Florbetaben PET in the Early Diagnosis of Alzheimer's Disease: A Discrete Event Simulation to Explore Its Potential Value and Key Data Gaps

Charting the Next Road Map for CSF Biomarkers in Alzheimer's Disease and Related Dementias

Clinical prediction of underlying pathologic substrates in people with Alzheimer's disease (AD) dementia or related dementia syndromes (ADRD) has limited accuracy. Etiologic biomarkers - including cerebrospinal fluid (CSF) levels of AD proteins and cerebral amyloid PET imaging - have greatly modernized disease-modifying clinical trials in AD, but their integration into medical practice has been slow. Beyond core CSF AD biomarkers (including beta-amyloid 1-42, total tau, and tau phosphorylated at threonine 181), novel biomarkers have been interrogated in single- and multi-centered studies with uneven rigor. Here, we review early expectations for ideal AD/ADRD biomarkers, assess these goals' future applicability, and propose study designs and performance thresholds for meeting these ideals with a focus on CSF biomarkers. We further propose three new characteristics: equity (oversampling of diverse populations in the design and testing of biomarkers), access (reasonable availability to 80% of people at risk for disease, along with pre- and post-biomarker processes), and reliability (thorough evaluation of pre-analytical and analytical factors influencing measurements and performance). Finally, we urge biomarker scientists to balance the desire and evidence for a biomarker to reflect its namesake function, indulge data- as well as theory-driven associations, re-visit the subset of rigorously measured CSF biomarkers in large datasets (such as Alzheimer's disease neuroimaging initiative), and resist the temptation to favor ease over fail-safe in the development phase. This shift from discovery to application, and from suspended disbelief to cogent ingenuity, should allow the AD/ADRD biomarker field to live up to its billing during the next phase of neurodegenerative disease research.

Cost-effectiveness of Alzheimer's disease CSF biomarkers and amyloid-PET in early-onset cognitive impairment diagnosis

This study aimed at determining the cost-effectiveness of amyloid-positron emission tomography (PET) compared to Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers (amyloid-β₄₂, total-Tau and phosphorylated-Tau) for the diagnosis of AD in patients with early-onset cognitive impairment. A decision tree model using a national health care perspective was developed to compare the costs and effectiveness associated with Amyloid-PET and AD CSF biomarkers. Available evidence from the literature and primary data from Hospital Clínic de Barcelona were used to inform the model and calculate the efficiency of these diagnostic alternatives. Medical visits and diagnostic procedures were considered and reported in €2020. We calculated the incremental cost-effectiveness ratio to measure the cost per % of correct diagnoses detected and we perform one-way deterministic and probabilistic sensitivity analyses to assess the uncertainty of these results. Compared with AD CSF biomarkers, Amyloid-PET resulted in 7.40% more correctly diagnosed cases of AD, with an incremental total mean cost of €146,854.80 per 100 cases. We found a 50% of probability that Amyloid-PET was cost-effective for a willingness to pay (WTP) of €19,840.39 per correct case detected. Using a WTP of €75,000, the probability that it is cost-effective reached a maximum of 76.9%, thus leading to a conclusion that Amyloid-PET is not a cost-effective technique compared to AD CSF biomarkers, unless the funder is willing to pay a minimum of €19,840.39 to detect one more correct case. Furthermore, obtaining CSF provides simultaneous information on amyloid β and tau biomarkers and allows other biomarkers to be analyzed at a relatively low cost.

Cost-effectiveness of using amyloid positron emission tomography in individuals with mild cognitive impairment

Background

Amyloid positron emission tomography (PET) makes it possible to diagnose Alzheimer’s disease (AD) in its prodromal phase including mild cognitive impairment (MCI). This study evaluated the cost-effectiveness of including amyloid-PET for assessing individuals with MCI.

Methods

The target population was 60-year-old patients who were diagnosed with MCI. We constructed a Markov model for the natural history of AD with the amyloid positivity (AP). Because amyloid-PET can detect the AP MCI state, AD detection can be made faster by reducing the follow-up interval for a high-risk group. The health outcomes were evaluated in quality-adjusted life years (QALYs) and the final results of cost-effectiveness analysis were presented in the form of the Incremental Cost-Effectiveness Ratio (ICER). To handle parameter uncertainties, one-way sensitivity analyses for various variables were performed.

