Biomarker tests for the diagnosis of Alzheimer's disease: Generating evidence to inform insurance coverage determinations

Out-of-Pocket Expenses for Long-Term Care by Dementia Status and Residential Setting among US Older Adults

OBJECTIVE

To examine long-term care out-of-pocket payments by dementia status and residential setting.

DESIGN

Compare monthly out-of-pocket long-term care expenses paid to facilities and helpers, total monthly out-of-pocket long-term expenses and as a percentage of monthly income by dementia status and residential status (community, residential facility, and nursing home).

SETTING AND PARTICIPANTS

US Nationwide, 2019 National Health and Aging Trends Study (NHATS) respondents aged ≥70 years.

METHODS

We analyzed respondent-level data from the nationally representative 2019 NHATS. Weighted descriptive statistics were calculated for long-term care payments by source and summarized by dementia status and the respondent's residential status.

RESULTS

Among 4505 respondents aged ≥70 years, 1750 (38.8%) had possible or probable dementia and 2755 (61.2%) had no dementia. The median monthly out-of-pocket long-term care expenses for persons with dementia was $1465 for those living in nursing homes, and $2925 for those living in other residential facilities, much higher than those with dementia living in the community ($260). Although these are similar to the median out-of-pocket payments for persons without dementia by setting, those with dementia were at greater risk of facing catastrophic out-of-pocket expenses for long-term care than those without dementia, with the 75th percentile value of out-of-pocket payment at $4566 among dementia adults living in non-nursing home residential care facilities, and $7500 for those in nursing homes, compared to $3694 and $3100 among those without dementia. At median, these expenses accounted for 100% of monthly income of respondents with dementia living in facilities.

CONCLUSIONS AND IMPLICATIONS

Persons with dementia living in facilities often face substantial financial burdens from high out-of-pocket long-term care expenses. Policies that provide sufficient financial assistance are needed to address long-term care-related financial burdens experienced by older adults and their families, especially for those with dementia.

Raman spectroscopy and machine learning for biomedical applications: Alzheimer's disease diagnosis based on the analysis of cerebrospinal fluid

Current Alzheimer's disease (AD) diagnostics is based on clinical assessments, imaging and neuropsychological tests that are efficient only at advanced stages of the disease. Early diagnosis of AD will provide decisive opportunities for preventive treatment and development of disease-modifying drugs. Cerebrospinal fluid (CSF) is in direct contact with the human brain, where the deadly pathological process of the disease occurs. As such, the CSF biochemical composition reflects specific changes associated with the disease and is therefore the most promising body fluid for AD diagnostic test development. Here, we describe a new method to diagnose AD based on CSF via near infrared (NIR) Raman spectroscopy in combination with machine learning analysis. Raman spectroscopy is capable of probing the entire biochemical composition of a biological fluid at once. It has great potential to detect small changes specific to AD, even at the earliest stages of pathogenesis. NIR Raman spectra were measured of CSF samples acquired from 21 patients diagnosed with AD and 16 healthy control (HC) subjects. Artificial neural networks (ANN) and support vector machine discriminant analysis (SVM-DA) statistical methods were used for differentiation purposes, with the most successful results allowing for the differentiation of AD and HC subjects with 84% sensitivity and specificity. Our classification models show high discriminative power, suggesting the method has a great potential for AD diagnostics. The reported Raman spectroscopic examination of CSF can complement current clinical tests, making early AD detection fast, accurate, and inexpensive. While this study shows promise using a small sample set, further method validation on a larger scale is required to indicate the true strength of the approach.

Biomarkers: Delivering on the expectation of molecularly driven, quantitative health

Biomarkers are the pillars of precision medicine and are delivering on expectations of molecular, quantitative health. These features have made clinical decisions more precise and personalized, but require a high bar for validation. Biomarkers have improved health outcomes in a few areas such as cancer, pharmacogenetics, and safety. Burgeoning big data research infrastructure, the internet of things, and increased patient participation will accelerate discovery in the many areas that have not yet realized the full potential of biomarkers for precision health. Here we review themes of biomarker discovery, current implementations of biomarkers for precision health, and future opportunities and challenges for biomarker discovery. Impact statement Precision medicine evolved because of the understanding that human disease is molecularly driven and is highly variable across patients. This understanding has made biomarkers, a diverse class of biological measurements, more relevant for disease diagnosis, monitoring, and selection of treatment strategy. Biomarkers' impact on precision medicine can be seen in cancer, pharmacogenomics, and safety. The successes in these cases suggest many more applications for biomarkers and a greater impact for precision medicine across the spectrum of human disease. The authors assess the status of biomarker-guided medical practice by analyzing themes for biomarker discovery, reviewing the impact of these markers in the clinic, and highlight future and ongoing challenges for biomarker discovery. This work is timely and relevant, as the molecular, quantitative approach of precision medicine is spreading to many disease indications.

