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July 16, 2021

Developing an Economic and Policy Research Agenda for Blood Biomarkers of Neurodegenerative Diseases

Author Affiliations
  • 1The Memory and Aging Center, Department of Neurology, University of California, San Francisco
  • 2Center for Translational and Policy Research on Personalized Medicine, Department of Clinical Pharmacy, University of California, San Francisco
  • 3Penn Memory Center, Perelman School of Medicine, University of Pennsylvania
JAMA Health Forum. 2021;2(7):e211428. doi:10.1001/jamahealthforum.2021.1428

In the past 2 decades, researchers have discovered biomarkers for the pathologic causes of neurodegeneration, such as β-amyloid (Aβ) and tau associated with Alzheimer disease and dopamine identified through DaTscan imaging to confirm Parkinson disease. These tests have reconceptualized the definitions of neurodegenerative diseases. As a result, biomarkers are changing how clinicians diagnose these diseases and may soon change how these diseases are treated. Biomarker tests offer exciting new possibilities to improve diagnostic accuracy, assess risk in asymptomatic individuals, and discover disease-modifying therapies. For example, they have been essential to the discovery of aducanumab, the first disease-modifying therapy for Alzheimer disease recently approved by the US Food and Drug Administration. This controversial approval and the post-approval criticism have emphasized the importance of biomarker tests to therapy discovery and the critical need for economic and policy evaluations.

Two notable challenges to the translation of biomarkers into clinical practice have been their high cost and reliance on invasive techniques, including radiotracer imaging and cerebrospinal fluid analyses.1 These were among the reasons Medicare declined to cover Aβ positron emission tomography imaging for Alzheimer disease in 2013.1,2 Recent progress in validating blood-based biomarkers may overcome these challenges.

Blood-based biomarkers shift the economic and policy paradigm. Unlike cerebrospinal fluid analysis or imaging, these biomarkers do not require invasive techniques or costly equipment. They could facilitate population-level screening for those at the highest risk of developing symptomatic disease and even generate a direct-to-consumer market for testing.3 As they become increasingly available to patients, blood-based biomarkers will transform clinical care.

This scientific progress, however, raises notable economic and policy challenges. Assumptions that drive economic models and policies in neurodegenerative diseases must be revisited. Current models assume that long-term care needs are the primary drivers of costs for Alzheimer disease and related dementias, which are ranked among the most expensive chronic conditions in the US. Clinical adoption of biomarkers will alter these assumptions by introducing novel cost drivers associated with tests, treatments, monitoring, and care alongside a potentially beneficial but costly extension of the disease course of dementias.4

Therefore, an economic and policy research agenda is essential to evaluating critical questions about the value of blood tests for biomarkers, with attention to payer coverage, costs, and health care disparities in accessing novel risk assessments, diagnostic tests, and therapies. Maximizing the value of disease-modifying therapies for neurodegenerative diseases will require intervening early and identifying the right subpopulations. Blood tests for biomarkers offer accessible options to identify individuals most likely to benefit from therapies—driving the expectation of a high demand for testing.5

Evidence of this demand can be found in ongoing clinical trials that increasingly use biomarkers as eligibility criteria. Positivity for Aβ—measured through cerebrospinal fluid, imaging, and most recently, blood-based biomarkers—has been an eligibility criterion of multiple secondary-prevention trials. Similarly, emerging clinical trials in amyotrophic lateral sclerosis are integrating biomarker neurofilament light chain tests alongside genetic testing for SOD1 as eligibility criteria.6 The potential clinical costs and payer coverage for testing, if implemented at larger scales, are currently unknown. PrecivityAD (C2N Diagnostics), a blood test to measure Aβ for Alzheimer disease, is commercially available for $1250. However, it is unclear whether this pricing will change in the future, particularly if other companies develop similar tests. The potential expenditures and risks of testing and treating a large population of individuals, particularly if offered prior to symptom onset, could be substantial.

The impending demand heightens the need for early evaluation of economic and policy issues, especially considering the costs and risks of testing and disease-modifying therapies, specifically the cost and effectiveness of biomarker testing.2 The paucity of economic analyses of neurodegenerative diseases contrasts with that of cancer, which has experienced a similar reconceptualization of disease and for which there has been far more economic analyses examining blood-based biomarker use.7 Economic analyses of blood tests for biomarkers of neurodegenerative diseases must receive similar attention given their future clinical importance. A delay in resolving challenges related to economic value, payer coverage, and disparities will adversely affect the clinical adoption of these biomarkers. We propose the following 4 approaches to inform a research and policy agenda.

