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-β (Aβ) 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 Aβ-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 Aβ-positive (38 [76%]), and half (25 [50%]) were subsequently treated with aducanumab. Elevated P-tau217 predicted cerebral Aβ 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 Aβ-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.

Access to novel disease modifying treatments (DMTs) for Alzheimer's disease (AD) hinges upon e cient detection of cerebral amyloid-β (Aβ) pathology in patients with early-stage disease (1,2).The recent Food and Drug Administration (FDA) approval of amyloid-lowering immunotherapies, such as aducanumab and lecanemab, necessitates the optimization of screening techniques for Aβ pathology, as biomarker con rmation of Aβ status is required prior to treatment (3,4).This important requirement represents a major barrier to treatment access for many patients due to current reliance on invasive and expensive positron emission tomography (PET) or cerebrospinal uid (CSF) testing (5), and may compound existing racial and ethnic inequalities in AD treatment (6-9).The development of a minimally invasive and costeffective screening method to facilitate early detection and intervention is, therefore, of high clinical importance in expanding equitable access to new and forthcoming treatments for early AD (1,10).
While Aβ-PET/CSF testing remains the standard-of-care, blood biomarkers have been extensively investigated and have been shown to accurately detect cerebral Aβ pathology in large observational cohort studies (10).Among them, plasma tau phosphorylated at threonine-217 (P-tau217) has emerged as the most promising, with data from the Swedish BioFINDER study and others demonstrating high accuracy for prediction of Aβ status (11)(12)(13)(14).While the majority of this work has focused on using a single P-tau217 cutoff to de ne Aβ status (referred to here as the 'one-cutoff' approach), a number of assay and patientdependent factors may contribute to test-retest variability and can lead to false positives and negatives (15).Emerging data suggests that using a tiered 'two-cutoff' approach can partly circumvent this issue by de ning a borderline or 'gray zone' of P-tau217 values that merit con rmatory testing (16,17), and theoretically expedited eligibility screening when applied to potential DMT candidates from BioFINDER-2 in a recent publication by Mattsson-Carlgren et al. (17).While these ndings are promising, data are limited in clinical populations who are actively seeking treatment with DMTs, and there is a need to explore the generalizability of cutoffs between cohorts to represent how these tests are likely to be used in clinical practice.
Therefore, we sought to address these knowledge gaps by examining the diagnostic performance of P-tau217 at the Butler Hospital Memory & Aging Program (MAP).We hypothesized that plasma P-tau217 would predict Aβ positivity with high diagnostic accuracy when assessing eligibility for treatment with aducanumab.To con rm the usefulness of one-and two-cutoff approaches to P-tau217 interpretation in a relevant clinical context, we established cutoffs in a cohort of Butler MAP Aβ-positive and -negative controls of mixed cognitive status (n = 50), and then cross-validated these cutoffs in a separate cohort that included patients who subsequently received aducanumab alongside Aβ-positive and -negative controls with mild cognitive impairment (MCI) or mild dementia with no contraindications to aducanumab according to the Appropriate Use Recommendations (n = 50) (3).We additionally compared diagnostic performance of these cutoffs to a matched sample of BioFINDER-2 participants with MCI or mild dementia (n = 50), as well as the previously published cut-offs identi ed by Mattsson-Carlgren et al. (17) in predicting Aβ status in all BioFINDER-2 participants deemed potentially eligible for DMTs.
Our ndings highlight the promise of P-tau217 in expediting DMT eligibility determination, while also addressing key challenges that we address with site-speci c cutoffs and comparison of interpretation strategies to handle intermediate P-tau217 values.Our ndings, established in memory clinic patients seeking treatment with aducanumab, the rst FDA-approved DMT, mark an important translational step towards expanding access to current and future DMTs, a key priority for the eld that is expected to improve clinical outcomes for patients living with early AD.

