Introduction: Blood-based biomarkers (BBBMs), including plasma amyloid beta (Aβ) or phosphorylated tau (p-tau), combined with apolipoprotein E () testing, are anticipated to serve as prescreening tools before amyloid positron emission tomography (PET) for recruiting participants for Alzheimer's disease (AD) prevention studies. The predictive efficacy and cost-effectiveness of prescreening may vary with different testing combinations, sequences, and cutoff levels.
Methods: We conducted a simulation study utilizing data from our ongoing Japanese Trial-Ready Cohort (J-TRC) onsite study ( = 202) recruited online. We included cognitively unimpaired individuals who had undergone amyloid PET, genotyping, and evaluation of BBBMs (i.e., plasma Aβ42/Aβ40 ratio, plasma p-tau217, and plasma p-tau217/Aβ42 ratio). We examined 14 different prescreening models incorporating genotype and/or BBBMs with varied combinations and cutoff levels. Models were evaluated for predictive performance (sensitivity, specificity, and positive predictive value [PPV]) and cost-effectiveness (cost per identified amyloid-positive case) across varied testing costs and the prevalence of amyloid positivity.
Results: Applying BBBM prescreening significantly decreased sensitivity and increased specificity and PPV compared to the no-prescreening scenario. Although no single model was superior in all performance metrics, a trade-off between sensitivity and specificity was observed. Generalized linear models (GLMs) simultaneously incorporating plasma Aβ42/Aβ40 ratio and p-tau217 showed a balanced efficacy (the best level of improvement in number needed to screen (NNS) but modest worsening in sensitivity) and the best level of cost-effectiveness compared to other models, although there were substantial overlaps in their 95% confidence intervals (CIs). The minimum-required PET/BBBM cost ratio to achieve improved cost-effectiveness by employing the prescreening process was negatively associated with the background prevalence of amyloid positivity.
Discussion: The choice of prescreening strategy in AD prevention studies/trials should be tailored to specific trial requirements, considering the relative importance of sensitivity versus cost-effectiveness, local testing cost environments, and background population characteristics.
Highlights: We investigated different models of blood-based biomarker (BBBM) prescreening.Data from Japanese Trial-Ready Cohort Study were used for simulation.BBBM reduced the number needed to screen with positron emission tomography (PET) but decreased the sensitivity.The cost-effectiveness improved with a higher PET/BBBM cost ratio.No single model was optimal for all scenarios.
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http://dx.doi.org/10.1002/trc2.70065 | DOI Listing |
Introduction: Blood-based biomarkers (BBBMs), including plasma amyloid beta (Aβ) or phosphorylated tau (p-tau), combined with apolipoprotein E () testing, are anticipated to serve as prescreening tools before amyloid positron emission tomography (PET) for recruiting participants for Alzheimer's disease (AD) prevention studies. The predictive efficacy and cost-effectiveness of prescreening may vary with different testing combinations, sequences, and cutoff levels.
Methods: We conducted a simulation study utilizing data from our ongoing Japanese Trial-Ready Cohort (J-TRC) onsite study ( = 202) recruited online.
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Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston Salem, North Carolina, USA.
The Alzheimer's Disease in Older Adults with Chronic Conditions (ADACC) Network is funded by the National Institute on Aging as a U24 cooperative agreement. ADACC is an inclusive, multidisciplinary group across multiple institutions that is charged with the task of developing evidence-based strategies for the use and implementation of Alzheimer's disease and related dementias (AD/ADRD) biomarkers among older adults with cognitive impairment and multiple chronic conditions (MCCs). This report summarizes highlights of the First Annual Symposium of ADACC, which was held in Winston-Salem, North Carolina, in April 2024.
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