Alzheimer Disease: Neumann PJ

Cohen JT, Neumann PJ. · Center for the Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, Tufts-New England Medical Center, Boston, MA, USA. · Alzheimers Dement. · Pubmed #18631970 No free full text.

Abstract: Decision analytic policy models for Alzheimer's disease (AD) enable researchers and policy makers to investigate questions about the costs and benefits of a wide range of existing and potential screening, testing, and treatment strategies. Such models permit analysts to compare existing alternatives, explore hypothetical scenarios, and test the strength of underlying assumptions in an explicit, quantitative, and systematic way. Decision analytic models can best be viewed as complementing clinical trials both by filling knowledge gaps not readily addressed by empirical research and by extrapolating beyond the surrogate markers recorded in a trial. We identified and critiqued 13 distinct AD decision analytic policy models published since 1997. Although existing models provide useful insights, they also have a variety of limitations. (1) They generally characterize disease progression in terms of cognitive function and do not account for other distinguishing features, such as behavioral symptoms, functional performance, and the emotional well-being of AD patients and caregivers. (2) Many describe disease progression in terms of a limited number of discrete states, thus constraining the level of detail that can be used to characterize both changes in patient status and the relationships between disease progression and other factors, such as residential status, that influence outcomes of interest. (3) They have focused almost exclusively on evaluating drug treatments, thus neglecting other disease management strategies and combinations of pharmacologic and nonpharmacologic interventions. Future AD models should facilitate more realistic and compelling evaluations of various interventions to address the disease. An improved model will allow decision makers to better characterize the disease, to better assess the costs and benefits of a wide range of potential interventions, and to better evaluate the incremental costs and benefits of specific interventions used in conjunction with other disease management strategies.

Neumann PJ, Goldie SJ, Weinstein MC. · Program on the Economic Evaluation of Medical Technology, Center for Risk Analysis, Harvard School of Public Health, Boston, Massachusetts 02115, USA. · Annu Rev Public Health. · Pubmed #10884966 No free full text.

Abstract: Estimating preferences for states of health has been an active area of research in recent years. Unlike psychophysical approaches, which discriminate levels of health status, preference-based approaches incorporate values or utilities for health outcomes and can be used in cost-effectiveness analyses to aid resource allocation decisions. This chapter considers issues and controversies involved in using preference-based measures in economic evaluation in health care, with a particular emphasis on cost-utility analysis and the estimation of quality-adjusted life years. Topics considered include techniques for measuring preferences, the use of preference-based classification systems, the relationship between patient and community preferences, methods for obtaining utilities from clinical trials, mapping health status from health utilities, the development of "off-the-shelf" preference weights, and proposed alternatives to quality-adjusted life years. We also consider applications of cost-utility analyses to public health interventions. Although cost-utility analyses have become more popular recently, many challenges remain for the field. Widespread acceptance of the methodology likely awaits more consensus on measurement techniques, as well as educational efforts in the public health and medical communities on the usefulness of the approach.

Neumann PJ. · Department of Health Policy and Management and Center for Risk Analysis, Harvard School of Public Health, Boston, Massachusetts, USA. · Pharmacoeconomics. · Pubmed #15960551 No free full text.

Abstract: The National Institute for Health and Clinical Excellence (NICE) provisional decision against memantine and other medications for Alzheimer's disease (AD) has generated much discussion. In its decision, NICE expressed concern about the data source used for the utility scores in the industry submission of the memantine model. NICE therefore turned to an alternative data source. However, in doing so, it made the key assumption that moderate-to-severe AD patients living in the community were independent. Furthermore, the NICE data source also had its limitations.There are numerous limitations in inferring from available data how utilities vary between dependent and non-dependent patients with AD. Most importantly, we lack direct evidence from primary data. Nonetheless, it seems reasonable to assume that patients with severe AD, and likely those with moderate AD as well, have full-time care needs, regardless of their setting. The NICE assumption that they do not results in a difference in utilities between dependent and non-dependent AD individuals of only 0.06. This seems to be at the low end of what one would consider a reasonable estimate.

