Blood biomarkers (BBMs) represent an acceptable, accessible, equitable, and scalable alternative to amyloid positron emission tomography (PET) or cerebrospinal fluid (CSF) biomarkers to help establish an Alzheimer's disease diagnosis. The PrecivityAD2 test (C2N Diagnostics, St. Louis, MO) is a multi-analyte assay with algorithmic analysis (MAAA) BBM test that detects presence of brain amyloid plaques with high diagnostic accuracy among patients undergoing evaluation for cognitive impairment. While the clinical validity of the PrecivityAD2 test has been established, its budgetary impact has not been well described. Our budget impact model, based on a decision tree that considered a one million (1MM) US health plan population, evaluated the effects of PrecivityAD2 test adoption as a first evaluation at the neurologist's office versus the first current standard use of PET or CSF testing in patients with cognitive impairment. We used estimates of real-world adoption, adherence, and drop-out measures drawn from clinical expert opinion as well as clinical utility study data, rather than idealized scenarios, to simulate clinical practice more closely. A clinical pathway using the PrecivityAD2 test early in the evaluation process had improved sensitivity (90.1% vs 93.5%) and reduced specificity (92.3% vs 84.8%) as compared to usual care utilizing PET or CSF biomarkers as first-line biomarker testing. Net savings from PrecivityAD2 test use in the diagnostic work-up was $10.9MM or $0.91 per member per month (PMPM) in this 1MM lives model, representing a 26.2% reduction in total costs for AD evaluation. Among diagnosed cases in the model, PrecivityAD2 testing resulted in cost savings of $2,753 and $3,578 per case identified at 40% and 100% test penetration, respectively. Savings were driven by reductions in utilization of PET and CSF testing. The potential for economic impact is significant: at a 40% adoption rate, savings to the US healthcare system could exceed $3.5B dollars. In a budget impact model, PrecivityAD2 testing prior to usual care brain amyloid detection methods in patients undergoing evaluation for cognitive impairment provides cost savings and reduces the predicted burden on both patients and payers, while maintaining a high quality of care.

BACKGROUND:Blood biomarkers (BBMs) represent an acceptable, accessible, equitable, and scalable alternative to amyloid positron emission tomography (PET) or cerebrospinal fluid (CSF) biomarkers to help establish an Alzheimer's disease diagnosis. The PrecivityAD2 test (C2N Diagnostics, St. Louis, MO) is a multi-analyte assay with algorithmic analysis (MAAA) BBM test that detects presence of brain amyloid plaques with high diagnostic accuracy among patients undergoing evaluation for cognitive impairment. While the clinical validity of the PrecivityAD2 test has been established, its budgetary impact has not been well described. METHOD:Our budget impact model, based on a decision tree that considered a one million (1MM) US health plan population, evaluated the effects of PrecivityAD2 test adoption as a first evaluation at the neurologist's office versus the first current standard use of PET or CSF testing in patients with cognitive impairment. We used estimates of real-world adoption, adherence, and drop-out measures drawn from clinical expert opinion as well as clinical utility study data, rather than idealized scenarios, to simulate clinical practice more closely. RESULT:A clinical pathway using the PrecivityAD2 test early in the evaluation process had improved sensitivity (90.1% vs 93.5%) and reduced specificity (92.3% vs 84.8%) as compared to usual care utilizing PET or CSF biomarkers as first-line biomarker testing. Net savings from PrecivityAD2 test use in the diagnostic work-up was $10.9MM or $0.91 per member per month (PMPM) in this 1MM lives model, representing a 26.2% reduction in total costs for AD evaluation. Among diagnosed cases in the model, PrecivityAD2 testing resulted in cost savings of $2,753 and $3,578 per case identified at 40% and 100% test penetration, respectively. Savings were driven by reductions in utilization of PET and CSF testing. The potential for economic impact is significant: at a 40% adoption rate, savings to the US healthcare system could exceed $3.5B dollars. CONCLUSION:In a budget impact model, PrecivityAD2 testing prior to usual care brain amyloid detection methods in patients undergoing evaluation for cognitive impairment provides cost savings and reduces the predicted burden on both patients and payers, while maintaining a high quality of care.

