia and their carers have potential. However, memory aids aiming to affect daily living activities in early-stage dementia or intensive packages compared with basic care in later-stage dementia were not clinically effective or cost-effective.

Future work

Further work needs to identify what people with dementia and their carers prefer and develop more sensitive outcome measures.

Study registration

Current Controlled Trials ISRCTN12591717. The evidence synthesis is registered as PROSPERO CRD42014008890.

Funding

This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 9, No. 6. See the NIHR Journals Library website for further project information.

Where are we at with model-based economic evaluations of interventions for dementia? a systematic review and quality assessment

ABSTRACTObjective:To identify, review, and critically appraise model-based economic evaluations of all types of interventions for people with dementia and their carers.

DESIGN

A systematic literature search was undertaken to identify model-based evaluations of dementia interventions. A critical appraisal of included studies was carried out using guidance on good practice methods for decision-analytic models in health technology assessment, with a focus on model structure, data, and model consistency.

SETTING

Interventions for people with dementia and their carers, across prevention, diagnostic, treatment, and disease management.

RESULTS

We identified 67 studies, with 43 evaluating pharmacological products, 19 covering prevention or diagnostic strategies, and 5 studies reporting non-pharmacological interventions. The majority of studies use Markov models with a simple structure to represent dementia symptoms and disease progression. Half of all studies reported taking a societal perspective, with the other half adopting a third-party payer perspective. Most studies follow good practices in modeling, particularly related to the decision problem description, perspective, model structure, and data inputs. Many studies perform poorly in areas related to the reporting of pre-modeling analyses, justifying data inputs, evaluating data quality, considering alternative modeling options, validating models, and assessing uncertainty.

CONCLUSIONS

There is a growing literature on the model-based evaluations of interventions for dementia. The literature predominantly reports on pharmaceutical interventions for Alzheimer's disease, but there is a growing literature for dementia prevention and non-pharmacological interventions. Our findings demonstrate that decision-makers need to critically appraise and understand the model-based evaluations and their limitations to ensure they are used, interpreted, and applied appropriately.

Using Cerebrospinal Fluid Biomarker Testing to Target Treatment to Patients with Mild Cognitive Impairment: A Cost-Effectiveness Analysis

OBJECTIVE

Cerebrospinal fluid (CSF) biomarkers are shown to facilitate a risk identification of patients with mild cognitive impairment (MCI) into different risk levels of progression to Alzheimer's disease (AD). Knowing a patient's risk level provides an opportunity for earlier interventions, which could result in potential greater benefits. We assessed the cost effectiveness of the use of CSF biomarkers in MCI patients where the treatment decision was based on patients' risk level.

METHODS

We developed a state-transition model to project lifetime quality-adjusted life-years (QALYs) and costs for a cohort of 65-year-old MCI patients from a US societal perspective. We compared four test-and-treat strategies where the decision to treat was based on a patient's risk level (low, intermediate, high) of progressing to AD with two strategies without testing, one where no patients were treated during the MCI phase and in the other all patients were treated. We performed deterministic and probabilistic sensitivity analyses to evaluate parameter uncertainty.

RESULTS

Testing and treating low-risk MCI patients was the most cost-effective strategy with an incremental cost-effectiveness ratio (ICER) of US$37,700 per QALY. Our results were most sensitive to the level of treatment effectiveness for patients with mild AD and for MCI patients. Moreover, the ICERs for this strategy at the 2.5th and 97.5th percentiles were US$18,900 and US$50,100 per QALY, respectively.

CONCLUSION

Based on the best available evidence regarding the treatment effectiveness for MCI, this study suggests the potential value of performing CSF biomarker testing for early targeted treatments among MCI patients with a narrow range for the ICER.

Systematic literature review of methodologies and data sources of existing economic models across the full spectrum of Alzheimer's disease and dementia from apparently healthy through disease progression to end of life care: a systematic review protocol

INTRODUCTION

Dementia is one of the greatest health challenges the world will face in the coming decades, as it is one of the principal causes of disability and dependency among older people. Economic modelling is used widely across many health conditions to inform decisions on health and social care policy and practice. The aim of this literature review is to systematically identify, review and critically evaluate existing health economics models in dementia. We included the full spectrum of dementia, including Alzheimer's disease (AD), from preclinical stages through to severe dementia and end of life. This review forms part of the Real world Outcomes across the Alzheimer's Disease spectrum for better care: multimodal data Access Platform (ROADMAP) project.

METHODS AND ANALYSIS

Electronic searches were conducted in Medical Literature Analysis and Retrieval System Online, Excerpta Medica dataBASE, Economic Literature Database, NHS Economic Evaluation Database, Cochrane Central Register of Controlled Trials, Cost-Effectiveness Analysis Registry, Research Papers in Economics, Database of Abstracts of Reviews of Effectiveness, Science Citation Index, Turning Research Into Practice and Open Grey for studies published between January 2000 and the end of June 2017. Two reviewers will independently assess each study against predefined eligibility criteria. A third reviewer will resolve any disagreement. Data will be extracted using a predefined data extraction form following best practice. Study quality will be assessed using the Phillips checklist for decision analytic modelling. A narrative synthesis will be used.