McMahon PM, Araki SS, Sandberg EA, Neumann PJ, Gazelle GS. · Institute for Technology Assessment, Massachusetts General Hospital, Zero Emerson Place, Suite 2H, Boston, MA 02114, USA. · Radiology. · Pubmed #12802006 links to  free full text

Abstract: PURPOSE: To evaluate the cost-effectiveness of positron emission tomography (PET) in the diagnosis of Alzheimer disease (AD) in community-dwelling patients with mild or moderate dementia who present to specialized AD centers. MATERIALS AND METHODS: A decision-analytic model was used to compare costs and quality-adjusted life years (QALYs) associated with strategies involving single photon emission computed tomography (SPECT), dynamic susceptibility-weighted contrast material-enhanced magnetic resonance (MR) imaging, and PET as functional imaging adjuncts to the standard clinical work-up. Sensitivity analyses were performed to examine changes in test characteristics, health-related quality-of-life survey instruments, therapeutic effectiveness, and treatment rules. RESULTS: The use of PET to confirm the results of the standard clinical work-up cost more but yielded fewer benefits than a strategy in which dynamic susceptibility-weighted contrast-enhanced MR imaging was substituted for the typically performed structural computed tomography. This relationship remained stable in scenarios in which standard diagnostic work-up accuracy, drug treatment effectiveness, and version of the Health Utilities Index were altered. Dynamic susceptibility-weighted contrast-enhanced MR imaging cost US dollars 598800 per QALY gained (range, US dollars 74400 to US dollars 1.9 million per QALY), compared with the cost of the standard diagnostic work-up. Treating all patients with dementia was the dominant imaging strategy, except when side effects in patients with non-AD-related dementia were modeled. In all scenarios, SPECT yielded fewer benefits than other strategies at a higher cost. CONCLUSION: PET may have high diagnostic accuracy, but adding it to the standard diagnostic regimen at AD clinics would yield limited, if any, benefits at very high costs.

Doraiswamy PM, Leon J, Cummings JL, Marin D, Neumann PJ. · Department of Psychiatry, Duke University Medical Center, Durham, North Carolina 27710, USA. · J Gerontol A Biol Sci Med Sci. · Pubmed #11867654 No free full text.

Abstract: BACKGROUND: We examined the prevalence of comorbid medical illnesses in Alzheimer's disease (AD) patients at different severity levels. We also examined the effect of cumulative medical comorbidity on cognition and function. METHODS: Analyses of data from 679 AD patients (Mini-Mental State Exam score range 0-30, mean +/- SD = 11.8 +/- 8) from 13 sites (four dementia centers assessing outpatients, four managed care organizations, two assisted living facilities, and three nursing homes) prospectively recruited using a stratification approach including dementia severity and care setting. Medical comorbidity was quantified using the Cumulative Illness Rating Scale-Geriatric. RESULTS: Across patients, 61% had three or more comorbid medical illnesses. Adjusting for age, gender, race, and care setting, medical comorbidity increased with dementia severity (mild to moderate, p <.01; moderate to severe, p <.001). Adjusting for age, educational level, gender, race, and care setting, higher medical comorbidity was associated with greater impairment in cognition (p <.001) and in self-care (p <.001). CONCLUSIONS: Despite the limitation of a cross-sectional design, our initial findings suggest that there is a strong association between medical comorbidity and cognitive status in AD. Optimal management of medical illnesses may offer potential to improve cognition in AD.

Neumann PJ, Araki SS, Arcelus A, Longo A, Papadopoulos G, Kosik KS, Kuntz KM, Bhattacharjya A. · Program on the Economic Evaluation of Medical Technology, Center for Risk Analysis, Harvard School of Public Health, Boston, MA 02115, USA. · Neurology. · Pubmed #11571317 No free full text.

Abstract: OBJECTIVES: To estimate annual transition probabilities (i.e., the likelihood that a patient will move from one disease stage to another in a given time period) for AD progression. Transition probabilities are estimated by disease stages (mild, moderate, severe) and settings of care (community, nursing home), accounting for differences in age, gender, and behavioral symptoms as well as the length of time a patient has been in a disease stage. Methods: Using data from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), the authors employed a modified survival analysis to estimate stage-to-stage and stage-to-nursing home transition probabilities. To account for individual variability, a Cox proportional hazards model was fit to the CERAD data to estimate hazard ratios for gender, age (50 to 64, 65 to 74, and more than 75 years), and level of behavioral symptoms (low/high, according to responses to the Behavioral Rating Scale for Dementia) for each of the key stage-to-stage and stage-to-nursing home transitions. RESULTS: The transition probabilities underscore the rapid progression of patients into more severe disease stages and into nursing homes and the differences among population subgroups. In general, male gender, age under 65, and high level of behavioral symptoms were associated with higher transition probabilities to more severe disease stages. Disease progression is roughly constant as a function of the time a patient has spent in a particular stage. CONCLUSIONS: Transition probabilities provide a useful means of characterizing AD progression. Economic models of interventions for AD should consider the varied course of progression for different population subgroups, particularly those defined by high levels of behavioral symptoms.