Blood biomarker (BBM) tests for Alzheimer’s disease represent accurate and accessible tools to aid healthcare providers (HCPs) in the evaluation of patients presenting with signs or symptoms of mild cognitive impairment or dementia. The objective of this analysis was to examine the effects of patient age and sex on clinical decisions using a commercially available mass spectrometry BBM test (PrecivityAD2™ test) yielding the Amyloid Probability Score 2 (APS2), which informs on the likelihood of a positive amyloid PET scan result. This secondary analysis of the QUIP II Study (NCT06025877) included 203 patients (average age 74 years, 53% female) evaluated by 12 HCPs representing 8 outpatient sites. Clinical decision-making was recorded by survey pre- and post-BBM testing. The composite primary endpoint, defined as a change in AD diagnostic certainty, AD medications, or additional brain amyloid evaluation pre- and post-BBM testing, was 75% (p < 0.0001 versus pre-specified threshold of 20% clinically meaningful change). The relationship between APS2 and composite endpoint was highly significant (p < 0.0001), yet was not significantly different when stratified by age (p = 0.94) or sex (p = 0.337). In a subgroup analysis of the three individual components of the composite endpoint, the only significant finding was that the magnitude of change in pre- and post-BBM AD diagnostic certainty was lower in the Negative APS2 patients aged 60-69 versus Negative APS2 patients aged 80 and older (p = 0.01), likely related to a lower pre-test AD probability among younger patients. These study results support the usefulness and generalizability of this BBM test in clinical care.

Global implementation of blood tests for Alzheimer's disease (AD) would be facilitated by easily scalable, cost-effective and accurate tests. In the present study, we evaluated plasma phospho-tau217 (p-tau217) using predefined biomarker cutoffs. The study included 1,767 participants with cognitive symptoms from 4 independent secondary care cohorts in Malm & ouml; (Sweden, n = 337), Gothenburg (Sweden, n = 165), Barcelona (Spain, n = 487) and Brescia (Italy, n = 230), and a primary care cohort in Sweden (n = 548). Plasma p-tau217 was primarily measured using the fully automated, commercially available, Lumipulse immunoassay. The primary outcome was AD pathology defined as abnormal cerebrospinal fluid A beta 42:p-tau181. Plasma p-tau217 detected AD pathology with areas under the receiver operating characteristic curves of 0.93-0.96. In secondary care, the accuracies were 89-91%, the positive predictive values 89-95% and the negative predictive values 77-90%. In primary care, the accuracy was 85%, the positive predictive values 82% and the negative predictive values 88%. Accuracy was lower in participants aged >= 80 years (83%), but was unaffected by chronic kidney disease, diabetes, sex, APOE genotype or cognitive stage. Using a two-cutoff approach, accuracies increased to 92-94% in secondary and primary care, excluding 12-17% with intermediate results. Using the plasma p-tau217:A beta 42 ratio did not improve accuracy but reduced intermediate test results (<= 10%). Compared with a high-performing mass-spectrometry-based assay for percentage p-tau217, accuracies were comparable in secondary care. However, percentage p-tau217 had higher accuracy in primary care and was unaffected by age. In conclusion, this fully automated p-tau217 test demonstrates high accuracy for identifying AD pathology. A two-cutoff approach might be necessary to optimize performance across diverse settings and subpopulations.

Objective: The objective of this study was to assess clinical decision-making associated with the use of a multi-analyte blood biomarker (BBM) test among patients presenting with signs or symptoms of mild cognitive impairment or dementia. Methods: The Quality Improvement PrecivityAD2 (QUIP II) Clinician Survey (NCT06025877) study evaluated the clinical utility of the PrecivityAD2™ blood test in a prospective, single cohort of 203 patients presenting with symptoms of Alzheimer’s disease (AD) or other causes of cognitive decline across 12 memory specialists. The PrecivityAD2 blood test (C2N Diagnostics, St. Louis, MO) combines the plasma Aβ42/Aβ40 ratio and the p-tau217/np-tau217 ratio (%p-tau217) measurements in a statistical algorithm to yield an Amyloid Probability Score 2 (APS2) that informs on the likelihood of brain amyloid plaques. After receiving the BBM test results, clinicians completed surveys on management strategies for each patient. Results: Patients had a median age of 74, 53% were female, and 28% were traditionally under-represented in Black, Hispanic, and Asian groups. The composite primary endpoint, defined as a change in AD diagnostic certainty, drug therapy, or additional brain amyloid evaluation pre- and post-BBM testing, was 75% (p < 0.0001 versus the pre-specified threshold of 20% clinically meaningful change). Anti-AD medication orders decreased among negative APS2 patients and increased among positive APS2 patients (p < 0.0001). Additional brain amyloid testing decreased among negative APS2 patients (p < 0.0001). Conclusions: This blood biomarker test can help memory specialists guide patients to anti-AD therapies as well as rule out AD to allow for other diagnostic considerations.