Study design
We conducted a retrospective, cross-sectional, diagnostic cohort study of Butler Alzheimer's Prevention Registry participants (18).We included participants who began treatment with aducanumab in our memory clinic between June 16, 2021 and August 1, 2022, alongside additional Aβ-positive and -negative controls who were enrolled in the Registry Biobanking Substudy.We included all participants with MCI or mildmoderate dementia with known Aβ status in our analysis, including all participants who received aducanumab treatment and those who did not.To achieve su cient sample size for model training, we also included Aβ-positive and negative controls with a lookback period of 3 years.Participants were then divided into Butler MAP Training and Test Cohorts according to the following criteria.The Training Cohort (n = 50) included all preclinical Aβ-positive and negative controls (n = 37) alongside untreated MCI or mild-moderate dementia cases (n = 13).The Test Cohort (n = 50) included all aducanumab-treated cases (n = 25) alongside randomly selected Aβ-positive and -negative controls with MCI or mild dementia (n = 25).To re ect the high prevalence of Aβ-positivity in our tertiary memory clinic setting, controls were selected to achieve an overall prevalence of ~ 70% Aβ-positivity in the total sample.

Butler MAP participants
Registry participants were selected for aducanumab treatment by their memory clinic physician based on clinical judgement according to the Appropriate Use Recommendations, as previously described (3,19).To determine eligibility, the standard work-up included a full history, informant report, cognitive screening (Mini-Mental State Examination [MMSE], Montreal Cognitive Assessment [MoCA]), complete physical exam, general laboratory work-up, brain magnetic resonance imaging (MRI), and Aβ-PET/CSF testing.Neuropsychological testing was performed by a clinical neuropsychologist on a case-by-case basis for clinical purposes.A board-certi ed neurologist or geriatric psychiatrist was responsible for determining diagnosis, and for those found eligible, treatment decisions were made collaboratively with patients and families after careful informed consent.General data collection protocols for the Butler Alzheimer's Prevention Registry are listed in the Supplementary Methods and have been previously published (18-20).Study participation was not required to receive treatment with aducanumab.All participants provided written informed consent to sharing of deidenti ed data and biospecimens.Local study procedures were approved by the Butler Hospital Institutional Review Board (IRB #2108-001, #1604-001) and were consistent with the Helsinki Declaration of 1975.

BioFINDER-2 participants
The BioFINDER-2 database was searched to generate a separate BioFINDER-2 Training Cohort (n = 50) containing participants with MCI or mild dementia.BioFINDER-2 participants were selected to approximately match to the Butler MAP Test Cohort on group-level clinical characteristics (Age, APOE-ε4 status, MMSE, Clinical Diagnosis, and Aβ positivity) irrespective of P-tau217 levels.Selection was blinded to participant-level data from the Butler MAP Test Cohort.Procedures for the Swedish BioFINDER-2 Study (NCT03174938) procedures were approved by the Regional Ethics Committee in Lund, Sweden.Details of these procedures have been described elsewhere and are summarized in the Supplementary Methods (11).

Apolipoprotein E (APOE) Genotyping
Participants underwent an optional cheek swab to collect epithelial cells for genotyping.Sequences were ampli ed using primers corresponding to each allele with the Genomadix PCR method as previously described (20).

Plasma P-tau217 quanti cation
Laboratory procedures were identical for BioFINDER-2 and Butler MAP participants.Brie y, trained technicians drew whole venous blood (20 mL) into 10 ml EDTA draw tubes.Blood samples were centrifuged at 2,000g for 15 minutes, then the plasma fraction was aliquoted into 1 mL polypropylene cryovials and stored at -80°C.P-tau217 analysis was conducted in a single batch for Butler MAP and a separate batch for BioFINDER-2, respectively, by the Hansson laboratory at Lund University, Sweden, using the Mesoscale Discovery (MSD) platform in a blinded fashion as previously described (11).The assay was calibrated using a recombinant tau (4R2N) protein that was phosphorylated in vitro and characterized by mass spectrometry (11,21).Plasma samples, after thawing on ice, were lightly vortexed and centrifuged at 2,000 g for 10 minutes.Plasma was then diluted 1:2 with sample buffer containing a heterophilic blocking reagent.MSD small-spot streptavidin-coated plates were prepared by blocking with 3% BSA in DPBS.After washing, biotinylated-IBA493, a capture antibody, was added to the wells for incubation.Following another wash, 50 µl of diluted plasma sample or calibrator was added to each well for a two-hour incubation.After this, the plates were washed, and the SULFO-tagged E2 (anti-Tau) detection antibody was introduced.Read buffer was applied and P-tau217 levels subsequently quanti ed using the MSD SQ120.