Neumann PJ, Hammitt JK, Mueller C, Fillit HM, Hill J, Tetteh NA, Kosik KS. · Program on the Economic Evaluation of Medical Technology at the Harvard School of Public Health, Boston, Massachusetts, USA. · Health Aff (Millwood). · Pubmed #11558711 links to  free full text

Abstract: In a general population survey (N = 314), 79 percent of respondents stated that they would take a hypothetical genetic test to predict whether they will eventually develop Alzheimer's disease. The proportion fell to 45 percent for a "partially predictive" test (which had a one in ten chance of being incorrect). Inclination to obtain testing was similar across age groups. Respondents were willing to pay $324 for the completely predictive test. Respondents stated that if they tested positive, they would sign advance directives (84 percent), get their finances in order (74 percent), and purchase long-term care insurance (69 percent). Only a third of respondents expressed concern about confidentiality. The results suggest that people value genetic testingfor personal and financial reasons, but they also underscore the need to counsel potential recipients carefully about the accuracy and implications of test information.

Bell CM, Araki SS, Neumann PJ. · Program on the Economic Evaluation of Medical Technology, Center for Risk Analysis, Harvard School of Public Health, Boston, Massachusetts, USA. · Alzheimer Dis Assoc Disord. · Pubmed #11522930 No free full text.

Abstract: The burden experienced by family caregivers of individuals with Alzheimer disease (AD) affects the caregivers' overall health-related quality of life (HRQOL). Assessing the influence on HRQOL is an integral part of determining the efficacy and economic attractiveness of interventions for AD. Generic preference-weighted instruments such as the Health Utilities Index Mark 2 (HUI2) are recommended for measuring HRQOL for cost-effectiveness studies. However, these instruments focus on physical attributes and have not been tested in an AD caregiver population. We administered the HUI2 to a population of 679 caregivers to people with AD at 13 community and institutional sites in the United States. We also administered the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36), a caregiver time questionnaire, and a caregiver burden instrument. The mean global HUI2 utility score for caregivers was 0.87 and varied little by the affected person's setting of care and AD stage (range, 0.86-0.89; p > 0.2). The caregiver burden scales all varied by the affected person's setting of care, and some also varied by disease severity. The mental health component summary score of the SF-36 for caregivers varied across both disease stage and setting. Caregiver time increased for caregivers of AD-affected persons with more severe cognitive impairment. Generic preference-weighted instruments may not adequately capture differences in the burden of caregivers of those with AD. The development of condition-specific preference-weighted instruments may provide the means to better estimate HRQOL in AD caregivers.

Claxton K, Neumann PJ, Araki S, Weinstein MC. · University of York. · Int J Technol Assess Health Care. · Pubmed #11329844 No free full text.

Abstract: A framework is presented that distinguishes the conceptually separate decisions of which treatment strategy is optimal from the question of whether more information is required to inform this choice in the future. The authors argue that the choice of treatment strategy should be based on expected utility, and the only valid reason to characterize the uncertainty surrounding outcomes of interest is to establish the value of acquiring additional information. A Bayesian decision theoretic approach is demonstrated through a probabilistic analysis of a published policy model of Alzheimer's disease. The expected value of perfect information is estimated for the decision to adopt a new pharmaceutical for the population of patients with Alzheimer's disease in the United States. This provides an upper bound on the value of additional research. The value of information is also estimated for each of the model inputs. This analysis can focus future research by identifying those parameters where more precise estimates would be most valuable and indicating whether an experimental design would be required. We also discuss how this type of analysis can also be used to design experimental research efficiently (identifying optimal sample size and optimal sample allocation) based on the marginal cost and marginal benefit of sample information. Value-of-information analysis can provide a measure of the expected payoff from proposed research, which can be used to set priorities in research and development. It can also inform an efficient regulatory framework for new healthcare technologies: an analysis of the value of information would define when a claim for a new technology should be deemed substantiated and when evidence should be considered competent and reliable when it is not cost-effective to gather any more information.

Neumann PJ, Sandberg EA, Araki SS, Kuntz KM, Feeny D, Weinstein MC. · Program on the Economic Evaluation of Medical Technology, Center for Risk Analysis, Harvard School of Public Health, Boston, Massachusetts 02115, USA. · Med Decis Making. · Pubmed #11059474 No free full text.

