Clinical application of plasma P-tau217 to assess eligibility for amyloid-lowering immunotherapy in memory clinic patients with early Alzheimer's disease.

Background: With the approval of disease-modifying treatments (DMTs) for early Alzheimer's disease (AD), there is an increased need for efficient and non-invasive detection methods for cerebral amyloid-ß (Aß) pathology. Current methods, including positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis, are costly and invasive methods that may limit access to new treatments. Plasma tau phosphorylated at threonine-217 (P-tau217) presents a promising alternative, yet optimal cutoffs for treatment eligibility with DMTs like aducanumab require further investigation. This study evaluates the efficacy of one- and two-cutoff strategies for determining DMT eligibility at the Butler Hospital Memory & Aging Program (MAP). Methods: In this retrospective, cross-sectional diagnostic cohort study, we first developed P-tau217 cutoffs using site-specific training data and BioFINDER-2, which were then tested in potential DMT candidates from Butler MAP (total n = 150). ROC analysis was used to calculate the area under the curve (AUC) and accuracy of P-tau217 interpretation strategies, using Aß-PET/CSF testing as the standard of truth. Results: Potential DMT candidates at Butler MAP (n = 50), primarily diagnosed with mild cognitive impairment (n = 29 [58%]) or mild dementia (21 [42%]), were predominantly Aß-positive (38 [76%]), and half (25 [50%]) were subsequently treated with aducanumab. Elevated P-tau217 predicted cerebral Aß positivity in potential DMT candidates (AUC = 0.97 [0.92-1]), with diagnostic accuracy ranging from 0.88 (0.76-0.95, p = 0.028) to 0.96 (0.86-1, p < .001). When using site-specific cutoffs, a subset of DMT candidates (10%) exhibited borderline P-tau217 (between 0.273 and 0.399 pg/mL) that would have potentially required from confirmatory testing. Conclusions: This study, which included participants treated with aducanumab, confirms the utility of one- and two-cutoff strategies for interpreting plasma P-tau217 in assessing DMT eligibility. Using P-tau217 could potentially replace more invasive diagnostic methods, and all aducanumab-treated participants would have been deemed eligible based on P-tau217. However, false positives remain a concern, particularly when applying externally derived cutoffs that exhibited lower specificity which could have led to inappropriate treatment of Aß-negative participants. Future research should focus on prospective validation of P-tau217 cutoffs to enhance their generalizability and inform standardized treatment decision-making across diverse populations.

Clinical application of plasma P-tau217 to assess eligibility for amyloid-lowering immunotherapy in memory clinic patients with early Alzheimer's disease.

BACKGROUND: With the approval of disease-modifying treatments (DMTs) for early Alzheimer's disease (AD), there is an increased need for efficient and non-invasive detection methods for cerebral amyloid-ß (Aß) pathology. Current methods, including positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis, are costly and invasive methods that may limit access to new treatments. Plasma tau phosphorylated at threonine-217 (P-tau217) presents a promising alternative, yet optimal cutoffs for treatment eligibility with DMTs like aducanumab require further investigation. This study evaluates the efficacy of one- and two-cutoff strategies for determining DMT eligibility at the Butler Hospital Memory & Aging Program (MAP). METHODS: In this retrospective, cross-sectional diagnostic cohort study, we first developed P-tau217 cutoffs using site-specific and BioFINDER-2 training data, which were then tested in potential DMT candidates from Butler MAP (total n = 150). ROC analysis was used to calculate the area under the curve (AUC) and accuracy of P-tau217 interpretation strategies, using Aß-PET/CSF testing as the standard of truth. RESULTS: Potential DMT candidates at Butler MAP (n = 50), primarily diagnosed with mild cognitive impairment (n = 29 [58%]) or mild dementia (21 [42%]), were predominantly Aß-positive (38 [76%]), and half (25 [50%]) were subsequently treated with aducanumab. Elevated P-tau217 predicted cerebral Aß positivity in potential DMT candidates (AUC = 0.97 [0.92-1]), with diagnostic accuracy ranging from 0.88 (0.76-0.95, p = 0.028) to 0.96 (0.86-1, p < .001). When using site-specific cutoffs, a subset of DMT candidates (10%) exhibited borderline P-tau217 (between 0.273 and 0.399 pg/mL) that would have potentially required confirmatory testing. CONCLUSIONS: This study, which included participants treated with aducanumab, confirms the utility of one- and two-cutoff strategies for interpreting plasma P-tau217 in assessing DMT eligibility. Using P-tau217 could potentially replace more invasive diagnostic methods, and all aducanumab-treated participants would have been deemed eligible based on P-tau217. However, false positives remain a concern, particularly when applying externally derived cutoffs that exhibited lower specificity which could have led to inappropriate treatment of Aß-negative participants. Future research should focus on prospective validation of P-tau217 cutoffs to enhance their generalizability and inform standardized treatment decision-making across diverse populations.

Remote and in-clinic digital cognitive screening tools outperform the MoCA to distinguish cerebral amyloid status among cognitively healthy older adults.

INTRODUCTION: We evaluated the accuracy of remote and in-person digital tests to distinguish between older adults with and without AD pathological change and used the Montreal Cognitive Assessment (MoCA) as a comparison test. METHODS: Participants were 69 cognitively normal older adults with known beta-amyloid (Aß) PET status. Participants completed smartphone-based assessments 3×/day for 8 days, followed by TabCAT tasks, DCTclock™, and MoCA at an in-person study visit. We calculated the area under the curve (AUC) to compare task accuracies to distinguish Aß status. RESULTS: Average performance on the episodic memory (Prices) smartphone task showed the highest accuracy (AUC = 0.77) to distinguish Aß status. On in-person measures, accuracy to distinguish Aß status was greatest for the TabCAT Favorites task (AUC = 0.76), relative to the DCTclockTM (AUC = 0.73) and MoCA (AUC = 0.74). DISCUSSION: Although further validation is needed, our results suggest that several digital assessments may be suitable for more widespread cognitive screening application.