ETHICS AND DISSEMINATION

The results will be made available in a scientific peer-reviewed journal paper, will be presented at relevant conferences and will also be made available through the ROADMAP project.

PROSPERO REGISTRATION NUMBER

CRD42017073874.

Alzheimer's disease Archimedes condition-event simulator: Development and validation

Introduction

Several advances have been made in Alzheimer's Disease (AD) modeling, however, there remains a need for a simulator that represents the full scope of disease progression and can be used to study new disease-modifying treatments for early-stage and even prodromal AD.

Methods

We developed AD Archimedes condition-event simulator, a patient-level simulator with a focus on simulating the effects of early interventions through changes in biomarkers of AD. The simulator incorporates interconnected predictive equations derived from longitudinal data sets.

Results

The results of external validations on AD Archimedes condition-event simulator showed that it provides reasonable estimates once compared to literature results on transition to dementia AD, institutionalization, and mortality. A case study comparing a disease-modifying treatment and a symptomatic treatment also showcases the benefits of early treatment.

Discussion

The AD Archimedes condition-event simulator is designed to perform economic evaluation on various interventions through close tracking of disease progression and the related clinical outcomes.

Decision modelling of non-pharmacological interventions for individuals with dementia: a systematic review of methodologies

OBJECTIVES

The main objective of this study is to conduct a systematic review to identify and discuss methodological issues surrounding decision modelling for economic evaluation of non-pharmacological interventions (NPIs) in dementia.

METHODS

A systematic search was conducted for publications using decision modelling to investigate the cost-effectiveness of NPIs for individuals with dementia. Search was limited to studies in English. Studies were excluded if they evaluated interventions aimed only at caregivers of patients with dementia, or if they only included economic evaluation alongside an RCT without additional modelling.

RESULTS

Two primary, five secondary and three tertiary prevention intervention studies were identified and reviewed. Five studies utilised Markov models, with others using discrete event, regression-based simulation, and decision tree approaches. A number of challenging methodological issues were identified, including the use of MMSE-score as the main outcome measure, limited number of strategies compared, restricted time horizons, and limited or dated data on dementia onset, progression and mortality. Only one of the three tertiary prevention studies explicitly considered the effectiveness of pharmacological therapies alongside their intervention.

CONCLUSIONS

Economic evaluations of NPIs in dementia should utilise purposefully-developed decision models, and avoid models for evaluation of pharmaceuticals. Broader outcome measures could be a way to capture the wide impact of NPIs for dementia in future decision models. It is also important to account for the effects of pharmacological therapies alongside the NPIs in economic evaluations. Access to more localised and up-to-date data on dementia onset, progression and mortality is a priority for accurate prediction.

The cost-effectiveness implications of suboptimal treatment for different severities of Alzheimer's disease in the UK

OBJECTIVE

This study aims to evaluate the impact of suboptimal treatment, defined in terms of lower population coverage (percentage of total patient population receiving optimal treatment) and delay to treatment on the cost-effectiveness of pharmacological therapies approved for the treatment of different severities of Alzheimer's disease (AD) in the UK.

METHODS

A 5-year Markov model was used to simulate transition to full-time care, as delay and coverage were varied for AD patients with mild-to-moderate and moderate-to-severe dementia. The time-varying predictive equations, resource use, utilities, treatment effects and mortality were derived using published sources.

RESULTS

For the cohort with moderate-to-severe dementia, cost-effectiveness was optimised when delay was minimised and coverage maximised. For mild-to-moderate dementia, results were similar but varied widely depending on the inputted cost of acetylcholinesterase inhibitors.

CONCLUSIONS

The average cost-effectiveness of pharmacological treatments for AD is sensitive to delays to treatment and population coverage. The results of this study can inform future healthcare policy in order to maximise cost-effectiveness of pharmacological therapies for AD. Copyright © 2017 John Wiley & Sons, Ltd.

Clinical validity of brain fluorodeoxyglucose positron emission tomography as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework

The use of Alzheimer's disease (AD) biomarkers is supported in diagnostic criteria, but their maturity for clinical routine is still debated. Here, we evaluate brain fluorodeoxyglucose positron emission tomography (FDG PET), a measure of cerebral glucose metabolism, as a biomarker to identify clinical and prodromal AD according to the framework suggested for biomarkers in oncology, using homogenous criteria with other biomarkers addressed in parallel reviews. FDG PET has fully achieved phase 1 (rational for use) and most of phase 2 (ability to discriminate AD subjects from healthy controls or other forms of dementia) aims. Phase 3 aims (early detection ability) are partly achieved. Phase 4 studies (routine use in prodromal patients) are ongoing, and only preliminary results can be extrapolated from retrospective observations. Phase 5 studies (quantify impact and costs) have not been performed. The results of this study show that specific efforts are needed to complete phase 3 evidence, in particular comparing and combining FDG PET with other biomarkers, and to properly design phase 4 prospective studies as a basis for phase 5 evaluations.

