People get ready! A new generation of Alzheimer's therapies may require new ways to deliver and pay for healthcare.

The development of disease-modifying therapies (DMTs) for Alzheimer's disease (AD) has progressed over the last decade, and the first-ever therapies with potential to slow the progression of disease are approved in the United States. AD DMTs could provide life-changing opportunities for people living with this disease, as well as for their caregivers. They could also ease some of the immense societal and economic burden of dementia. However, AD DMTs also come with major challenges due to the large unmet medical need, high prevalence of AD, new costs related to diagnosis, treatment and monitoring, and uncertainty in the therapies' actual clinical value. This perspective article discusses, from the broad perspective of various health systems and stakeholders, how we can overcome these challenges and improve society's readiness for AD DMTs. We propose that innovative payment models such as performance-based payments, in combination with learning healthcare systems, could be the way forward to enable timely patient access to treatments, improve accuracy of cost-effectiveness evaluations and overcome budgetary barriers. Other important considerations include the need for identification of key drivers of patient value, the relevance of different economic perspectives (i.e. healthcare vs. societal) and ethical questions in terms of treatment eligibility criteria.

New 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 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 "ICER" and "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, QALY gains and cost savings were 21-31% smaller compared to the ICER model and 36-56% smaller compared to 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 opens-source model framework for researchers and decision-makers to cross-validate other (HTA submission) models and perform additional uncertainty analyses, setting an example for open science in AD decision modeling and supporting important reimbursement decisions.

The 2022 symposium on dementia and brain aging in low- and middle-income countries: Highlights on research, diagnosis, care, and impact.

Two of every three persons living with dementia reside in low- and middle-income countries (LMICs). The projected increase in global dementia rates is expected to affect LMICs disproportionately. However, the majority of global dementia care costs occur in high-income countries (HICs), with dementia research predominantly focusing on HICs. This imbalance necessitates LMIC-focused research to ensure that characterization of dementia accurately reflects the involvement and specificities of diverse populations. Development of effective preventive, diagnostic, and therapeutic approaches for dementia in LMICs requires targeted, personalized, and harmonized efforts. Our article represents timely discussions at the 2022 Symposium on Dementia and Brain Aging in LMICs that identified the foremost opportunities to advance dementia research, differential diagnosis, use of neuropsychometric tools, awareness, and treatment options. We highlight key topics discussed at the meeting and provide future recommendations to foster a more equitable landscape for dementia prevention, diagnosis, care, policy, and management in LMICs. HIGHLIGHTS: Two-thirds of persons with dementia live in LMICs, yet research and costs are skewed toward HICs. LMICs expect dementia prevalence to more than double, accompanied by socioeconomic disparities. The 2022 Symposium on Dementia in LMICs addressed advances in research, diagnosis, prevention, and policy. The Nairobi Declaration urges global action to enhance dementia outcomes in LMICs.

Structural equation modeling for identifying the drivers of health-related quality of life improvement experienced by patients with migraine receiving eptinezumab.

BACKGROUND: As new migraine therapies emerge, it is crucial for measures to capture the complexities of health-related quality of life (HRQoL) improvement beyond improvements in monthly migraine day (MMD) reduction. Investigations into the correlations between MMD reduction, symptom management, and HRQoL are lacking, particularly those that focus on improvements in canonical symptoms and improvement in patient-identified most-bothersome symptoms (PI-MBS), in patients treated with eptinezumab. This exploratory analysis identified efficacy measures mediating the effect of eptinezumab on HRQoL improvements in patients with migraine. METHODS: Data from the DELIVER study of patients with 2-4 prior preventive migraine treatment failures (NCT04418765) were inputted to two structural equation models describing sources of HRQoL improvement via Migraine-Specific Quality-of-Life Questionnaire (MSQ) scores. A single latent variable was defined to represent HRQoL and describe the sources of HRQoL in DELIVER. One model included all migraine symptoms while the second model included the PI-MBS as the only migraine symptom. Mediating variables capturing different aspects of efficacy included MMDs, other canonical symptoms, and PI-MBS. RESULTS: In the first model, reductions in MMDs and other canonical symptoms accounted for 35% (standardized effect size [SES] - 0.11) and 25% (SES - 0.08) of HRQoL improvement, respectively, with 41% (SES - 0.13) of improvement comprising "direct treatment effect," i.e., unexplained by mediators. In the second model, substantial HRQoL improvement with eptinezumab (86%; SES - 0.26) is due to MMD reduction (17%; SES - 0.05) and change in PI-MBS (69%; SES - 0.21). CONCLUSIONS: Improvements in HRQoL experienced by patients treated with eptinezumab can be substantially explained by its effect on migraine frequency and PI-MBS. Therefore, in addition to MMD reduction, healthcare providers should discuss PI-MBS improvements, since this may impact HRQoL. Health technology policymakers should consider implications of these findings in economic evaluation, as they point to alternative measurement of quality-adjusted life years to capture fully treatment benefits in cost-utility analyses. TRIAL REGISTRATION: ClinicalTrials.gov (Identifier: NCT04418765 ; EudraCT (Identifier: 2019-004497-25; URL: https://www.clinicaltrialsregister.eu/ctr-search/search?query=2019-004497-25 ).