Background/Objectives: A high-performing blood biomarker (BBM) test for Alzheimer’s disease (AD) represents an accurate, accessible, and scalable tool to aid healthcare professionals (HCPs) evaluating patients presenting with signs or symptoms of mild cognitive impairment (MCI) or dementia. However, implementation of AD blood tests into clinical practice has not been extensively evaluated. The objective of this study was to assess the implementation of the multi-analyte PrecivityAD2™ blood test (C2N Diagnostics, LLC, St. Louis, MO, USA) into the clinical workflow of memory care clinics. Methods: A total of 8 HCPs (neurologists, geriatricians, geriatric psychiatrists) who served as site directors from 8 outpatient sites that evaluated 203 cognitively symptomatic patients were included in this sub-study of the real-world QUIP II Study (NCT06025877). Implementation of this blood test was assessed through surveying these HCPs using published frameworks including the Technology Acceptance Model, net promoter score, and forced choice preference questions. These assessments were analyzed using Wilcoxon signed-rank test, Fisher’s Exact test, and Wilcoxon signed-rank test, respectively. Results: HCPs reported acceptance scores that averaged 9.6 out of 10 (p < 0.0001, effect size 0.840): the test’s contribution to clinical decision-making as well as the ease of understanding test results received the highest ratings. The net promoter score was 75 (p < 0.0001), exceeding the typical benchmark of 30 reported as good levels of satisfaction in healthcare settings. The APS2 results and individual blood analyte results were rated with similar preference around their roles in HCP clinical decision-making. Conclusions: The results indicate early evidence of user acceptance and recognition by HCPs that this AD blood test can personalize the clinical care pathway for evaluating cognitively symptomatic patients.

An accurate blood test for Alzheimer’s disease (AD) could streamline the diagnostic work-up and treatment of AD. Our aim was to evaluate an AD blood test in primary and secondary care, using predefined biomarker cutoffs and prospective analyses of plasma samples. 940 prospective and unselected patients seeking medical evaluation for early cognitive symptoms were included. Plasma %p-tau217 and Aβ42/40 was measured using mass spectrometry and the Amyloid Probability Score-2 (APS2) combining these values was calculated. Predefined cutoffs were established in an independent training cohort and were applied to primary (n=307) and secondary care (n=300) cohorts comprised of patients undergoing cognitive evaluation where plasma samples were analyzed in single batches. The blood test was then evaluated prospectively in primary (n=100) and secondary (n=234) care patients where plasma samples were analyzed bi-weekly. The main outcome was amyloid status as determined by cerebrospinal fluid AD biomarker positivity. In primary care, 51% of patients were AD pathology positive and were diagnosed with the following: 25% subjective cognitive decline (SCD), 47% mild cognitive impairment (MCI), and 28% dementia. In secondary care 49% were AD pathology positive and diagnoses were 21% SCD, 43% MCI, and 36% dementia. Using single batch analyses in primary care, the AUC for APS2 was 0.97 (95% CI 0.95–0.99), PPV 91% (87–96%), and NPV 92% (87–96%); in secondary care, the AUC was 0.96 (0.94–0.98), PPV 88% (83–93%), and NPV 87% (82–93%). When samples were analyzed prospectively in primary care, the AUC was 0.97 (0.95–1.00), PPV 90% (81–99%), and NPV 90% (82–98%); in secondary care, the AUC was 0.97 (0.94–0.99), PPV 92% (86–97%), and NPV 89% (83–94%). Primary care physicians accurately identified AD in 58% of patients after a standard work-up versus 89% (83–95%) for APS2 (p<0.001). Dementia experts had a diagnostic accuracy of 74% (69–80%) versus 90% (86–94%) for APS2 (p<0.001). At AAIC, we will also present prospective data using plasma p-tau217 immunoassay-based tests. Highly accurate AD blood tests might improve the diagnostic work-up of individuals with cognitive symptoms in primary and secondary care. Future studies are needed to further evaluate these tests prospectively in primary care of other countries.