Societal and Family Lifetime Cost of Dementia: Implications for Policy

OBJECTIVES

To estimate the cost of dementia and the extra cost of caring for someone with dementia over the cost of caring for someone without dementia.

DESIGN

We developed an evidence-based mathematical model to simulate disease progression for newly diagnosed individuals with dementia. Data-driven trajectories of cognition, function, and behavioral and psychological symptoms were used to model disease progression and predict costs. Using modeling, we evaluated lifetime and annual costs of individuals with dementia, compared costs of those with and without clinical features of dementia, and evaluated the effect of reducing functional decline or behavioral and psychological symptoms by 10% for 12 months (implemented when Mini-Mental State Examination score ≤21).

SETTING

Mathematical model.

PARTICIPANTS

Representative simulated U.S. incident dementia cases.

MEASUREMENTS

Value of informal care, out-of-pocket expenditures, Medicaid expenditures, and Medicare expenditures.

RESULTS

From time of diagnosis (mean age 83), discounted total lifetime cost of care for a person with dementia was $321,780 (2015 dollars). Families incurred 70% of the total cost burden ($225,140), Medicaid accounted for 14% ($44,090), and Medicare accounted for 16% ($52,540). Costs for a person with dementia over a lifetime were $184,500 greater (86% incurred by families) than for someone without dementia. Total annual cost peaked at $89,000, and net cost peaked at $72,400. Reducing functional decline or behavioral and psychological symptoms by 10% resulted in $3,880 and $680 lower lifetime costs than natural disease progression.

CONCLUSION

Dementia substantially increases lifetime costs of care. Long-lasting, effective interventions are needed to support families because they incur the most dementia cost.

Personalized predictive modeling for patients with Alzheimer's disease using an extension of Sullivan's life table model

BACKGROUND

Alzheimer's disease (AD) progression varies substantially among patients, hindering calculation of residual total life expectancy (TLE) and its decomposition into disability-free life expectancy (DFLE) and disabled life expectancy (DLE) for individual patients with AD. The objective of the present study was to assess the accuracy of a new synthesis of Sullivan's life table (SLT) and longitudinal Grade of Membership (L-GoM) models that estimates individualized TLEs, DFLEs, and DLEs for patients with AD. If sufficiently accurate, such information could enhance the quality of important decisions in AD treatment and patient care.

METHODS

We estimated a new SLT/L-GoM model of the natural history of AD over 10 years in the Predictors 2 Study cohort: N = 229 with 6 fixed and 73 time-varying covariates over 21 examinations covering 11 measurement domains including cognitive, functional, behavioral, psychiatric, and other symptoms/signs. Total remaining life expectancy was censored at 10 years. Disability was defined as need for full-time care (FTC), the outcome most strongly associated with AD progression. All parameters were estimated via weighted maximum likelihood using data-dependent weights designed to ensure that the estimates of the prognostic subtypes were of high quality. Goodness of fit was tested/confirmed for survival and FTC disability for five relatively homogeneous subgroups defined to cover the range of patient outcomes over the 21 examinations.

RESULTS

The substantial heterogeneity in initial patient presentation and AD progression was captured using three clinically meaningful prognostic subtypes and one terminal subtype exhibiting highly differentiated symptom severity on 7 of the 11 measurement domains. Comparisons of the observed and estimated survival and FTC disability probabilities demonstrated that the estimates were accurate for all five subgroups, supporting their use in AD life expectancy calculations. Mean 10-year TLE differed widely across subgroups: range 3.6-8.0 years, average 6.1 years. Mean 10-year DFLE differed relatively even more widely across subgroups: range 1.2-6.5 years, average 4.0 years. Mean 10-year DLE was relatively much closer: range 1.5-2.3 years, average 2.1 years.

CONCLUSIONS

The SLT/L-GoM model yields accurate maximum likelihood estimates of TLE, DFLE, and DLE for patients with AD; it provides a realistic, comprehensive modeling framework for endpoint and resource use/cost calculations.