Reference Standards
In Butler MAP participants, we determined Aβ status using clinically available tests representing the standard-of-care for patients in the United States.Aβ-PET imaging was performed using FDA-approved radiotracers ( 18 F-orbetapir or 18 F-orbetaben), with positive or negative results determined by expert clinical visual read as previously described (22,23).For CSF analysis, lumbar puncture (LP) was performed and CSF concentrations of P-tau181, total tau and Aβ 42 were measured using validated, clinically available immunoassays performed by Mayo Clinic Laboratories (Rochester, MN) or Athena Diagnostics (Marlborough, MA).CSF analysis was performed to calculate the P-tau181/Aβ 42 ratio by Mayo Clinic Laboratories (Aβ positivity de ned using a laboratory-speci c cutoff of P-tau181/Aβ 42 ≥ 0.028) or P-tau181 with Aβ 42 /total-tau index (ATI, Athena Diagnostics) using the ADMark® assay (Aβ positivity de ned using laboratory-speci c cutoffs as ATI < 1 and P-tau-181 > 61 pg/mL) (24).CSF analysis was performed on a case-by-case basis as part of routine clinical care, with Aβ status reported by the laboratory based on these cutoffs which are in line with previously published data and recommended clinical guidelines (24-26).

Statistical analysis
All analyses were conducted in R (Version 4.2.2) using the pROC and caret packages by a blinded investigator.Receiver operator characteristic (ROC) analysis was employed to calculate the area under the curve (AUC) of the model, along with sensitivity, speci city, and positive/negative predictive values (PPV, NPV) at pre-speci ed cutoffs (Youden, 90% Sensitivity, 90% Speci city) that are consistent with the literature, using Aβ-PET/CSF testing as the standard of truth (17).Participants in each cohort were categorized using one-and two-cutoff approaches.The one-cutoff approach assigned participants Aβ positive/negative status based on the Youden cutoff from the training data.Using the two-cutoff approach, participants were classi ed as negative, intermediate, or positive based on 90% Sensitivity or Speci city cutoffs.Those with intermediate P-tau217 values were handled using 'inclusive' and 'exclusive' strategies; the former assigned statuses based on known Aβ-PET/CSF results, while the latter excluded such participants from analysis.Confusion matrices for each strategy were generated using the caret package.Accuracy estimates and AUCs are reported with 95% con dence intervals (CI); accuracy was compared to the no-information rate using the exact binomial test, with statistical signi cance de ned as p < 0.05.Additionally, logistic regression was performed to examine the prediction of Aβ status with plasma P-tau217, with adjustment for age, sex, APOE-ε4 allele frequency, MoCA score, clinical diagnosis, and timing of reference standard testing (expressed as months from blood draw and Aβ-PET/CSF testing).All participants had available P-tau217 or Aβ-PET/CSF testing data, obviating the need for imputation or removal of cases for the primary outcomes reported in our analysis.For the adjusted model, missing-atrandom covariates were handled by multiple imputation by chained equations, detailed in Supplementary Table 1.