Abstract: PURPOSE: The Health Utilities Index (HUI) is a generic, multiattribute, preference-based health-status classification system. The HUI Mark 3 (HUI3) differs from the earlier HUI2 by modifying attributes and allowing more flexibility for capturing high levels of impairment. The authors compared HUI2 and HUI3 scores of patients with Alzheimer's disease (AD) and caregivers, and contrasted results of a cost-effectiveness analysis of new drugs for AD using the two systems. METHODS: In a cross-sectional study of 679 AD patient/caregiver pairs, stratified by patient's disease stage (questionable/mild/moderate/severe/profound/terminal) and setting (community/assisted living/nursing home), caregivers completed the combined HUI2/HUI3 questionnaire as proxy respondents for patients and for themselves. RESULTS: Mean (SD) global utility scores for patients were lower on the HUI3 (0.22[0.26]) than on the HUI2 (0.53 [0.21]). Patient HUI3 utility scores ranged from 0.47(0.24) for questionable AD to -0.23 (0.08) for terminal AD, compared with a range of 0.73 (0.15) to 0.14 (0.07) for the HUI2. Among the 203 patients in the severe, profound, and terminal stages, 96 (48%) had negative global HUI3 utility scores, while none had a negative HUI2 score. The utility scores for caregivers were similar on the HUI3 (0.87 [0.14]) and HUI2 (0.87 [0.11]). Cost-effectiveness analysis of a new medication to treat AD showed somewhat more favorable results using the HUI3. CONCLUSIONS: The HUI2 and HUI3 discriminate well across AD stages. Compared with the HUI2, the HUI3 yields lower global utility scores for patients with AD, and more scores for states judged worse than dead. The HUI3 may yield substantially different results from the HUI2, particularly for persons who have serious cognitive impairments such as AD.

McMahon PM, Araki SS, Neumann PJ, Harris GJ, Gazelle GS. · Department of Radiology, Decision Analysis and Technology Assessment Group, the Computer-Assisted Diagnostics Laboratory, Massachusetts General Hospital, Zero Emerson Pl, Ste 2H, Boston, MA 02114, USA. · Radiology. · Pubmed #11012424 links to  free full text

Abstract: PURPOSE: To evaluate the cost-effectiveness of functional neuroimaging in the work-up of patients at specialized Alzheimer disease clinics. MATERIALS AND METHODS: A decision model was used to calculate costs and benefits (in quality-adjusted life-years [QALYs]) that accrued to hypothetical cohorts of patients at presentation to an Alzheimer disease center. Sensitivity analysis was performed to examine the effects of diagnostic test characteristics, therapeutic efficacy, disease severity, and costs on cost-effectiveness. RESULTS: The incremental cost-effectiveness ratio of dynamic susceptibility contrast material-enhanced magnetic resonance (MR) imaging was $479,500 per QALY (compared with the usual diagnostic work-up), while visual or quantitative single photon emission computed tomography (SPECT) was dominated (higher costs, lower effectiveness) by the usual diagnostic work-up. These results depend critically on the sensitivity and specificity of the standard diagnostic work-up, the effectiveness of drug treatment, and the disease severity. Varying these parameters resulted in estimates of incremental cost-effectiveness for dynamic susceptibility contrast-enhanced MR imaging of $24,680 to $8.6 million per QALY. SPECT either was dominated by the usual diagnostic work-up or had cost-effectiveness ratios of $180,200 to $6 million per QALY. CONCLUSION: The addition of functional neuroimaging to the usual diagnostic regimen at Alzheimer disease clinics is not cost-effective given the effectiveness of currently available therapies.

Leon J, Neumann PJ. · Project Hope, Center for Health Affairs, Bethesda, MD 20814-6133, USA. · Am J Manag Care. · Pubmed #10557408 links to  free full text