Dependence Stage and Pharmacoeconomic Outcomes in Patients With Alzheimer Disease

The level of assistance patients with Alzheimer disease (AD) require in their care may be an important predictor of resource use, costs of care, and quality of life. The Dependence Scale (DS), a measure of care-assistance required, was used to estimate costs of care and quality of life of patients with AD categorized into 6 dependence stages based upon the summated item scores of the DS. Data were derived from a 3-year, noninterventional study of 132 patients with probable AD (ages, 50 to 85 y) and caregiver dyads. We investigated the association between DS scores and health care costs, health-related quality of life (HRQoL), caregiver burden and estimated annual costs and HRQoL for 6 dependence stages in adjusted models. DS scores were significant predictors of health care costs, HRQoL, and caregiver burden. The estimated annual health care costs and a measure of HRQoL (EuroQoL-5D) ranged from $11,418 and 1.00 for those at very mild dependence stage to $101,715 and 0.26 for those at very severe dependence stage. DS scores classified into 6 dependence stages provides a useful method to estimate unique levels of care-associated costs and health utilities for pharmacoeconomic evaluations of new treatments for AD.

Current issues and future research priorities for health economic modelling across the full continuum of Alzheimer's disease

Available data and models for the health-economic evaluation of treatment in Alzheimer's disease (AD) have limitations causing uncertainty to decision makers. Forthcoming treatment strategies in preclinical or early AD warrant an update on the challenges associated with their economic evaluation. The perspectives of the co-authors were complemented with a targeted review of literature discussing methodological issues and data gaps in AD health-economic modelling. The methods and data available to translate treatment efficacy in early disease into long-term outcomes of relevance to policy makers and payers are limited. Current long-term large-scale data accurately representing the continuous, multifaceted, and heterogeneous disease process are missing. The potential effect of disease-modifying treatment on key long-term outcomes such as institutionalization and death is uncertain but may have great effect on cost-effectiveness. Future research should give priority to collaborative efforts to access better data on the natural progression of AD and its association with key long-term outcomes.

Systematic Review of Model-Based Economic Evaluations of Treatments for Alzheimer's Disease

BACKGROUND

Numerous economic evaluations using decision-analytic models have assessed the cost effectiveness of treatments for Alzheimer's disease (AD) in the last two decades. It is important to understand the methods used in the existing models of AD and how they could impact results, as they could inform new model-based economic evaluations of treatments for AD.

OBJECTIVE

The aim of this systematic review was to provide a detailed description on the relevant aspects and components of existing decision-analytic models of AD, identifying areas for improvement and future development, and to conduct a quality assessment of the included studies.

METHODS

We performed a systematic and comprehensive review of cost-effectiveness studies of pharmacological treatments for AD published in the last decade (January 2005 to February 2015) that used decision-analytic models, also including studies considering patients with mild cognitive impairment (MCI). The background information of the included studies and specific information on the decision-analytic models, including their approach and components, assumptions, data sources, analyses, and results, were obtained from each study. A description of how the modeling approaches and assumptions differ across studies, identifying areas for improvement and future development, is provided. At the end, we present our own view of the potential future directions of decision-analytic models of AD and the challenges they might face.

RESULTS

The included studies present a variety of different approaches, assumptions, and scope of decision-analytic models used in the economic evaluation of pharmacological treatments of AD. The major areas for improvement in future models of AD are to include domains of cognition, function, and behavior, rather than cognition alone; include a detailed description of how data used to model the natural course of disease progression were derived; state and justify the economic model selected and structural assumptions and limitations; provide a detailed (rather than high-level) description of the cost components included in the model; and report on the face-, internal-, and cross-validity of the model to strengthen the credibility and confidence in model results. The quality scores of most studies were rated as fair to good (average 87.5, range 69.5-100, in a scale of 0-100).

CONCLUSION

Despite the advancements in decision-analytic models of AD, there remain several areas of improvement that are necessary to more appropriately and realistically capture the broad nature of AD and the potential benefits of treatments in future models of AD.

Predicting the progression of Alzheimer's disease dementia: A multidomain health policy model

INTRODUCTION

We develop a multidomain model to predict progression of Alzheimer's disease dementia (AD).

METHODS

Data from the US National Alzheimer's Coordinating Center (n = 3009) are used to examine change in symptom status and to estimate transition probabilities between health states described using cognitive function, functional ability, and behavior. A model is used to predict progression and to assess a hypothetical treatment scenario that slows mild to moderate AD progression.

RESULTS

More than 70% of participants moved state over 12 months. The majority moved in domains other than cognitive function. Over 5 years, of those alive more than half are in severe AD health states. Assessing an intervention scenario, we see fewer years in more severe health states and a potential impact (life years saved) due to mortality improvements.

DISCUSSION

The model developed is exploratory and has limitations but illustrates the importance of using a multidomain approach when assessing impacts of AD and interventions.

Modeling test and treatment strategies for presymptomatic Alzheimer disease

OBJECTIVES

In this study, we developed a model of presymptomatic treatment of Alzheimer disease (AD) after a screening diagnostic evaluation and explored the circumstances required for an AD prevention treatment to produce aggregate net population benefit.