Diagnostic performance of plasma P-tau217
To examine the diagnostic performance of plasma P-tau217, we rst performed ROC analysis with con rmed Aβ status (by PET or CSF) as the outcome variable in the Butler MAP Training Cohort (Fig. 1).This analysis indicated that P-tau217 predicted Aβ status with an AUC of 0.88 (95% CI: 0.76-1).Similarly, ROC analysis in the BioFINDER-2 Training Cohort identi ed robust prediction of Aβ status with P-tau217 (AUC = 0.99 [95% CI: 0.98-1]) (Fig. 2).
In Butler MAP participants, adjusting for age, sex, APOE-ε4 genotype, MoCA score, clinical diagnosis, as well as timing and type of reference standard used (PET or CSF) did not attenuate the relationship between P-tau217 and Aβ positivity, with statistically signi cant independent effects observed for P-tau217 (p = 0.001), age (p = 0.002) and APOE-ε4 genotype (p = 0.019) (Supplementary Table 2).The adjusted model exhibited similar performance to P-tau217 alone in the Butler MAP Training Cohort (AUC = 0.91 [95% CI: 0.88-0.94])(Supplementary Fig. 1).Taken together, these ndings from two separate cohorts, as well as our adjusted model, consistently identi ed plasma P-tau217 as an independent predictor of Aβ positivity.

Development of the one-and two-cutoff approaches
To rst develop our approaches for individual-level biomarker interpretation, we used the Butler MAP Training Cohort to create two distinct models with prespeci ed plasma P-tau217 cutoff characteristics (Fig. 1, Panel B).For development of the one-cutoff model, we performed ROC analysis to identify the P-tau217 level which corresponds to the maximal Youden index.This approach identi ed an optimal onecutoff of [P-tau217] ≥ 0.27 pg/mL, which in the Training Cohort predicted Aβ status with a diagnostic accuracy of 0.86 (95% CI: 0.73-0.94),p < 0.001; Fig. 1; Supplementary Table 3).
We then sought to improve prediction of intermediate P-tau217 values using the two-cutoff model, an alternative approach that strati es participants using low and high cut-offs that are optimized for sensitivity and speci city, respectively.We rst performed ROC analysis to identify a lower cutoff with a prespeci ed sensitivity ≥ 0.9, which corresponded to [P-tau217] < 0.273 pg/mL.Next, we identi ed a higher cutoff with a prespeci ed speci city ≥ .9, which corresponded to 0.399 pg/mL (prespeci ed sensitivity and speci city parameters were chosen based on the literature ( 17)).We then applied these cutoffs to stratify participants into three groups as follows: 1) Presumed Aβ-negative ([P-tau217] < 0.273 pg/mL), 2) Gray Zone ([P-tau217] = 0.273-0.399pg/mL), and 3) Presumed Aβ-positive ([P-tau217] ≥ 0.399 pg/mL) (Fig. 1, Panel B).
Participants in groups 1 and 3 were classi ed based on their P-tau217 level, while participants falling in the Gray Zone (n = 12 [24%]) were instead either classi ed based on previously obtained Aβ-PET/CSF testing ('inclusive' approach, modeling a situation where these results triggered con rmatory testing for all participants) or removed from the analysis ('exclusive' approach, modeling a situation where these intermediate values were considered inconclusive, thus excluded from treatment).Applying the inclusive approach produced an overall diagnostic accuracy of 0.92 (95% CI: 0.81-0.98,p < 0.001), while using the exclusive approach produced a diagnostic accuracy of 0.89 (95% CI: 0.75-0.97,p < 0.001).
In summary, our analysis found that while diagnostic performance of P-tau217 was similar between Butler MAP and BioFINDER-2 Training Cohorts, the cutoffs differed, with lower plasma [P-tau217] values favored in the BioFINDER-2 Training Cohort.Therefore, to assess the performance of these cutoffs and approaches when screening for DMT eligibility, we next sought to determine their performance when applied to the Butler MAP Test Cohort.