Results

Our model showed that amyloid-PET increased QALYs by 0.003 in individuals with MCI. The estimated additional costs for adopting amyloid-PET amounted to a total of 1250 USD per patient when compared with the cost when amyloid-PET is not adopted. The ICER was 3,71,545 USD per QALY. According to the sensitivity analyses, treatment effect of Donepezil and virtual intervention effect in MCI state were the most influential factors.

Conclusions

In our model, using amyloid-PET at the MCI stage was not cost-effective. Future advances in management of cognitive impairment would enhance QALYs, and consequently improve cost-effectiveness.

Outcomes of clinical utility in amyloid-PET studies: state of art and future perspectives

PURPOSE

To review how outcomes of clinical utility are operationalized in current amyloid-PET validation studies, to prepare for formal assessment of clinical utility of amyloid-PET-based diagnosis.

METHODS

Systematic review of amyloid-PET research studies published up to April 2020 that included outcomes of clinical utility. We extracted and analyzed (a) outcome categories, (b) their definition, and (c) their methods of assessment.

RESULTS

Thirty-two studies were eligible. (a) Outcome categories were clinician-centered (found in 25/32 studies, 78%), patient-/caregiver-centered (in 9/32 studies, 28%), and health economics-centered (5/32, 16%). (b) Definition: Outcomes were mainly defined by clinical researchers; only the ABIDE study expressly included stakeholders in group discussions. Clinician-centered outcomes mainly consisted of incremental diagnostic value (25/32, 78%) and change in patient management (17/32, 53%); patient-/caregiver-centered outcomes considered distress after amyloid-pet-based diagnosis disclosure (8/32, 25%), including quantified burden of procedure for patients' outcomes (n = 8) (1/8, 12.5%), impact of disclosure of results (6/8, 75%), and psychological implications of biomarker-based diagnosis (75%); and health economics outcomes focused on costs to achieve a high-confidence etiological diagnosis (5/32, 16%) and impact on quality of life (1/32, 3%). (c) Assessment: all outcome categories were operationalized inconsistently across studies, employing 26 different tools without formal rationale for selection.

CONCLUSION

Current studies validating amyloid-PET already assessed outcomes for clinical utility, although non-clinician-based outcomes were inconsistent. A wider participation of stakeholders may help produce a more thorough and systematic definition and assessment of outcomes of clinical utility and help collect evidence informing decisions on reimbursement of amyloid-PET.

Computer simulation of dementia care demand heterogeneity using hybrid simulation methods: improving population-level modelling with individual patient decline trajectories

OBJECTIVES

The aim of the study was to model dementia prevalence and outcomes within an ageing population using a novel hybrid simulation model that simultaneously takes population-level and patient-level perspectives to better inform dementia care service planning, taking into account severity progression variability.

STUDY DESIGN

This is a simulation study.

METHODS

We developed a hybrid computer simulation combining different methods to best represent population and individual dementia dynamics. Individual patient outcomes are aggregated into three progression rate types to report the effects of severity progression variability and intervention benefits.

RESULTS

Fast progression of dementia severity is associated with higher annual care cost and short overall survival duration. Those patients are more likely to develop moderate to severe symptoms more quickly, highlighting a need for more urgent provision of appropriate care services. Slower severity progression is associated with lower annual care costs, but longer survival requires higher overall financial provision. Although lifestyle interventions reduce overall care costs, treatment and lifestyle intervention benefits are modest at the population level.

CONCLUSIONS

Individual variation of dementia decline is an important factor to include in planning adequate levels of care services and to ensure timely and appropriate service availability. Hybrid simulation models provide useful insights at the population and individual level, supporting effective decision-making.

How relevant are social costs in economic evaluations? The case of Alzheimer's disease

BACKGROUND

The main objective of this study was to analyse how the inclusion (exclusion) of social costs can alter the results and conclusions of economic evaluations in the field of Alzheimer's disease interventions.

METHODS

We designed a systematic review that included economic evaluations in Alzheimer's disease. The search strategy was launched in 2000 and ran until November 2018. The inclusion criteria were: being an original study published in a scientific journal, being an economic evaluation of any intervention related to Alzheimer's disease, including social costs (informal care costs and/or productivity losses), being written in English, using QALYs as an outcome for the incremental cost-utility analysis, and separating the results according to the perspective applied.