METHODS

Monte Carlo simulation methods were used to estimate outcomes in a simulated population derived from data on AD incidence and mortality. A wide variety of treatment parameters were explored. Net population benefit was estimated in aggregated QALYs. Sensitivity analyses were performed by individually varying the primary parameters.

FINDINGS

In the base-case scenario, treatment effects were uniformly positive, and net benefits increased with increasing age at screening. A highly efficacious treatment (i.e. relative risk 0.6) modeled in the base-case is estimated to save 20 QALYs per 1000 patients screened and 221 QALYs per 1000 patients treated.

CONCLUSIONS

Highly efficacious presymptomatic screen and treat strategies for AD are likely to produce substantial aggregate population benefits that are likely greater than the benefits of aspirin in primary prevention of moderate risk cardiovascular disease (28 QALYS per 1000 patients treated), even in the context of an imperfect treatment delivery environment.

Psychometric properties of the Dependence Scale in large randomized clinical trials of patients with mild and moderate Alzheimer's disease

OBJECTIVE

The need for assistance from others is a hallmark concern in Alzheimer's disease (AD). The psychometric properties of the Dependence Scale (DS) for measuring treatment benefit were investigated in large randomized clinical trials of patients with mild to moderate AD.

METHODS

Reliability, validity, and responsiveness of the DS were examined. Path models appraised relationships and distinctiveness of key AD measures. The responder definition was empirically derived.

RESULTS

Generally acceptable reliability (α ≥ .65), significant (P < .001) known-groups tests, and moderate to strong correlations (r ≥ .31) confirmed the DS psychometric properties. Path models supported relationships and distinctiveness of key AD measures. A DS change of ≤ 1 point for patients with limited home care and ≤ 2 points for patients with assisted living care best described stability of the level of dependence on caregivers.

CONCLUSION

The DS is a psychometrically robust measure in mild to moderate AD. The empirically derived responder definition aids in the interpretation of DS change.

Evaluating disease-modifying agents: a simulation framework for Alzheimer's disease

BACKGROUND

Considerable advances have been made in modeling Alzheimer's disease (AD), with a move towards individual-level rather than cohort models and simulations that consider multiple dimensions when evaluating disease severity. However, the possibility that disease-modifying agents (DMAs) may emerge requires an update of existing modeling frameworks.

OBJECTIVES

The aim of this study was to develop a simulation allowing for economic evaluation of DMAs in AD.

METHODS

The model was developed based on a previously published, well-validated, discrete event simulation which measures disease severity on the basis of cognition, behaviour, and function, and captures the interrelated changes in these measures for individuals. The updated model adds one more domain, patient dependence, in addition to cognition, behaviour, and function to better characterize disease severity. Furthermore, the model was modified to have greater flexibility in assessing the impact of various important assumptions, such as the long-term effectiveness of DMAs and their impact on survival, on model outcomes. A validation analysis was performed to examine how well the model predicted change in disease severity among patients not receiving DMA treatment by comparing model results to those observed in two recent phase III clinical trials of bapineuzumab. In addition, various hypothetical scenarios were tested to demonstrate the improved features of the model.

RESULTS

Validation results show that the model closely predicts the mean changes in disease severity over 18 months. Results from different hypothetical scenarios show that the model allows for credible assessment of those major uncertainties surrounding the long-term effectiveness of DMAs, including the potential impact of improved survival with DMA treatment. They also indicate that varying these assumptions could have a major impact on the value of DMAs.

CONCLUSIONS

The updated economic model has good predictive power, but validation against longer-term outcomes is still needed. Our analyses also demonstrate the importance of designing a model with sufficient flexibility such that the model allows for assessment of the impact of key sources of uncertainty on the value of DMAs.

Health economic evaluation of treatments for Alzheimer's disease: impact of new diagnostic criteria

The socio-economic impact of Alzheimer's disease (AD) and other dementias is enormous, and the potential economic challenges ahead are clear given the projected future numbers of individuals with these conditions. Because of the high prevalence and cost of dementia, it is very important to assess any intervention from a cost-effectiveness viewpoint. The diagnostic criteria for preclinical AD suggested by the National Institute on Aging and Alzheimer's Association workgroups in combination with the goal of effective disease-modifying treatment (DMT) are, however, a challenge for clinical practice and for the design of clinical trials. Key issues for future cost-effectiveness studies include the following: (i) the consequences for patients if diagnosis is shifted from AD-dementia to predementia states, (ii) bridging the gap between clinical trial populations and patients treated in clinical practice, (iii) translation of clinical trial end-points into measures that are meaningful to patients and policymakers/payers and (iv) how to measure long-term effects. To improve cost-effectiveness studies, long-term population-based data on disease progression, costs and outcomes in clinical practice are needed not only in dementia but also in predementia states. Reliable surrogate end-points in clinical trials that are sensitive to detect effects even in predementia states are also essential as well as robust and validated modelling methods from predementia states that also take into account comorbidities and age. Finally, the ethical consequences of early diagnosis should be considered.

