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. 2024 Sep;20(9):6506-6516.
doi: 10.1002/alz.14140. Epub 2024 Jul 19.

Optimizing cutpoints for clinical interpretation of brain amyloid status using plasma p-tau217 immunoassays

Daniel J Figdore  1 , Michael Griswold  2 , Joshua A Bornhorst  1 , Jonathan Graff-Radford  3 , Vijay K Ramanan  3 , Prashanthi Vemuri  4 , Val J Lowe  4 , David S Knopman  3 , Clifford R Jack Jr  4 , Ronald C Petersen  3 , Alicia Algeciras-Schimnich  1
Affiliations

Optimizing cutpoints for clinical interpretation of brain amyloid status using plasma p-tau217 immunoassays

Daniel J Figdore et al. Alzheimers Dement. 2024 Sep.

Abstract

Introduction: We aimed to evaluate clinical interpretation cutpoints for two plasma phosphorylated tau (p-tau)217 assays (ALZpath and Lumipulse) as predictors of amyloid status for implementation in clinical practice.

Methods: Clinical performance of plasma p-tau217 against amyloid positron emission tomography status was evaluated in participants with mild cognitive impairment or mild dementia (n = 427).

Results: Using a one-cutpoint approach (negative/positive), neither assay achieved ≥ 90% in both sensitivity and specificity. A two-cutpoint approach yielding 92% sensitivity and 96% specificity provided the desired balance of false positives and false negatives, while categorizing 20% and 39% of results as indeterminate for the Lumipulse and ALZpath assays, respectively.

Discussion: This study provides a systematic framework for selection of assay-specific cutpoints for clinical use of plasma p-tau217 for determination of amyloid status. Our findings suggest that a two-cutpoint approach may have advantages in optimizing diagnostic accuracy while minimizing potential harm from false positive results.

Highlights: Phosphorylated tau (p-tau)217 cutpoints for detection of amyloid pathology were established. A two-cutpoint approach exhibited the best performance for clinical laboratory use. p-tau217 assays differed in the percentage of results categorized as intermediate.

Keywords: Alzheimer's disease; Fujirebio Lumipulse; Simoa ALZpath; amyloid pathology; amyloid positron emission tomography; blood‐based biomarkers; cutpoints; immunoassays; plasma phosphorylated tau217.

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Conflict of interest statement

A. Algeciras‐Schimnich has participated on advisory boards for Roche Diagnostics, Fujirebio Diagnostics, and Siemens Healthineers. J. A. Bornhorst has participated on an advisory board for Sunbird Bio and received an honorarium from Roche Diagnostics. D. J. Figdore reports no disclosures. J. Graff‐Radford receives funding from the NIH. He serves on DSMB for STROKENet and serves as site investigator for Alzheimer's Clinical Trial Consortium studies co‐sponsored by Cognition Therapeutics and Eisai. M. Griswold reports no disclosures. C. R. Jack receives funding from the NIH and the Alexander Family Alzheimer's Disease Research Professorship of the Mayo Clinic. D. S. Knopman serves on a Data Safety Monitoring Board for the Dominantly Inherited Alzheimer Network Treatment Unit study. He was an investigator in Alzheimer's disease clinical trials sponsored by Biogen, Lilly Pharmaceuticals, and the University of Southern California, both of which have ended, and is currently an investigator in a trial in frontotemporal degeneration with Alector. He has served as a consultant for Roche, AriBio, Linus Health, Biovie, and Alzeca Biosciences but receives no personal compensation. He receives funding from the NIH. V. J. Lowe consults for Bayer Schering Pharma, Piramal Life Sciences, Eisai, Inc., AVID Radiopharmaceuticals, Eli Lilly and Company, PeerView Institute for Medical Education, and Merck Research, and receives research support from GE Healthcare, Siemens Molecular Imaging, AVID Radiopharmaceuticals, and the NIH (NIA, NCI). R. C. Petersen has consulted for Roche, Inc.; Genentech, Inc.; Eli Lilly, Inc.; Nestle, Inc.; and Eisai, Inc.; is on a DSMB for Genentech, Inc.; and receives royalties from Oxford University Press for Mild Cognitive Impairment and from UpToDate. His research funding is from NIH/NIA. V. K. Ramanan has received research funding from the NIH and the Mangurian Foundation for Lewy body disease research; has provided educational content for Medscape; has received speaker and conference session honoraria from the American Academy of Neurology Institute; is co‐PI for a clinical trial supported by the Alzheimer's Association; is site Co‐I for the Alzheimer's Clinical Trials Consortium; and is a site clinician for clinical trials supported by Eisai, the Alzheimer's Treatment and Research Institute at USC, and Transposon Therapeutics, Inc. P. Vemuri receives funding from the NIH. Author disclosures are available in the supporting information.

Figures

FIGURE 1
FIGURE 1
ROC curves with Youden index cutpoints for prediction of amyloid PET positivity. Youden index (J), used to identify optimal binary cutpoints jointly maximizing sensitivity and specificity is provided in addition to AUCs calculated from the ROC curve for all assays. Aβ, amyloid beta; AUC, area under the receiver operating characteristic curve; CI, confidence interval; PET, positron emission tomography; p‐tau, phosphorylated tau; ROC, receiver operating characteristic
FIGURE 2
FIGURE 2
Biomarker categorizations with 92% sensitivity and 96% specificity two‐cutpoint thresholds for the Lumipulse (A,C) and ALZpath (B,D) p‐tau217 assays (Test1). Lower and upper cutpoints are represented with green and red dashed lines, respectively. Gray shaded areas represent the intermediate zone in which samples would require follow‐up testing. Numbers shown on the plot represent the number of samples falling into each classification category and for the bottom plot are separated by amyloid PET positivity. PET, positron emission tomography; p‐tau, phosphorylated tau
FIGURE 3
FIGURE 3
Effect of amyloid positivity prevalence on the number of results in the intermediate range for the Lumipulse (A) and ALZpath (B) p‐tau217 assays. Calculations consider follow‐up amyloid PET testing of intermediates to be 100% sensitive and specific. Dotted lines plotted at 30, 50, and 65% amyloid PET positivity prevalence represent approximations of expected prevalence in populations of individuals with subjective cognitive impairment, mild cognitive impairment, and dementia, respectively. Positive predictive value (PPV), negative predictive value (NPV), and accuracy are dependent on the amyloid positive prevalence. PET, positron emission tomography; p‐tau, phosphorylated tau
See this image and copyright information in PMC

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