Anti-amyloid treatments for early symptomatic Alzheimer disease have recently become clinically available in some countries, which has greatly increased the need for biomarker confirmation of amyloid pathology. Blood biomarker (BBM) tests for amyloid pathology are more acceptable, accessible and scalable than amyloid PET or cerebrospinal fluid (CSF) tests, but have highly variable levels of performance. The Global CEO Initiative on Alzheimer's Disease convened a BBM Workgroup to consider the minimum acceptable performance of BBM tests for clinical use. Amyloid PET status was identified as the reference standard. For use as a triaging test before subsequent confirmatory tests such as amyloid PET or CSF tests, the BBM Workgroup recommends that a BBM test has a sensitivity of ≥90% with a specificity of ≥85% in primary care and ≥75-85% in secondary care depending on the availability of follow-up testing. For use as a confirmatory test without follow-up tests, a BBM test should have performance equivalent to that of CSF tests - a sensitivity and specificity of ~90%. Importantly, the predictive values of all biomarker tests vary according to the pre-test probability of amyloid pathology and must be interpreted in the complete clinical context. Use of BBM tests that meet these performance standards could enable more people to receive an accurate and timely Alzheimer disease diagnosis and potentially benefit from new treatments.

Abstract There is an important unmet need for timely, noninvasive, low-burden diagnostic tools to aid in Alzheimer’s disease evaluation. The AAA-BBM2 (PrecivityAD2™) blood test combines plasma amyloid beta (AB)42/40 Ratio and phosphorylated-tau217/non-phosphorylated-tau217 Ratio (%p-tau217) into a clinically-validated algorithm. The test result, the Amyloid Probability Score 2 (APS2), determines the likelihood of brain amyloid, the pathological hallmark of Alzheimer’s disease, on amyloid PET scan: the test result has previously demonstrated 88% sensitivity and 89% specificity. The objective of the QUIP II Study (NCT06025877) is to evaluate the clinical utility of this blood biomarker test with APS2 result among cognitively symptomatic patients presenting to memory specialists. To date, 52 symptomatic patients (median age 75, 65% female, 77% white) from 7 memory centers received the AAA-BBM2 test. Concordance with intended use of the test was 100% (52/52). Positive APS2 results were noted in 26 patients (50%). From pre- to post-test, clinician-reported probability of AD decreased from 48% to 16% among negative APS2 patients (p< 0.0001), and increased from 71% to 93% among positive APS2 patients (p< 0.0001). The composite endpoint of change in AD diagnostic certainty, drug therapy, or brain amyloid evaluation pre- and post-AAA-BBM2 testing was 79% (p < 0.0001 versus a pre-specified threshold of 20% clinically meaningful change). We believe that the AAA-BBM2 test showed clinical utility in its association with changes in clinicians’ diagnostic certainty and clinical management among patients presenting with cognitive impairment. This blood biomarker test may allow memory specialists to guide patients to anti-AD therapies and facilitate other diagnostic considerations.