Reliability, validity, and interpretation of the dependence scale in mild to moderately severe Alzheimer's disease

INTRODUCTION

The Dependence Scale (DS) was designed to measure dependence on others among patients with Alzheimer's disease (AD). The objectives of this research were primarily to strengthen the psychometric evidence for the use of the DS in AD studies.

METHODS

Patients with mild to moderately severe AD were examined in 3 study databases. Within each data set, internal consistency, validity, and responsiveness were examined, and structural equation models were fit.

RESULTS

The DS has strong psychometric properties. The DS scores differed significantly across known groups and demonstrated moderate to strong correlations with measures hypothesized to be related to dependence (|r| ≥ .31). Structural equation modeling supported the validity of the DS concept. An anchor-based DS responder definition to interpret a treatment benefit over time was identified.

DISCUSSION

The DS is a reliable, valid, and interpretable measure of dependence associated with AD and is shown to be related to--but provides information distinct from--cognition, functioning, and behavior.

Determinants of care costs of patients with dementia or cognitive impairment

INTRODUCTION

Dementia causes a high burden on patients, caregivers, and societies. Decision analytic models to support allocation of resources are often developed making use of cost-of-illness (COI) studies. However, current COI study estimates are highly variable due to care setting and methodological issues. We aim to explore variables explaining the variation of (formal and informal) health care costs of cognitive disorders, using a broad spectrum of variables, including patient, caregiver, and social context variables.

METHODS

A bottom-up COI study design was used in which a societal viewpoint and a validated method to measure and value informal care was applied. Data were analyzed using univariate, multivariate, and forward regression analyses.

RESULTS

The average 1-year health care sector costs were &OV0556;26,140 ($34,505 or £17,775) and &OV0556;11,931 ($15,749 or £8113) for patient and family. The analyses indicated that cognitive functioning, caregiver burden, patient sex, and instrumental activities of daily living were significantly associated with care costs independently.

CONCLUSIONS

Cognitive functioning and instrumental activities of daily living are important variables to include in health care decision models. We recommend also including caregiver burden and patient sex in decision models for health policy decision makers to fully reflect the heterogeneity of the disease progression of cognitive disorders.

Disease progression and costs of care in Alzheimer's disease patients treated with donepezil: a longitudinal naturalistic cohort

BACKGROUND/AIMS

Improved data and methods are needed for modeling disease progression in Alzheimer's disease (AD) for economic evaluation of treatments. The aim is to estimate prediction models for long-term AD progression and subsequently economic outcomes.

METHODS

Three-year follow-up data on 435 patients treated with the cholinesterase inhibitor donepezil in clinical practise were analyzed. Regression models were estimated for long-term prediction of decline in cognitive function (ADAS-cog) and activities in daily living (ADL) ability, risk of institutionalization and costs of care.

RESULTS

The cognitive deterioration was estimated at between 1.6 and 4 ADAS-cog points per every 6 months, increasing with disease severity. Cognitive function was an important predictor of ADL-ability, which itself was the most important predictor of the risk of institutionalization and costs of care. Combining all models in a cross-validation process generated accurate predictions of costs of care at each 6 months follow-up.

CONCLUSION

The proposed methods for representing AD progression and economic outcomes can be used in micro-simulation models for the economic evaluation of new treatments.

Health state values for use in the economic evaluation of treatments for Alzheimer's disease

Alzheimer's disease (AD) is a chronic, progressive, neurodegenerative disease that places a heavy burden on people with the condition, their families and carers, health care systems and society in general. Health-related quality of life (HR-QOL) in patients deteriorates as the cognitive, behavioural and functional symptoms of AD develop. The human and financial cost of AD is forecast to grow rapidly as populations age, and those responsible for planning and financing health care face the challenge of allocating increasingly scarce resources against current and future interventions targeted towards AD. These include calls for early detection and diagnosis, preventative strategies, new medications, residential care, supportive care, and meeting the needs of carers as well as patients. Health care funders in many health systems now require a demonstration of the value of new interventions through a comparison of benefits in terms of improvements in HR-QOL and costs relative to those of competing or existing practices. Changes in HR-QOL provide the basis for the calculation of the quality-adjusted life-year (QALY), a key outcome used in economic evaluations to compare treatments within and between different disease conditions. The objective of this systematic review was to provide a summary of the published health state values (utilities) for AD patients and their carers that are currently available to estimate QALYs for use in health economic evaluations of interventions in AD. The health care literature was searched for articles published in English between 2000 and 2011, using keywords and variants including 'quality-adjusted life years', 'health state indicators', 'health utilities' and the specific names of generic measures of HR-QOL and health state valuation techniques. Databases searched included MEDLINE, EMBASE, NHS EED, PsycINFO and ISI Web of Science. This review identified 12 studies that reported utility values associated with health states in AD. Values for AD health states categorized according to cognitive impairment (where 1 = perfect health and 0 = dead) ranged from mild AD (0.52-0.73) to moderate AD (0.30-0.53) to severe AD (0.12-0.49). Utility values were almost all based on two generic measures of HR-QOL: the EQ-5D and Health Utility Index mark 2/3 (HUI2/3). There were no health state values estimated from condition- or disease-specific measures of HR-QOL. The review also identified 18 published cost-utility analyses (CUAs) of treatments for AD. The CUAs incorporated results from only three of the identified health state valuation studies. Twelve CUAs relied on the same study for health state values. We conclude that the literature on health state values in AD is limited and overly reliant on a single symptom (cognition) to describe disease progression. Other approaches to characterizing disease progression in AD based on multiple outcomes or dependency may be better predictors of costs and utilities in economic evaluations. Patient and proxy ratings were poorly correlated, particularly in patients with more advanced AD. However, proxy ratings displayed the validity and reliability across the entire range of AD severity needed to detect long-term changes relevant to economic evaluation. Further longitudinal research of patient and carer HR-QOL based on multidimensional measures of outcome and utilities is needed.

