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. 2023 Apr;19(4):1175-1183.
doi: 10.1002/alz.12754. Epub 2022 Aug 7.

Using Alzheimer's disease blood tests to accelerate clinical trial enrollment

Suzanne E Schindler  1   2 , Yan Li  1   2 , Melody Li  1 , Alyssa Despotis  3 , Ethan Park  1 , Liberty Vittert  3 , Barton H Hamilton  3 , Kyle B Womack  1   2 , Benjamin Saef  1 , David M Holtzman  1   2   4 , John C Morris  1   2 , Randall J Bateman  1   2   4 , Mahendra R Gupta  3
Affiliations

Using Alzheimer's disease blood tests to accelerate clinical trial enrollment

Suzanne E Schindler et al. Alzheimers Dement. 2023 Apr.

Abstract

Introduction: Screening potential participants in Alzheimer's disease (AD) clinical trials with amyloid positron emission tomography (PET) is often time consuming and expensive.

Methods: A web-based application was developed to model the time and financial cost of screening for AD clinical trials. Four screening approaches were compared; three approaches included an AD blood test at different stages of the screening process.

Results: The traditional screening approach using only amyloid PET was the most time consuming and expensive. Incorporating an AD blood test at any point in the screening process decreased both the time and financial cost of trial enrollment. Improvements in AD blood test accuracy over currently available tests only marginally increased savings. Use of a high specificity cut-off may improve the feasibility of screening with only an AD blood test.

Discussion: Incorporating AD blood tests into screening for AD clinical trials may reduce the time and financial cost of enrollment.

Highlights: The time and cost of enrolling participants in Alzheimer's disease (AD) clinical trials were modeled. A web-based application was developed to enable evaluation of key parameters. AD blood tests may decrease the time and financial cost of clinical trial enrollment. Improvements in AD blood test accuracy only marginally increased savings. Use of a high specificity cut-off may enable screening with only an AD blood test.

Keywords: Shiny app; amyloid positron emission tomography; blood tests; blood-based biomarkers; clinical trials; cost; economics; false negative; false positive; modeling; screening; screening approaches; time of enrollment.

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Conflict of interest statement

SES has analyzed data provided by C2N Diagnostics to Washington University, but she has not received any research funding or personal compensation from C2N Diagnostics or any other for-profit organizations. C2N Diagnostics had no role in this study, interpretation, or manuscript. YL, ML, AD, EP, LV, BHH, KW, BS, and MG report no disclosures. RJB and DMH co-founded C2N Diagnostics, which offers the PrecivityAD™ blood test. Washington University, RJB, and DMH have equity ownership interest in C2N Diagnostics and receive royalty income based on technology (stable isotope labeling kinetics and blood plasma assay) licensed by Washington University to C2N Diagnostics. RJB and DMH receive income from C2N Diagnostics for serving on the scientific advisory board. RJB has received honoraria as a speaker, consultant, or advisory board member from Amgen and Roche. DMH is on the scientific advisory board of Denali, Genentech, and Cajal Neuroscience and consults for Alector. Neither Dr. Morris nor his family owns stock or has equity interest (outside of mutual funds or other externally directed accounts) in any pharmaceutical or biotechnology company.

Figures

Figure 1.
Figure 1.. Estimated time and financial cost of four different screening approaches (A-D).
The time and financial cost of enrolling 100 amyloid PET positive participants who meet study criteria was estimated for each approach. Estimates are presented for an AD blood test with an 85% sensitivity and 80% specificity for brain amyloidosis. The number and type of individuals at the end of each step is shown (+MC: amyloid PET positive, meets study criteria; +DC: amyloid PET positive, does not meet study criteria; −MC: amyloid PET negative, meets study criteria; −DC: amyloid PET negative, does not meet study criteria.)
Figure 2.
Figure 2.. Effects of modifying a single parameter on the time and financial cost of enrollment.
The time (A-C) or financial cost (D-F) of enrolling 100 amyloid PET positive participants who meet study criteria was estimated for each approach as one key parameter was varied. The dashed vertical line represents the estimated value for AD clinical trials at Washington University. The cost of the AD blood test did not affect approach A, which does not include an AD blood test, and the cost of an amyloid PET scan did not affect approach D, which does not include an amyloid PET scan.
Figure 3.
Figure 3.. Reducing the time of enrollment for approach D.
The estimated time of enrollment for approach D as a function of initial calls per day and screening visits per day.
Figure 4.
Figure 4.. Time and cost of enrollment by AD blood test accuracy.
The time and financial cost of enrollment for each approach were examined as a function of the sensitivity and specificity of the AD blood test for brain amyloidosis.
Figure 5.
Figure 5.. False positive participants enrolled via approach D.
The number and proportion of individuals enrolled via approach D with a positive AD blood test who would be expected to have a negative amyloid PET scan (“false positives”) as a function of the specificity of the AD blood test for brain amyloidosis, stratified by the sensitivity (A). The number and percent of false positives as a function of the sensitivity stratified by the specificity (B). The number of individuals who must be called to yield 100 amyloid PET positive individuals who meet study criteria as a function of the AD blood test sensitivity (C), assuming that 75% of individuals called are eligible for the study.
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