RESULTS

It was finally included 27 studies and 55 economic evaluations. Around 11% of economic evaluations changed their main conclusions. More precisely, three of them concluded that the new intervention became cost-effective when the societal perspective was considered, whereas when using just the health care payer perspective, the new intervention did not result in a cost-utility ratio below the threshold considered. Nevertheless, the inclusion of social cost can also influence the results, as 37% of the economic evaluations included became the dominant strategy after including social costs when they were already cost-effective in the health care perspective.

CONCLUSIONS

Social costs can substantially modify the results of the economic evaluations. Therefore, taking into account social costs in diseases such as Alzheimer's can be a key element in making decisions about public financing and pricing of health interventions.

Incremental value of amyloid-PET versus CSF in the diagnosis of Alzheimer's disease

PURPOSE

To compare the incremental diagnostic value of amyloid-PET and CSF (Aβ42, tau, and phospho-tau) in AD diagnosis in patients with mild cognitive impairment (MCI) or mild dementia, in order to improve the definition of diagnostic algorithm.

METHODS

Two independent dementia experts provided etiological diagnosis and relative diagnostic confidence in 71 patients on 3 rounds, based on (1) clinical, neuropsychological, and structural MRI information alone; (2) adding one biomarker (CSF amyloid and tau levels or amyloid-PET with a balanced randomized design); and (3) adding the other biomarker.

RESULTS

Among patients with a pre-biomarker diagnosis of AD, negative PET induced significantly more diagnostic changes than amyloid-negative CSF at both rounds 2 (CSF 67%, PET 100%, P = 0.028) and 3 (CSF 0%; PET 78%, P < 0.001); PET induced a diagnostic confidence increase significantly higher than CSF on both rounds 2 and 3.

CONCLUSIONS

Amyloid-PET should be prioritized over CSF biomarkers in the diagnostic workup of patients investigated for suspected AD, as it provides greater changes in diagnosis and diagnostic confidence.

TRIAL REGISTRATION

EudraCT no.: 2014-005389-31.

Family and Caregiver Spillover Effects in Cost-Utility Analyses of Alzheimer's Disease Interventions

BACKGROUND AND OBJECTIVE

Alzheimer's disease or dementia can impose a significant burden on family and other informal caregivers. This study investigated how the inclusion of family/informal caregiver spillover effects in a cost-utility analysis may influence the reported value of Alzheimer's disease/dementia interventions.

METHODS

We used PubMed to identify Alzheimer's disease or dementia cost-utility analyses published from 1 January, 2000 to 31 March, 2018. We reviewed and abstracted information from each study using a two-reader consensus process. We investigated the frequency and methods in which family/caregiver spillover costs and health effects were incorporated into cost-utility analyses, and examined how their inclusion may influence the reported incremental cost-effectiveness ratios.

RESULTS

Of 63 Alzheimer's disease/dementia cost-utility analyses meeting inclusion criteria, 44 (70%) considered at least some family/caregiver spillover costs or health effects. Thirty-two studies incorporated spillover costs only, two incorporated spillover health effects only, and ten incorporated both. The most common approach for accounting for spillover was adding informal caregiving time costs to patient costs (n = 36) and adding informal caregiver quality-adjusted life-years to patient values (n = 7). In a subset of 33 incremental cost-effectiveness ratio pairs from 19 studies, incorporating spillover outcomes made incremental cost-effectiveness ratios more favorable (n = 15; 45%) or kept the intervention cost saving (n = 13; 39%) in most cases. In fewer cases, including spillover increased incremental cost-effectiveness ratios (n = 2; 6%), kept the intervention dominated [more costs/less quality-adjusted life-years] (n = 2; 6%), or changed incremental cost-effectiveness ratio from dominated to less cost/less quality-adjusted life-years (n = 1; 3%). In 11 cases (33%), adding spillover effects into analyses resulted in a lower incremental cost-effectiveness ratio that crossed a common cost-effectiveness threshold, which could have downstream implications for programs or policies that are adopted based on cost-effectiveness analysis results.