Cross-validation of P-tau217 in the Butler MAP Test Cohort
To cross-validate our ndings in potential DMT candidates from our memory clinic, we next examined the diagnostic performance of plasma P-tau217 in the Butler MAP Test Cohort (n = 50).ROC analysis demonstrated that P-tau217 predicted Aβ status in these participants, all potential DMT candidates (AUC = 0.97 [95% CI: 0.92-1]; Fig. 3, Panel A), which was also observed in the adjusted model (AUC = 0.99 [95% CI: 0.98-0.99];Supplementary Fig. 2, Panel A).We then compared the one-and two-cutoff approaches using the 'site-speci c' cutoffs generated in the Butler MAP Training Cohort, as well as those identi ed from the 'external' BioFINDER-2 Training Cohort to provide a comparison of cutoff generalizability.
Applying the site-speci c cutoffs to the Butler MAP Test Cohort, we found that the one-cutoff approach demonstrated a diagnostic accuracy of 0.90 (95% CI: 0.78-0.96,p = 0.011; Table 3; Fig. 3, Panel B).The twocutoff approach identi ed 6 (12%) of P-tau217 values falling within the Gray Zone, impacting 3 Aβ-positive and 3 Aβ-negative participants.When these gray zone cases were excluded from the analysis, the twocutoff approach exhibited a diagnostic accuracy of 0.96 (0.86-1, p < 0.001); when these cases were included based on known Aβ-PET/CSF testing, the model had a diagnostic accuracy of 0.95 (95% CI: 0.84-0.99,p = 0.003; Table 3; Fig. 3, Panel B).Similar ndings were observed with statistically signi cant diagnostic accuracy of one-cutoff and two-cutoff approaches in the adjusted model (all p < 0.001; Supplementary Table 4). 2 P-value: accuracy of model prediction of cerebral Aβ status compared to the no information rate. 3BioFINDER-2 cutoffs identi ed 1 Aβ positive and 4 Aβ negative participants in the intermediate "gray zone" (5/50 = 10%). 4Remaining sample size after removal of 5 intermediate cases. 5Site-speci c cutoffs identi ed 3 Aβ positive and 3 Aβ negative participants in the intermediate "gray zone" (6/50 = 12%).
6 Remaining sample size after removal of 6 intermediate cases.
In comparison, applying the externally derived BioFINDER-2 cutoffs had a diagnostic accuracy of 0.88 (0.76-0.95, p = 0.028) using the one-cutoff approach, and an accuracy of 0.92 (95% CI: 0.81-0.98,p = 0.003) or 0.91 (0.79-0.98, p = 0.079) when using the two-cutoff approach with inclusive or exclusive handling of Gray Zone cases, respectively (n = 5 [10%]; 1 Aβ-positive and 4 Aβ-negative; Table 3; Fig. 3, Panel C).As an additional control, we also tested previously published cutoffs from an unmatched sample of BioFINDER-2 DMT programs such as ours, paving the way for broader treatment accessibility in primary care and other non-tertiary settings.
These ndings are timely given the anticipated Revised Criteria for Diagnosis and Staging of AD from the Alzheimer's Association Work Group, which at present proposes that elevated plasma P-tau217 is su cient to ful ll Core 1 criteria for A (amyloidosis) and T1 (secreted phosphorylated tau fragments) for a biomarker diagnosis of AD (28).However, Core 2 criteria including tau tangle burden (T2) is not fully captured by P-tau217 and may be an important factor in predicting response to amyloid-lowering treatments, as seen in the recently published phase 3 data for donanemab (27).A recent study identi ed CSF microtubule-binding region of tau containing the residue 243 (MTBR-tau43) as a novel uid biomarker of tau tangle pathology, holding potential alongside P-tau217 and other biomarkers for detailed molecular staging of AD, although more work is needed to examine its performance as a more accessible blood test (29).If successful, this methodological innovation would represent a major step forward in the biomarker eld, potentially shaping future personalized medicine approaches to DMTs.
Our retrospective analysis indicates that P-tau217 is a promising tool to determine DMT eligibility for individuals seeking treatment with aducanumab, and our comparison of cutoffs and strategies in a cohort of patients subsequently treated with aducanumab marks an important translational step towards providing clinical guidance on the use of speci c blood biomarker interpretation strategies at the level of an individual patient (30).Our data suggest that the use of two-cutoffs to stratify patients is feasible in the memory clinic setting, and may reduce false positives to more effectively discriminate AD from non-AD cases.Rather than replacing PET/CSF tests entirely, this more nuanced approach addresses the diagnostic uncertainty in borderline cases by providing standardized guidance to target con rmatory testing to this group.While we relied on a single reference method for our analysis, removing the intermediate-range cases from treatment decisions also proved to be an effective approach.Alternatively, the use of targeted CSF testing to handle intermediate-range P-tau217 is supported by two recently published studies which showed that showed enhanced prediction of amyloid PET status using P-tau217 with re ex CSF con rmatory testing (16,17).