Associations of Orthostatic Hypotension and Frailty With Dementia and Mortality in Older Adults: A Population-Based Cohort Study.

BACKGROUND: This study aimed to assess the associations of orthostatic hypotension (OH), in the presence or absence of frailty, with dementia and mortality in older adults. METHODS: We conducted a 15-year population-based cohort study including 2 703 baseline dementia-free individuals from the Swedish National Study on Aging and Care in Kungsholmen. At baseline, OH was defined as a decline in systolic/diastolic blood pressure ≥20/10 mm Hg 1 minute after standing up from a supine position. Frailty status was defined following Fried's frailty phenotype. Dementia was diagnosed following the Diagnostic and Statistical Manual of Mental Disorders-fourth edition criteria. Multistate flexible parametric survival models were used to estimate associations of OH and frailty with dementia and mortality. RESULTS: Robust people with OH (adjusted hazard ratio [HR] = 2.28; 95% confidence interval [CI] = 1.47-3.54) and frail people without OH (HR = 1.98; 95% CI = 1.40-2.82) or with OH (HR = 2.73; 95% CI = 1.82-4.10) had a higher dementia risk than OH-free and robust people. Moreover, frail people, independently of the presence of OH, had higher mortality rate than OH-free and robust people. In individuals who developed dementia during the follow-up period, neither OH nor frailty was significantly associated with mortality. CONCLUSIONS: Older adults with OH, whether robust or frail, may have a higher dementia risk than those without OH. Older adults with OH, when having frailty, may have a higher mortality rate than those without OH. The concurrent assessments of OH and frailty may provide prognostic values in terms of dementia and mortality risk in older adults.

Progression analysis versus traditional methods to quantify slowing of disease progression in Alzheimer's disease.

BACKGROUND: The clinical meaningfulness of the effects of recently approved disease-modifying treatments (DMT) in Alzheimer's disease is under debate. Available evidence is limited to short-term effects on clinical rating scales which may be difficult to interpret and have limited intrinsic meaning to patients. The main value of DMTs accrues over the long term as they are expected to cause a delay or slowing of disease progression. While awaiting such evidence, the translation of short-term effects to time delays or slowing of progression could offer a powerful and readily interpretable representation of clinical outcomes. METHODS: We simulated disease progression trajectories representing two arms, active and placebo, of a hypothetical clinical trial of a DMT. The placebo arm was simulated based on estimated mean trajectories of clinical dementia rating scale-sum of boxes (CDR-SB) recordings from amyloid-positive subjects with mild cognitive impairment (MCI) from Alzheimer's Disease Neuroimaging Initiative (ADNI). The active arm was simulated to show an average slowing of disease progression versus placebo of 20% at each visit. The treatment effects in the simulated trials were estimated with a progression model for repeated measures (PMRM) and a mixed model for repeated measures (MMRM) for comparison. For PMRM, the treatment effect is expressed in units of time (e.g., days) and for MMRM in units of the outcome (e.g., CDR-SB points). PMRM results were implemented in a health economics Markov model extrapolating disease progression and death over 15 years. RESULTS: The PMRM model estimated a 19% delay in disease progression at 18 months and 20% (~ 7 months delay) at 36 months, while the MMRM model estimated a 25% reduction in CDR-SB (~ 0.5 points) at 36 months. The PMRM model had slightly greater power compared to MMRM. The health economic model based on the estimated time delay suggested an increase in life expectancy (10 months) without extending time in severe stages of disease. CONCLUSION: PMRM methods can be used to estimate treatment effects in terms of slowing of progression which translates to time metrics that can be readily interpreted and appreciated as meaningful outcomes for patients, care partners, and health care practitioners.