Abstract: BACKGROUND: The number of people with Alzheimer's disease (AD) is expected to grow as the US population ages. Given the increasing enrollment in managed care organizations, growth in the number of managed care patients with AD is a certainty. To our knowledge, no study to date has focused on the cost of care of community-dwelling AD patients receiving care through a health maintenance organization (HMO) system. METHODS: One hundred and fifty patients were recruited from 4 managed care sites from July through December 1996. Staff at each site clinically confirmed patients' AD diagnosis, AD severity, and ascertained patients' comorbidities. Demographic, quality of life, and service utilization data were collected from proxy respondents. Costs of hospitalization, medications, doctor visits (formal costs), and caregiver assistance (informal costs) were analyzed separately. RESULTS: The average total (formal and informal) per-patient costs in the 4 settings in 1996 were $18,804. Costs increased with cognitive impairment. For patients with mild, moderate, and severe AD, annual total costs were $14,904, $19,272, and $25,860, respectively. Annual direct costs were $5520, $7044 and $10,992, respectively. CONCLUSION: Across all severity levels, we calculated a total annual cost of $8.8 billion for managed care enrollees older than 65 years in the United States. We did not estimate these costs for the population younger than 65 years because of the variability in AD prevalence estimates. Due to the increased costs for patients with more severe AD, interventions that would reverse or delay progression may result in significant cost savings.

Neumann PJ, Kuntz KM, Leon J, Araki SS, Hermann RC, Hsu MA, Weinstein MC. · Program on the Economic Evaluation of Medical Technology, Center for Risk Analysis, Harvard School of Public Health, Boston, MA 02115, USA. · Med Care. · Pubmed #10413389 No free full text.

Abstract: OBJECTIVES: Although the broad impacts of Alzheimer's disease (AD) are increasingly recognized, little work has focused on the overall health-related quality of life experienced by Alzheimer's disease patients and their caregivers. The study had two main objectives: (1) to test the feasibility of measuring health utilities in Alzheimer's disease with a generic preference-weighted instrument using proxy respondents and (2) to assess the utility scores of Alzheimer's disease patients (and their caregivers) in different disease stages and care setting. METHODS: A cross-sectional study of 679 Alzheimer's disease patient/caregiver pairs was conducted at 13 sites in the United States: four academic medical centers, four managed care plans, two assisted living facilities, and three nursing homes. The Health Utilities Index Mark II (HUI:2) questionnaire was administered to caregivers of patients who responded both as proxies for patients and for themselves. Responses to the questionnaire were converted into a global utility score, between 0 and 1, using the HUI:2 multi-attribute utility function. RESULTS: Global utility scores varied considerably across patients' Alzheimer's disease stage: for the six stages assessed (questionable, mild, moderate, severe, profound, and terminal), mean utility scores were 0.73, 0.69, 0.53, 0.38, 0.27, and 0.14, respectively. In multiple regression analyses, Alzheimer's disease stage was a negative and significant predictor of utility scores for patients; setting did not exert an independent effect. Utility scores for the caregivers were insensitive to patients' Alzheimer's disease stage and setting. CONCLUSIONS: Patients' Alzheimer's disease stage had a substantial influence on health utilities, as measured by the HUI:2. More research is needed to assess the validity of using proxy respondents.

Neumann PJ, Hermann RC, Kuntz KM, Araki SS, Duff SB, Leon J, Berenbaum PA, Goldman PA, Williams LW, Weinstein MC. · Program on the Economic Evaluation of Medical Technology, Center for Risk Analysis, Harvard School of Public Health, Boston, MA 02115, USA. · Neurology. · Pubmed #10214734 No free full text.

Abstract: OBJECTIVE: To demonstrate the use of cost-effectiveness analysis to assess the economic impact of donepezil in the treatment of mild or moderate AD. BACKGROUND: Cost-effectiveness analyses show the relationship between resources used (costs) and health benefits achieved (effects) for an intervention compared with an alternative strategy. METHODS: We developed a model to estimate the incremental cost-effectiveness of donepezil compared with no treatment. We determined costs per quality-adjusted life-years gained, a measurement that enhances the comparability of diverse studies. The model projects the progression of AD patients into more severe disease stages and into nursing homes. Data from a randomized clinical trial of donepezil were used to assess the drug's impact on the 6-week probabilities of progression. Data on the costs and health-related quality of life associated with different disease stages and settings were taken from published estimates and our companion cross-sectional study, respectively. RESULTS: Donepezil costs are partially offset by a reduction in the costs of care due to enhancement in cognitive functioning and the delay to more costly disease stages and settings. The magnitude of this cost offset and of the effect of donepezil on health-related quality of life depends on the model's assumptions about the duration of the drug effect, where controlled data are lacking. If the drug effect exceeds 2 years, the model predicts that for mild AD the drug would pay for itself in terms of cost offsets. CONCLUSIONS: The results of the cost-effectiveness model presented here suggest that donepezil may be cost-effective but additional controlled data on long-term drug efficacy are needed.

Neumann PJ. · No affiliation provided · Pharmacoeconomics. · Pubmed #10747762 No free full text.

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