ImportanceAn accurate blood test for Alzheimer disease (AD) could streamline the diagnostic workup and treatment of AD.ObjectiveTo prospectively evaluate a clinically available AD blood test in primary care and secondary care using predefined biomarker cutoff values.Design, Setting, and ParticipantsThere were 1213 patients undergoing clinical evaluation due to cognitive symptoms who were examined between February 2020 and January 2024 in Sweden. The biomarker cutoff values had been established in an independent cohort and were applied to a primary care cohort (n = 307) and a secondary care cohort (n = 300); 1 plasma sample per patient was analyzed as part of a single batch for each cohort. The blood test was then evaluated prospectively in the primary care cohort (n = 208) and in the secondary care cohort (n = 398); 1 plasma sample per patient was sent for analysis within 2 weeks of collection.ExposureBlood tests based on plasma analyses by mass spectrometry to determine the ratio of plasma phosphorylated tau 217 (p-tau217) to non–p-tau217 (expressed as percentage of p-tau217) alone and when combined with the amyloid-β 42 and amyloid-β 40 (Aβ42:Aβ40) plasma ratio (the amyloid probability score 2 [APS2]).Main Outcomes and MeasuresThe primary outcome was AD pathology (determined by abnormal cerebrospinal fluid Aβ42:Aβ40 ratio and p-tau217). The secondary outcome was clinical AD. The positive predictive value (PPV), negative predictive value (NPV), diagnostic accuracy, and area under the curve (AUC) values were calculated.ResultsThe mean age was 74.2 years (SD, 8.3 years), 48% were women, 23% had subjective cognitive decline, 44% had mild cognitive impairment, and 33% had dementia. In both the primary care and secondary care assessments, 50% of patients had AD pathology. When the plasma samples were analyzed in a single batch in the primary care cohort, the AUC was 0.97 (95% CI, 0.95-0.99) when the APS2 was used, the PPV was 91% (95% CI, 87%-96%), and the NPV was 92% (95% CI, 87%-96%); in the secondary care cohort, the AUC was 0.96 (95% CI, 0.94-0.98) when the APS2 was used, the PPV was 88% (95% CI, 83%-93%), and the NPV was 87% (95% CI, 82%-93%). When the plasma samples were analyzed prospectively (biweekly) in the primary care cohort, the AUC was 0.96 (95% CI, 0.94-0.98) when the APS2 was used, the PPV was 88% (95% CI, 81%-94%), and the NPV was 90% (95% CI, 84%-96%); in the secondary care cohort, the AUC was 0.97 (95% CI, 0.95-0.98) when the APS2 was used, the PPV was 91% (95% CI, 87%-95%), and the NPV was 91% (95% CI, 87%-95%). The diagnostic accuracy was high in the 4 cohorts (range, 88%-92%). Primary care physicians had a diagnostic accuracy of 61% (95% CI, 53%-69%) for identifying clinical AD after clinical examination, cognitive testing, and a computed tomographic scan vs 91% (95% CI, 86%-96%) using the APS2. Dementia specialists had a diagnostic accuracy of 73% (95% CI, 68%-79%) vs 91% (95% CI, 88%-95%) using the APS2. In the overall population, the diagnostic accuracy using the APS2 (90% [95% CI, 88%-92%]) was not different from the diagnostic accuracy using the percentage of p-tau217 alone (90% [95% CI, 88%-91%]).Conclusions and RelevanceThe APS2 and percentage of p-tau217 alone had high diagnostic accuracy for identifying AD among individuals with cognitive symptoms in primary and secondary care using predefined cutoff values. Future studies should evaluate how the use of blood tests for these biomarkers influences clinical care.

More than 16 million Americans living with cognitive impairment warrant a diagnostic evaluation to determine the cause of this disorder. The recent availability of disease-modifying therapies for Alzheimer's disease (AD) is expected to significantly drive demand for such diagnostic testing. Accurate, accessible, and affordable methods are needed. Blood biomarkers (BBMs) offer advantages over usual care amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in these regards. This study used a budget impact model to assess the economic utility of the PrecivityAD® blood test, a clinically validated BBM test for the evaluation of brain amyloid, a pathological hallmark of AD. The model compared 2 scenarios: (1) baseline testing involving usual care practice, and (2) early use of a BBM test before usual care CSF and PET biomarker use. At a modest 40% adoption rate, the BBM test scenario had comparable sensitivity and specificity to the usual care scenario and showed net savings in the diagnostic work-up of $3.57 million or $0.30 per member per month in a 1 million member population, translating to over $1B when extrapolated to the US population as a whole and representing a 11.4% cost reduction. Savings were driven by reductions in the frequency and need for CSF and PET testing. Additionally, BBM testing was associated with a cost savings of $643 per AD case identified. Use of the PrecivityAD blood test in the clinical care pathway may prevent unnecessary testing, provide cost savings, and reduce the burden on both patients and health plans.