Identify Evidence for Economic Analyses and Payer Coverage Decisions

As blood tests for biomarkers become part of standard care, payers will require proactive approaches to develop evidence to support coverage decisions. Equitable adoption of biomarkers will require evidence of the benefits and consequences of improved diagnostic accuracy and early detection of disease pathology. There have been 2 recent steps forward. First, in May 2021, the Institute for Clinical and Economic Review published a draft report evaluating the economic and health outcomes of aducanumab for the treatment of Alzheimer disease.8 The report determined that the evidence was insufficient to find a net health benefit of aducanumab. Given its “risk of side effects and the uncertainty of benefit," aducanumab’s pricing ($56,000 per year) also received criticism. Second, Mattke and colleagues9 estimated that testing in a primary care setting could reduce wait time for specialists and reduce costs. However, these studies do not fully address the paucity of research on biomarkers to provide evidence for insurers’ decision-making and value assessments.2 Evidence will be particularly important to address variation among payers’ coverage approaches and rationales.10 Identifying the evidence needed to support policy and economic evaluations is critical to avoid delaying these efforts until new interventions become realistic clinical options.

Develop a Neurodegenerative Disease Taxonomy to Guide Policy

There is a critical need to examine economic and policy issues across neurodegenerative diseases to ensure fairness and equity in coverage. Each neurodegenerative disease is distinct in its clinical presentation and underlying pathology, but these diseases often share similar features, including progressive disability. For example, frontotemporal lobar degeneration and amyotrophic lateral sclerosis share at least 1 genetic marker and overlap in disease progression. Yet, the field lacks a widely accepted taxonomy that captures clinical features (ie, age of onset, length of disease) and causes of pathology. Such a taxonomy can promote consistency across policy-related decisions and support for neurodegenerative diseases.

Evaluate the Consequences of the Direct-to-Consumer Market

Research is needed to evaluate the economic consequences of blood-based biomarker tests in the direct-to-consumer market. To our knowledge, there are currently at least 2 companies that offer direct-to-consumer testing for ApoE, genetic risk factors for Parkinson disease, and carrier status for genetic markers of autosomal recessive spastic ataxia of Charlevoix-Saguenay and Canavan diseases. This testing sets the stage for a relatively affordable direct-to-consumer market for blood-based biomarkers, which would have ripple effects on individual decision-making and alter economic models that assume individuals will receive testing through clinical settings.3

Assess the Influence on Disparities

Blood-based biomarkers of neurodegenerative diseases are a novel opportunity to close a gap regarding clinical implementation models that could mitigate existing health care disparities. Yet, it is unclear whether they could also exacerbate existing disparities. Historically, biomarker testing has been restricted to specialty clinics. The accessibility of blood-based biomarkers may mitigate disparities in access to neurodegenerative disease care experienced by individuals from disadvantaged groups and communities that are disproportionately affected by neurodegenerative diseases. However, the lack of data validating biomarkers in these groups, given their underrepresentation in longitudinal and clinical studies, may hinder adoption. This disparity may be further exacerbated if payer coverage of tests and the related treatments is inequitable or if access to a specialist is required to obtain testing.


Questions about economic value, payer coverage, and disparities will challenge the adoption of blood tests for biomarkers into clinical practice. The answers to these questions will affect access to diagnostic tests, predictive screening, and treatment. We must not wait until blood-based biomarkers are clinically available to consider whether they have economic value or how coverage decisions might vary among diseases. There is a critical opportunity now to consider these questions to ensure efficient and equitable clinical adoption of biomarkers for neurodegenerative diseases.

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Article Information

Published: July 16, 2021. doi:10.1001/jamahealthforum.2021.1428

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Arias JJ et al. JAMA Health Forum.

Corresponding Author: Jalayne J. Arias, JD, The Memory and Aging Center, Department of Neurology, University of California, 675 Nelson Rising Lane, Ste 190, San Francisco, CA 94158 (jalayne.arias@ucsf.edu).