Ethical issues in neurogenetics

Many neurogenetic conditions are inherited and therefore diagnosis of a patient will have implications for the patient's relatives and can raise ethical issues. Predictive genetic testing offers asymptomatic relatives the opportunity to determine their risk status for a neurogenetic condition, and professional guidelines emphasize patients' autonomy and informed, voluntary decision making. Beneficence and nonmaleficence both need to be considered when making decisions about disclosure and nondisclosure of genetic information and test results. There can be disclosure concerns and challenges in determining whose autonomy to prioritize when a patient makes a genetic testing decision that can reveal the genetic status of a relative (e.g., testing an adult child when the at-risk parent has not been tested). Ethical issues are prominent when genetic testing for neurogenetic conditions is requested prenatally, on minors, adoptees, adult children at 25% risk, and for individuals with psychiatric issues or cognitive impairment. Neurogenetic conditions can result in cognitive decline which can affect decisional capacity and lead to ethical challenges with decision making, informed consent, and determining the patient's ability to comprehend test results. The ethical implications of genetic testing and emerging issues, including direct-to-consumer genetic testing, disclosure of secondary findings from genomic sequencing, and use of apolipoprotein E testing in clinical and research settings, are also discussed. Resources for information about genetic testing practice guidelines, insurance laws, and directories of genetics clinics are included.

CSF Biomarkers of Alzheimer’s Disease: Impact on Disease Concept, Diagnosis, and Clinical Trial Design

Data from clinicopathologic and biomarker studies have converged to support the view of Alzheimer’s disease (AD) as a continuum, with pathology developing decades prior to the onset of cognitive symptoms which culminate as dementia at the end stage of the disease. This concept is impacting disease nomenclature, diagnostic criteria, prognostic potential, and clinical trial design. Revisions to diagnostic criteria to incorporate biomarker results have recently been proposed in order to increase the confidence of AD as the underlying etiology of a clinical impairment and to permit a diagnosis of AD across the disease continuum, eventually perhaps in the asymptomatic period. Individuals in this preclinical stage are receiving intense focus as a targeted population for secondary prevention trials aimed at identifying disease-modifying therapies that have the best chance of preserving normal cognitive function. The goal is to bring validated biomarkers to clinical practice for the purpose of disease diagnosis, prognosis, and evaluation of therapeutic efficacy once disease-modifying treatments become available. Realization of this goal requires worldwide biomarker standardization efforts, consensus among researchers and clinicians regarding the clinical utility of assessing biomarkers in patient care settings, and eventually the endorsement and adoption of such procedures and practices into global health care systems.

Biomarker tests for the diagnosis of Alzheimer's disease: Generating evidence to inform insurance coverage determinations

Outside of their uses in drug development and clinical research trials, the current clinical value of performing any type of formal biomarker testing for the diagnosis or exclusion of Alzheimer's disease (AD) is controversial, and most biomarker tests for AD are not covered by public or private insurers. This situation raises the issue of how insurers determine whether there is "adequate" evidence to justify a positive coverage determination in this area. This article, a focused condensation of a larger white paper, is the product of an initiative led by the Institute for Clinical and Economic Review to convene a multiple-stakeholder AD Diagnostics Policy Development Group composed of patient advocates, clinicians, clinical researchers, manufacturers, and insurers. The larger white paper was the basis for the evidence review presented to the Medicare Evidence Development and Coverage Advisory Committee meeting on January 30, 2013, as part of its deliberations on positron emission tomography-amyloid imaging. Herein we focus on the description of the core elements of what insurers will be looking for in evidence on all potential diagnostic tests for AD. Corresponding research recommendations are also included, framed to serve as a guide for future AD diagnostics research.