Diagnosing Alzheimer's disease (AD) poses significant challenges to health care, often resulting in delayed or inadequate patient care. The clinical integration of blood-based biomarkers (BBMs) for AD holds promise in enabling early detection of pathology and timely intervention. However, several critical considerations, such as the lack of consistent guidelines for assessing cognition, limited understanding of BBM test characteristics, insufficient evidence on BBM performance across diverse populations, and the ethical management of test results, must be addressed for widespread clinical implementation of BBMs in the United States. The Global CEO Initiative on Alzheimer's Disease BBM Workgroup convened to address these challenges and provide recommendations that underscore the importance of evidence-based guidelines, improved training for health-care professionals, patient empowerment through informed decision making, and the necessity of community-based studies to understand BBM performance in real-world populations. Multi-stakeholder engagement is essential to implement these recommendations and ensure credible guidance and education are accessible to all stakeholders.

Abstract Recent studies have shown that commercially available, high-performing blood biomarkers (BBMs) for Alzheimer’s disease (AD) pathology represent accurate, accessible, acceptable, and equitable tools to aid health care providers (HCPs) in the evaluation of their patients with signs or symptoms of mild cognitive impairment (MCI) or dementia. However, implementation of AD BBM tests into the clinical care pathway has not been extensively evaluated. The objective of this study was to assess the incorporation of the multi-analyte blood biomarker PrecivityAD2™ test (C2N Diagnostics, LLC, St. Louis, MO) into the clinical workflow of specialty clinics. A total of 203 patients (average age 74 years) evaluated by 12 HCPs (neurologists, geriatricians, geriatric psychiatrists, and others) representing 8 outpatient sites were included as part of the real-world QUIP II Study (NCT06025877). A five-item, end-of-study survey was developed and conducted using The Technology Acceptance Model (David, 1989) and included two constructs: perceived usefulness and perceived ease of use of this BBM test. HCP-reported acceptance scores averaged 9.6 (median 10, range 7-10): contribution to clinical decision-making and ease of understanding test results received the highest ratings. The net promoter score was 75, above the benchmark of 50 associated with excellent customer satisfaction (Qualtrics, 2024). Given recent guidelines and workshop recommendations highlighting the use of AD BBM tests in clinical care, we believe these survey data provide evidence of robust usefulness and acceptance of this BBM test, supporting its incorporation into the clinical care pathway to help HCPs rule in and rule out AD in cognitively symptomatic patients.

BACKGROUND:With the availability of disease-modifying therapies for Alzheimer's disease (AD), it is important for clinicians to have tests to aid in AD diagnosis, especially when the presence of amyloid pathology is a criterion for receiving treatment. METHODS:High-throughput, mass spectrometry-based assays were used to measure %p-tau217 and amyloid beta (Aβ)42/40 ratio in blood samples from 583 individuals with suspected AD (53% positron emission tomography [PET] positive by Centiloid > 25). An algorithm (PrecivityAD2 test) was developed using these plasma biomarkers to identify brain amyloidosis by PET. RESULTS:The area under the receiver operating characteristic curve (AUC-ROC) for %p-tau217 (0.94) was statistically significantly higher than that for p-tau217 concentration (0.91). The AUC-ROC for the PrecivityAD2 test output, the Amyloid Probability Score 2, was 0.94, yielding 88% agreement with amyloid PET. Diagnostic performance of the APS2 was similar by ethnicity, sex, age, and apoE4 status. DISCUSSION:The PrecivityAD2 blood test showed strong clinical validity, with excellent agreement with brain amyloidosis by PET.

Blood-based biomarkers (BBM) for Alzheimer's disease (AD) are being increasingly used in clinical practice to support an AD diagnosis. In contrast to traditional diagnostic modalities, such as amyloid positron emission tomography and cerebrospinal fluid biomarkers, BBMs offer a more accessible and lower cost alternative for AD biomarker testing. Their unique scalability addresses the anticipated surge in demand for biomarker testing with the emergence of disease-modifying treatments (DMTs) that require confirmation of amyloid pathology. To facilitate the uptake of BBMs in clinical practice, The Global CEO Initiative on Alzheimer's Disease convened a BBM Workgroup to provide recommendations for two clinical implementational pathways for BBMs: one for current use for triaging and another for future use to confirm amyloid pathology. These pathways provide a standardized diagnostic approach with guidance on interpreting BBM test results. Integrating BBMs into clinical practice will simplify the diagnostic process and facilitate timely access to DMTs for eligible patients.