DISCUSSION

Most Alzheimer's disease/dementia cost-utility analyses incorporated spillover costs, often as caregiver time costs, but considered spillover health impacts less often. In about 85% of the analyses, including Alzheimer's disease/dementia spillover cost or health effects decreased incremental cost-effectiveness ratios or kept the intervention cost saving. The broader value of an Alzheimer's disease/dementia intervention to society may in some cases be underestimated without considering these spillover effects on family and informal caregivers.

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.

Clinical Use and Utility of Amyloid Imaging

Currently, 3 amyloid PET tracers are approved and commercially available for clinical use. They allow for the accurate in vivo detection of amyloid plaques, one hallmark of Alzheimer disease. Here, we review the current knowledge on the clinical use and utility of amyloid imaging. Appropriate use criteria for the clinical application of amyloid imaging are established, and most currently available data point to their validity. Visual amyloid image analysis is highly standardized. Disclosure of amyloid imaging results is desired by many cognitively impaired subjects and seems to be safe once appropriate education is delivered to the disclosing clinicians. Regarding clinical utility, increasing evidence points to a change in diagnosis via amyloid imaging in about 30% of cases, to an increase in diagnostic confidence in about 60% of cases, to a change in patient management in about 60% of cases, and specifically to a change in medication in about 40% of cases. Also, amyloid imaging results seem to have a relevant impact on caregivers. Further, initial simulation studies point to a potential positive effect on patient outcome and to cost effectiveness of amyloid imaging. These features, however, will require confirmation in prospective clinical trials. More work is also required to determine the clinical utility of amyloid imaging specifically in subjects with mild cognitive impairment and in comparison with or in conjunction with other Alzheimer disease biomarkers. In summary, the clinical use of amyloid imaging is being studied, and the currently available data point to a relevant clinical utility of this imaging technique. Ongoing research will determine whether this accurate and noninvasive approach to amyloid plaque load detection will translate into a benefit to cognitively impaired subjects.

Clinical and cost implications of amyloid beta detection with amyloid beta positron emission tomography imaging in early Alzheimer's disease - the case of florbetapir

OBJECTIVE

Amyloid beta (Aβ) positron emission tomography (PET) imaging helps estimate Aβ neuritic plaque density in patients with cognitive impairment who are under evaluation for Alzheimer's disease (AD). This study aims to evaluate the cost-effectiveness of the Aβ-PET scan as an adjunct to standard diagnostic assessment for diagnosis of AD in France, using florbetapir as an example.

METHODS

A state-transition probability analysis was developed adopting the French Health Technology Assessment (HTA) perspective per guidance. Parameters included test characteristics, rate of cognitive decline, treatment effect, costs, and quality of life. Additional scenarios assessed the validity of the analytical framework, including: (1) earlier evaluation/treatment; (2) cerebrospinal fluid (CSF) as a comparator; and (3) use of other diagnostic procedures. Outputs included differences in quality-adjusted life years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs). All benefits and costs were discounted for time preferences. Sensitivity analyses were performed to assess the robustness of findings and key influencers of outcomes.

RESULTS

Aβ-PET used as an adjunct to standard diagnostic assessment increased QALYs by 0.021 years and 10 year costs by €470 per patient. The ICER was €21,888 per QALY gained compared to standard diagnostic assessment alone. When compared with CSF, Aβ-PET costs €24,084 per QALY gained. In other scenarios, Aβ-PET was consistently cost-effective relative to the commonly used affordability threshold (€40,000 per QALY). Over 95% of simulations in the sensitivity analysis were cost-effective.

CONCLUSION

Aβ-PET is projected to affordably increase QALYs from the French HTA perspective per guidance over a range of clinical scenarios, comparators, and input parameters.

[Amyloid positron-emission-tomography with [18 F]-florbetaben in the diagnostic workup of dementia patients]

BACKGROUND

To this day the definite diagnosis of Alzheimer's disease still relies on post-mortem histopathological detection of neurofibrillary tangles and beta-amyloid deposits. Amyloid positron emission tomography (PET) is a new diagnostic tool that enables the in vivo quantification of pathological beta-amyloid deposits. The aim of the current study was to evaluate to what extent ¹⁸F-florbetaben-PET (FBB-PET) influences the diagnosis of patients with dementia.