Cost-effectiveness of magnetic resonance imaging with a new contrast agent for the early diagnosis of Alzheimer's disease

Background

Used as contrast agents for brain magnetic resonance imaging (MRI), markers for beta-amyloid deposits might allow early diagnosis of Alzheimer's disease (AD). We evaluated the cost-effectiveness of such a diagnostic test, MRI+CLP (contrastophore-linker-pharmacophore), should it become clinically available.

Methodology/Principal Findings

We compared the cost-effectiveness of MRI+CLP to that of standard diagnosis using currently available cognition tests and of standard MRI, and investigated the impact of a hypothetical treatment efficient in early AD. The primary analysis was based on the current French context for 70-year-old patients with Mild Cognitive Impairment (MCI). In alternative “screen and treat” scenarios, we analyzed the consequences of systematic screenings of over-60 individuals (either population-wide or restricted to the ApoE4 genotype population). We used a Markov model of AD progression; model parameters, as well as incurred costs and quality-of-life weights in France were taken from the literature. We performed univariate and probabilistic multivariate sensitivity analyses.

The base-case preferred strategy was the standard MRI diagnosis strategy. In the primary analysis however, MRI+CLP could become the preferred strategy under a wide array of scenarios involving lower cost and/or higher sensitivity or specificity. By contrast, in the “screen and treat” analyses, the probability of MRI+CLP becoming the preferred strategy remained lower than 5%.

Conclusions/Significance

It is thought that anti-beta-amyloid compounds might halt the development of dementia in early stage patients. This study suggests that, even should such treatments become available, systematically screening the over-60 population for AD would only become cost-effective with highly specific tests able to diagnose early stages of the disease. However, offering a new diagnostic test based on beta-amyloid markers to elderly patients with MCI might prove cost-effective.

Evaluating the cost effectiveness of donepezil in the treatment of Alzheimer's disease in Germany using discrete event simulation

BACKGROUND

Previous cost-effectiveness studies of cholinesterase inhibitors have modeled Alzheimer's disease (AD) progression and treatment effects through single or global severity measures, or progression to "Full Time Care". This analysis evaluates the cost-effectiveness of donepezil versus memantine or no treatment in Germany by considering correlated changes in cognition, behavior and function.

METHODS

Rates of change were modeled using trial and registry-based patient level data. A discrete event simulation projected outcomes for three identical patient groups: donepezil 10 mg, memantine 20 mg and no therapy. Patient mix, mortality and costs were developed using Germany-specific sources.

RESULTS

Treatment of patients with mild to moderately severe AD with donepezil compared to no treatment was associated with 0.13 QALYs gained per patient, and 0.01 QALYs gained per caregiver and resulted in average savings of €7,007 and €9,893 per patient from the healthcare system and societal perspectives, respectively. In patients with moderate to moderately-severe AD, donepezil compared to memantine resulted in QALY gains averaging 0.01 per patient, and savings averaging €1,960 and €2,825 from the healthcare system and societal perspective, respectively.In probabilistic sensitivity analyses, donepezil dominated no treatment in most replications and memantine in over 70% of the replications. Donepezil leads to savings in 95% of replications versus memantine.

CONCLUSIONS

Donepezil is highly cost-effective in patients with AD in Germany, leading to improvements in health outcomes and substantial savings compared to no treatment. This holds across a variety of sensitivity analyses.