Abstract Objective The objective of this study was to examine clinicians' patient selection and result interpretation of a clinically validated mass spectrometry test measuring amyloid beta and ApoE blood biomarkers combined with patient age (PrecivityAD® blood test) in symptomatic patients evaluated for Alzheimer's disease (AD) or other causes of cognitive decline. Methods The Quality Improvement and Clinical Utility PrecivityAD Clinician Survey (QUIP I, ClinicalTrials.gov Identifier: NCT05477056) was a prospective, single‐arm cohort study among 366 patients evaluated by neurologists and other cognitive specialists. Participants underwent blood biomarker testing and received an amyloid probability score (APS), indicating the likelihood of a positive result on an amyloid positron emission tomography (PET) scan. The primary study outcomes were appropriateness of patient selection as well as result interpretation associated with PrecivityAD blood testing. Results A 95% (347/366) concordance rate was noted between clinicians' patient selection and the test's intended use criteria. In the final analysis including these 347 patients (median age 75 years, 56% women), prespecified test result categories incorporated 133 (38%) low APS, 162 (47%) high APS, and 52 (15%) intermediate APS patients. Clinicians' pretest and posttest AD diagnosis probability changed from 58% to 23% in low APS patients and 71% to 89% in high APS patients (p < 0.0001). Anti‐AD drug therapy decreased by 46% in low APS patients (p < 0.0001) and increased by 57% in high APS patients (p < 0.0001). Interpretation These findings demonstrate the clinical utility of the PrecivityAD blood test in clinical care and may have added relevance as new AD therapies are introduced.

Abstract The QUIP I Study (ClinicalTrials.gov Identifier: NCT05477056) was a prospective, single-arm study which included 347 older persons (average age 74, 56% women) presenting with signs and symptoms of cognitive impairment. In a subgroup analysis, we measured the effect of a person’s age and sex on clinical decision making around the PrecivityAD® blood biomarker (BBM) test result. The test result was reported as the Amyloid Probability Score (APS), which measures the likelihood of a positive result on an amyloid PET scan. Clinical decision making was recorded by clinician survey pre- and post-BBM testing. Clinician-reported probability of Alzheimer’s disease (“AD”) changed pre-test to post-test from 58% to 23% (Low APS group) and from 71% to 89% (High APS group) (p < 0.0001 for all APS groups). The relationships between APS and change in diagnostic certainty were not significantly different as analyzed by age (p=0.344 for Low APS, p=0.292 for High APS) or sex (p=0.167 for Low APS, p=0.213 for High APS). Overall use of AD drug therapy decreased from 48% to 26% (Low APS group) and increased from 56% to 88% (High APS group) (p < 0.0001 for all APS groups). The relationships between APS and change in medication prescribing were not significantly different as analyzed by age (p=0.4534 for Low APS, p=0.9939 for High APS) or sex (p=1 for Low APS, p=0.931 for High APS). We believe that the current study results help to underscore the usefulness and generalizability of this BBM among older adults in clinical care pathways.

Introduction: We have previously shown that combining a polygenic risk score (PRS) for cardiovascular disease (CVD), with standard clinical risk calculators such as QRISK®2, results in improved CVD risk prediction via an integrated risk tool (CVD-IRT). Research Question: The objective of this study was to explore the implementation of CVD-IRT within routine practice in the UK National Health Service (NHS), through participant and healthcare provider (HCP) surveys and interviews. Methods: The Healthcare Evaluation of Absolute Risk Testing Study (HEART) (NCT05294419), a prospective, single-arm pragmatic trial, enrolled 836 participants undergoing health checks across 12 NHS general practices. QRISK2 and CVD-IRT scores were returned to participants via HCPs. The primary outcome of the study was feasibility of CVD-IRT implementation. This was assessed by a mixed methods approach (quantitative and qualitative methods). Results: After the results were reported and discussed, 520 surveys were completed by participants and 824 surveys were completed by HCPs. Subsequently, 21 participants were interviewed and 13 HCPs attended focus groups or interviews to explore their experiences. 23 HCPs completed a final questionnaire (34.8% physician, 21.7% research nurse, 43.5% other). For 90.7% of reports, HCPs indicated that the CVD-IRT could be incorporated into routine primary care in a straightforward manner. 80% of HCPs agreed that having these tests could lead to better health outcomes for patients, and 68.4% believed that the CVD-IRT could help them manage their patients through a shared decision making process covering lifestyle and treatment options. Participants found the report personally useful (98.5%) and easy to understand (94.3%); agreed that genetic measures are important to identify the risks of developing CVD (85.2%); thought that the test should be widely made available (interview summaries); and would recommend to friends and family (86.8%). Conclusion: The implementation of the CVD-IRT into routine health-checks was recommendable, feasible and well received by both HCPs and participants, who felt that the information was useful, could support clinical decisions, and easy to understand.