Based on these results, it appears that the two-cutoff strategy could be a viable alternative for reducing reliance on PET/CSF testing when determining DMT eligibility.However, more work is needed to assess how clinical outcomes may change when these approaches are used to prospectively select patients for treatment.
Importantly, our study identi ed higher optimal cutoffs than the recent paper by Mattsson-Carlgren et al. (17), despite harmonized blood collection protocols, centralized measurement of P-tau217 levels, similar analytic approaches and large effect sizes for the prediction of amyloid status (17).This could be due to differences in the inclusion of preclinical AD in the Butler MAP Training Cohort or test-retest variability in immunoassay performance, although the adjusted model and the cutoffs generated in the matched BioFINDER-2 Training Cohort argue against these explanations.Ongoing efforts by our laboratory and others to develop and re ne standardized calibrators may help to further reduce inter-assay variability observed with immunoassay techniques (1).Avenues for future research include examining prediction models that control for speci c comorbidities and medications that may in uence P-tau217 levels (15,31,32), as well as exploration of as-yet unknown lifestyle factors (i.e.diet, exercise, sleep, stress) and differing prevalence of AD that could impact choice of cutoff for a given population.Given the strong internal validity between training/test cohorts our study and the analysis by Mattsson-Carlgren et al. (17), and the differences in optimal cutoffs that were observed between these studies, we continue to recommend using site-speci c cutoffs when considering implementation of P-tau217 for clinical use, as speci c cutoffs are not yet generalizable.
While our study's ndings are promising, they must be interpreted within the context of some important limitations.The retrospective, cross-sectional design limits our ability to compare P-tau217 with multiple measures of Aβ or tau status, and additionally limits our ability to assess treatment outcomes when P-tau217 is used to detect Aβ positivity compared to standard approaches.Although we have previously published data on a subset of participants who experienced amyloid-related imaging abnormalities (ARIA), treatment decisions were made based on Aβ-PET/CSF results in line with the Appropriate Use Recommendations for aducanumab (3,19).While our sample included all registry participants treated with aducanumab in our clinic (and are generally re ective of those who traditionally participate in DMT trials at our site), the potential for ascertainment bias and our limited sample size likely reduces generalizability compared to other, larger studies (17).Furthermore, this cohort is not demographically diverse and does not fully represent the general population at risk for AD, a problem for research on blood biomarkers, DMTs and the eld more broadly (6, 7).There may be important uid and imaging biomarker-related interactions with self-reported race, social determinants of health, medical comorbidities and APOE genotype that remain understudied and not captured by our analysis (33)(34)(35)(36).
Future prospective research should seek to identify and address remaining barriers to routine clinical use with a focus on diverse populations in non-tertiary care settings.This is essential, especially in the context of efforts to expand treatment to traditionally underserved groups.Surmounting these remaining hurdles will require coordinated efforts between clinical sites to assess the precision and reliability of P-tau217 measurements when conducted on an individual basis, as opposed to batch testing, to ensure consistent and accurate results in clinical practice given the potential for inter-assay variability (1).We must also move to assess dissemination and implementation-based strategies to improve communication of advances in the eld to community healthcare providers and patients, with the goal of improving AD diagnosis and treatment in equitable and sustainable ways.

CONCLUSIONS
This study substantiates the use of plasma P-tau217 as a viable biomarker for DMT eligibility screening, with potential signi cant impacts on clinical practice.The two-cutoff strategy presents an innovative method to re ne biomarker analysis for the purpose of determining treatment eligibility or need for additional con rmatory testing.These ndings underscore the challenge of applying speci c cutoffs across studies and populations.Future research should aim to develop standardized cutoffs using samples drawn from multiple sites, and investigate broader clinical applications of P-tau217 and other blood biomarkers.

Declarations
Ethics approval and consent to participate

Table 3
Comparison of one and two-cutoffs for DMT eligibility screening.