Dependence as a unifying construct in defining Alzheimer's disease severity

This article reviews measures of Alzheimer's disease (AD) progression in relation to patient dependence and offers a unifying conceptual framework for dependence in AD. Clinicians typically characterize AD by symptomatic impairments in three domains: cognition, function, and behavior. From a patient's perspective, changes in these domains, individually and in concert, ultimately lead to increased dependence and loss of autonomy. Examples of dependence in AD range from a need for reminders (early AD) to requiring safety supervision and assistance with basic functions (late AD). Published literature has focused on the clinical domains as somewhat separate constructs and has given limited attention to the concept of patient dependence as a descriptor of AD progression. This article presents the concept of dependence on others for care needs as a potential method for translating the effect of changes in cognition, function, and behavior into a more holistic, transparent description of AD progression.

Model-based economic evaluation in Alzheimer's disease: a review of the methods available to model Alzheimer's disease progression

OBJECTIVE

To consider the methods available to model Alzheimer's disease (AD) progression over time to inform on the structure and development of model-based evaluations, and the future direction of modelling methods in AD.

METHODS

A systematic search of the health care literature was undertaken to identify methods to model disease progression in AD. Modelling methods are presented in a descriptive review.

RESULTS

The literature search identified 42 studies presenting methods or applications of methods to model AD progression over time. The review identified 10 general modelling frameworks available to empirically model the progression of AD as part of a model-based evaluation. Seven of these general models are statistical models predicting progression of AD using a measure of cognitive function. The main concerns with models are on model structure, around the limited characterization of disease progression, and on the use of a limited number of health states to capture events related to disease progression over time. None of the available models have been able to present a comprehensive model of the natural history of AD.

CONCLUSIONS

Although helpful, there are serious limitations in the methods available to model progression of AD over time. Advances are needed to better model the progression of AD and the effects of the disease on peoples' lives. Recent evidence supports the need for a multivariable approach to the modelling of AD progression, and indicates that a latent variable analytic approach to characterising AD progression is a promising avenue for advances in the statistical development of modelling methods.

A review of the methods used to estimate the cost of Alzheimer's disease in the United States

BACKGROUN/RATIONALE: To determine the suitability of published estimates of the US cost of Alzheimer's disease (AD) for use in cost-effectiveness models for new AD treatments.

METHODS

A systematic literature review of published information on direct medical, direct nonmedical, indirect, and informal care costs for different levels of disease severity.

RESULTS

Nineteen studies were included in the review. In studies presenting mean costs by disease severity, the change in different types of costs with increasing disease severity varied, depending on the data sources and characteristics of patients with AD. In studies presenting the results of regression analyses, costs were shown to be independently associated with cognition, functional status, behavioral symptoms, and dependence.

CONCLUSIONS

Published US studies (1) did not include all the types of costs and AD populations, and (2) generally did not include all the measures of disease severity that are needed for cost-effectiveness models.

Cost effectiveness of donepezil in the treatment of mild to moderate Alzheimer's disease: a UK evaluation using discrete-event simulation

Recommendations in the UK suggest restricting treatment of Alzheimer's disease with cholinesterase inhibitors, on cost-effectiveness grounds, to patients with moderate cognitive decline. As the economic analyses that informed these recommendations have been the subject of debate, we sought to address the potential limitations of existing models and produce estimates of donepezil treatment cost effectiveness in the UK using the most recent available data and simulation techniques. A discrete-event simulation was developed that predicts progression of Alzheimer's disease through correlated changes in cognition, behavioural disturbance and function. Patient-level data from seven randomized, placebo-controlled donepezil trials and a 7-year follow-up registry provided the basis for modeling longitudinal outcomes. Individuals in the simulation were assigned unique demographic and clinical characteristics and then followed for 10 years, with severity of disease tracked on continuous scales. Patient mix and costs were developed from UK-specific literature. Analyses were run for severity subgroups to evaluate outcomes for sub-populations with disease of mild versus moderate severity from both a healthcare payer and societal perspective. All costs are reported in pound, year 2007 values, and all outcomes are discounted at 3.5% per annum. Over 10 years, treatment of all patients with mild to moderate disease reduces overall direct medical costs by an average of over pound2300 per patient. When unpaid caregiver time is also taken into consideration, savings increase to over pound4700 per patient. Compared with untreated patients, patients receiving donepezil experience a discounted gain in QALYs averaging 0.11, with their caregivers gaining, on average, 0.01 QALYs. For the subset of patients starting treatment with more severe disease, savings are more modest, averaging about pound1600 and pound3750 from healthcare and societal perspectives, respectively. In probabilistic sensitivity analyses, donepezil dominated no treatment between 57% and 62% of replications when only medical costs were considered, and between 74% and 79% of replications when indirect costs were included, with results more favourable for treatment initiation in the mild versus moderate severity stages of the disease. Although the simulation results are not definitive, they suggest that donepezil leads to health benefits and cost savings when used to treat mild to moderately severe Alzheimer's disease in the UK. They also indicate that both benefits and savings may be greatest when treatment is started while patients are still in the mild stages of Alzheimer's disease.