Author Contributions: Prof Arias and Dr Phillips contributed equally to this work.

Conflict of Interest Disclosures: Prof Arias reports an award from the National Institute on Aging of the National Institutes of Health (NIH; K01AG057796) during the conduct of this work. Dr Phillips reports consulting income from Illumina and honorarium from participation on evidence review panels for the Institute for Clinical and Economic Review, outside the submitted work. Dr Karlawish reports income from Eli Lilly for funding of the A4 Clinical trial, outside the submitted work.

Funding/Support: This work was funded by grants from the National Cancer Institute of the NIH (R01 CA221870, R01 CA221870-S1) and by the National Institute on Aging of the NIH (U54AG063546), which funds the Imbedded Pragmatic Alzheimer’s Disease and AD-Related Dementias Clinical Trials Collaboratory (NIA IMPACT Collaboratory).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Additional Contributions: Michael P. Douglas, MS, Center for Translational and Policy Research on Personalized Medicine, and Ana M. Tyler, JD, The Memory and Aging Center, both of the University of California San Francisco, contributed research support and editorial reviews of the manuscript. They were not compensated for their work.

Karlawish  J.  The problem of Alzheimer’s. St Martin's Press; 2021.
Pearson  SD, Ollendorf  DA, Colby  JA; ICER Alzheimer’s Diagnostics Policy Development Group.  Biomarker tests for the diagnosis of Alzheimer’s disease: generating evidence to inform insurance coverage determinations.   Alzheimers Dement. 2013;9(6):745-752. doi:10.1016/j.jalz.2013.06.002 PubMedGoogle ScholarCrossref
Largent  EA, Wexler  A, Karlawish  J.  The future is p-tau: anticipating direct-to-consumer Alzheimer disease blood tests.   JAMA Neurol. 2021;78(4):379-380. doi:10.1001/jamaneurol.2020.4835 PubMedGoogle ScholarCrossref
Wimo  A, Reed  CC, Dodel  R,  et al.  The GERAS study: a prospective observational study of costs and resource use in community dwellers with Alzheimer’s disease in three European countries: study design and baseline findings.   J Alzheimers Dis. 2013;36(2):385-399. doi:10.3233/JAD-122392 PubMedGoogle ScholarCrossref
Kopits  IM, Chen  C, Roberts  JS, Uhlmann  W, Green  RC.  Willingness to pay for genetic testing for Alzheimer’s disease: a measure of personal utility.   Genet Test Mol Biomarkers. 2011;15(12):871-875. doi:10.1089/gtmb.2011.0028 PubMedGoogle ScholarCrossref
Benatar  M, Wuu  J, Andersen  PM, Lombardi  V, Malaspina  A.  Neurofilament light: a candidate biomarker of presymptomatic amyotrophic lateral sclerosis and phenoconversion.   Ann Neurol. 2018;84(1):130-139. doi:10.1002/ana.25276 PubMedGoogle ScholarCrossref
Guzauskas  GF, Garbett  S, Zhou  Z,  et al.  Cost-effectiveness of population-wide genomic screening for hereditary breast and ovarian cancer in the United States.   JAMA Netw Open. 2020;3(10):e2022874. doi:10.1001/jamanetworkopen.2020.22874 PubMedGoogle Scholar
Institute for Clinical and Economic Review. Aducanumab for Alzheimer’s disease: effectiveness and value. Draft evidence report, May 5, 2021. Accessed June 15, 2021. https://icer.org/wp-content/uploads/2020/10/ICER_ALZ_Draft_Evidence_Report_050521.pdf
Mattke  S, Cho  SK, Bittner  T, Hlávka  J, Hanson  M.  Blood-based biomarkers for Alzheimer’s pathology and the diagnostic process for a disease-modifying treatment: projecting the impact on the cost and wait times.   Alzheimers Dement (Amst). 2020;12(1):e12081. doi:10.1002/dad2.12081PubMedGoogle Scholar
Arias  JJ, Tyler  AM, Douglas  MP, Phillips  KA.  Private payer coverage policies for ApoE-e4 genetic testing.   Genet Med. 2021;23(4):614-620. doi:10.1038/s41436-020-01042-4 PubMedGoogle ScholarCrossref
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