MATERIAL AND METHODS

Imaging with FBB-PET was performed on 33 patients from our outpatient department for cognitive neurology. Beforehand all patients underwent a comprehensive clinical, neuropsychiatric and laboratory examination as well as imaging by means of magnetic resonance imaging (MRI) and fluorodeoxyglucose-PET. The working diagnoses before and after FBB-PET imaging were compared.

RESULTS

17 out of 33 patients were scored as FBB-PET positive. In four cases the initial diagnosis had to be changed to Alzheimer's disease (three cases) and cerebral amyloid angiopathy (one case) due to the positive FBB-PET scan. 16 patients showed a negative FBB-PET scan. In three patients the initial diagnosis of Alzheimer's disease could be ruled out due to the negative FBB-PET scan. Overall, in 7 out of 33 examined patients the initial diagnosis had to be changed because of the findings of the FBB-PET scan. In 24 patients the initial diagnosis was confirmed by the results of the FBB-PET scan.

CONCLUSION

Amyloid-PET is currently no standard procedure in the diagnosis of dementia; however, it can be a helpful additional diagnostic tool when used according to the "Appropriate Use Criteria" and the S3 guidelines on dementia in cases of unclear clinical presentation, atypically early age of onset as well as in patients with persistent or progressive unexplained mild cognitive impairment. By facilitating early diagnosis amyloid-PET imaging allows patient selection for therapeutic drug trials.

Beta-amyloid imaging with florbetaben

Florbetaben is a fluorine-18 (18F)-labeled stilbene derivative that was developed as a positron emission tomography (PET) tracer for routine clinical application to visualize β-amyloid plaques in the Alzheimer's disease (AD) brain. The tracer successfully completed a global multicenter phase 0-III development program and was, as a consequence, recently approved by the US Food and Drug Administration and the European Medicines Agency. This review provides an overview on the florbetaben tracer characteristics and preclinical data leading to its human testing. Further, the favorable results of human pharmacokinetics, safety, and dosimetry evaluation of florbetaben are presented. Next, the results of the clinical testing of florbetaben are discussed, in which the tracer was shown to sensitively and specifically detect β-amyloid neuritic plaques, as evidenced by employing different gold standards (from clinical diagnosis to post mortem histopathology). The potential of florbetaben to predict AD dementia in cases of mild cognitive impairment and to assist in the differential diagnosis in cases of dementia is also described. Finally, potential clinical impact and clinical routine PET image acquisition and analysis protocols for florbetaben are discussed. Taken together, the evidence shows that florbetaben is a valuable β-amyloid-targeting PET tracer in the clinic with great potential to serve as a biomarker supporting clinical AD diagnosis.

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.

When to use discrete event simulation (DES) for the economic evaluation of health technologies? A review and critique of the costs and benefits of DES

Modelling in economic evaluation is an unavoidable fact of life. Cohort-based state transition models are most common, though discrete event simulation (DES) is increasingly being used to implement more complex model structures. The benefits of DES relate to the greater flexibility around the implementation and population of complex models, which may provide more accurate or valid estimates of the incremental costs and benefits of alternative health technologies. The costs of DES relate to the time and expertise required to implement and review complex models, when perhaps a simpler model would suffice. The costs are not borne solely by the analyst, but also by reviewers. In particular, modelled economic evaluations are often submitted to support reimbursement decisions for new technologies, for which detailed model reviews are generally undertaken on behalf of the funding body. This paper reports the results from a review of published DES-based economic evaluations. Factors underlying the use of DES were defined, and the characteristics of applied models were considered, to inform options for assessing the potential benefits of DES in relation to each factor. Four broad factors underlying the use of DES were identified: baseline heterogeneity, continuous disease markers, time varying event rates, and the influence of prior events on subsequent event rates. If relevant, individual-level data are available, representation of the four factors is likely to improve model validity, and it is possible to assess the importance of their representation in individual cases. A thorough model performance evaluation is required to overcome the costs of DES from the users' perspective, but few of the reviewed DES models reported such a process. More generally, further direct, empirical comparisons of complex models with simpler models would better inform the benefits of DES to implement more complex models, and the circumstances in which such benefits are most likely.