Early identification of Alzheimer’s disease (AD) is critical for disease-modifying therapies. The Davos Alzheimer’s Collaborative flagship program tested the feasibility of implementing a digital cognitive assessment (DCA) followed by a blood biomarker (BBM) for early detection of cognitive impairment (CI). Individuals ≥65 years without dementia were approached via their primary care provider (PCP) or through direct-to-consumer (DTC) social media. After consenting, participants completed the Cogstate Brief Battery (CBB) DCA. Participants with an abnormal or borderline CBB score were offered the Montreal Cognitive Assessment (MoCA) and the PrecivityAD® blood test, a CLIA-certified laboratory developed test that uses mass spectrometry to analyze biomarkers to identify brain amyloid plaques (reported by the Amyloid Probability Score-APS) in individuals with CI. Over 2300 participants expressed interest. Of 2001 eligible, 1076 (96% social media, 4% PCP) e-consented. 742 completed the CBB of which 211 (28%) were borderline, 113 (15%) abnormal, and 418 (56%) were negative for CI. Of the 324 with borderline or abnormal CBB scores, 219 (67%) completed the MoCA (59% Normal range, 38% Mild CI range, 2% Moderate CI range, and 0.5% Severe CI range). Of the 324, 218 (67%) received BBM: 18.8% had High APS, 67.9% Low APS, and 13.3% Intermediate (e.g. non-informative) APS. The APS result for participants with a normal MoCA showed 20% with High APS, 12% with an Intermediate APS, and 69% with Low APS. Of those with an impaired MoCA 18% had High APS, 15% Intermediate and 67% low APS. A Fisher’s Exact test determined there was no statistically significant relationship between MoCA impairment and APS category (p-value 0.68). This study highlights the success of a DTC approach. The MoCA, alone, is insufficient to identify risk of AD in individuals with CI. A more comprehensive clinical evaluation of AD can be enhanced with the addition of a BBM leading to better disease-modifying strategies.

Introduction: We have previously shown that combining a polygenic risk score (PRS) for cardiovascular disease (CVD), a numerical summary of an individual’s genetic predisposition to CVD, with standard clinical risk calculators such as ASCVD-PCE and QRISK results in improved estimates of CVD risk. Implementation of such a cardiovascular integrated risk tool (CVD IRT) into real world clinical practice is a key focus for further study. Hypothesis: We assessed the hypothesis that a CVD IRT can be incorporated into routine primary care. Methods: The Healthcare Evaluation of Absolute Risk Testing Study (NCT05294419) is a prospective trial recruiting up to 1,000 healthy participants undergoing health checks across 12 UK NHS general practices. Both QRISK2 and CVD IRT scores were generated and returned to clinicians, who then communicated the results to participants. The primary outcome of this study is operational success as well as feedback from health care providers (HCPs) and participants. The study also measures the impact of the CVD IRT on clinical decision making. Results: These are interim analyses. As of April 2022, 624 eligible participants (62% female, mean age 55) have been recruited. A total of 371 CVD IRT reports have been generated, with 100% of blood samples generating scores that were all returned within the designated time frame. Among the primary care HCPs, 89% (8/9) agreed that the incorporation of CVD IRT into routine care could be done in a straightforward manner. Among the participants who have completed a survey to date, 93% (125/135) would likely or very likely recommend the CVD IRT to friends and family. Average QRISK2 (6.3%) and CVD IRT (6.6%) risk scores did not differ significantly, but there were broad changes in risk among individual patients, with 5% (19/371) of patients crossing above the risk threshold to treat according to NICE guidelines (10-year risk ≥ 10%) as well as 3% (11/371) of patients reclassified as very high risk (10-year risk ≥ 20%). Conclusions: The rollout of an integrated risk tool combining polygenic risk into a standardized CVD risk calculator within primary care is feasible and well accepted by clinicians and participants. The CVD IRT results suggest clinically actionable changes in a substantial proportion of this population.