Racial and ethnic differences in plasma biomarker eligibility for a preclinical Alzheimer's disease trial.

INTRODUCTION: In trials of amyloid-lowering drugs for Alzheimer's disease (AD), differential eligibility may contribute to under-inclusion of racial and ethnic underrepresented groups. We examined plasma amyloid beta 42/40 and positron emission tomography (PET) amyloid eligibility for the ongoing AHEAD Study preclinical AD program (NCT04468659). METHODS: Univariate logistic regression models were used to examine group differences in plasma and PET amyloid screening eligibility. RESULTS: Of 4905 participants screened at time of analysis, 1724 were plasma eligible to continue in screening: 13.3% Hispanic Black, 24.7% Hispanic White, 20.8% non-Hispanic (NH) Asian, 24.7% NH Black, and 38.9% NH White. Plasma eligibility differed across groups in models controlling for covariates (odds ratio from 1.9 to 4.0 compared to the NH White reference group, P < 0.001). Among plasma eligible participants, PET eligibility did not differ by group. DISCUSSION: These results suggest that prevalence of brain amyloid pathology differed, but that eligibility based on plasma was equally effective across racial and ethnic group members. HIGHLIGHTS: Plasma amyloid eligibility is lower in underrepresented racial and ethnic groups. In plasma eligible adults, positron emission tomography eligibility rates are similar across race and ethnicity. Plasma biomarker tests may be similarly effective across racial and ethnic groups.

Plasma Aß42/Aß40 and phospho-tau217 concentration ratios increase the accuracy of amyloid PET classification in preclinical Alzheimer's disease.

INTRODUCTION: Incorporating blood-based Alzheimer's disease biomarkers such as tau and amyloid beta (Aß) into screening algorithms may improve screening efficiency. METHODS: Plasma Aß, phosphorylated tau (p-tau)181, and p-tau217 concentration levels from AHEAD 3-45 study participants were measured using mass spectrometry. Tau concentration ratios for each proteoform were calculated to normalize for inter-individual differences. Receiver operating characteristic (ROC) curve analysis was performed for each biomarker against amyloid positivity, defined by > 20 Centiloids. Mixture of experts analysis assessed the value of including tau concentration ratios into the existing predictive algorithm for amyloid positron emission tomography status. RESULTS: The area under the receiver operating curve (AUC) was 0.87 for Aß42/Aß40, 0.74 for phosphorylated variant p-tau181 ratio (p-tau181/np-tau181), and 0.92 for phosphorylated variant p-tau217 ratio (p-tau217/np-tau217). The Plasma Predicted Centiloid (PPC), a predictive model including p-tau217/np-tau217, Aß42/Aß40, age, and apolipoprotein E improved AUC to 0.95. DISCUSSION: Including plasma p-tau217/np-tau217 along with Aß42/Aß40 in predictive algorithms may streamline screening preclinical individuals into anti-amyloid clinical trials. CLINICALTRIALS: gov Identifier: NCT04468659 HIGHLIGHTS: The addition of plasma phosphorylated variant p-tau217 ratio (p-tau217/np-tau217) significantly improved plasma biomarker algorithms for identifying preclinical amyloid positron emission tomography positivity. Prediction performance at higher NAV Centiloid levels was improved with p-tau217/np-tau217. All models generated for this study are incorporated into the Plasma Predicted Centiloid (PPC) app for public use.

Natural cubic splines for the analysis of Alzheimer's clinical trials.

Mixed model repeated measures (MMRM) is the most common analysis approach used in clinical trials for Alzheimer's disease and other progressive diseases measured with continuous outcomes over time. The model treats time as a categorical variable, which allows an unconstrained estimate of the mean for each study visit in each randomized group. Categorizing time in this way can be problematic when assessments occur off-schedule, as including off-schedule visits can induce bias, and excluding them ignores valuable information and violates the intention to treat principle. This problem has been exacerbated by clinical trial visits which have been delayed due to the COVID19 pandemic. As an alternative to MMRM, we propose a constrained longitudinal data analysis with natural cubic splines that treats time as continuous and uses test version effects to model the mean over time. Compared to categorical-time models like MMRM and models that assume a proportional treatment effect, the spline model is shown to be more parsimonious and precise in real clinical trial datasets, and has better power and Type I error in a variety of simulation scenarios.

Evaluation of Blood-Based Plasma Biomarkers as Potential Markers of Amyloid Burden in Preclinical Alzheimer's Disease.

BACKGROUND: Participant eligibility for the A4 Study was determined by amyloid PET imaging. Given the disadvantages of amyloid PET imaging in accessibility and cost, blood-based biomarkers may serve as a sufficient biomarker and more cost-effective screening tool for patient enrollment into preclinical AD trials. OBJECTIVE: To determine if a blood-based screening test can adequately identify amyloid burden in participants screened into a preclinical AD trial. METHODS: In this cross-sectional study, 224 participants from the A4 Study received an amyloid PET scan (18Florbetapir) within 90 days of blood sample collection. Blood samples from all study participants were processed within 2 h after phlebotomy. Plasma amyloid measures were quantified by Shimazdu and C2 N Diagnostics using mass spectrometry-based platforms. A corresponding subset of blood samples (n = 100) was processed within 24 h after phlebotomy and analyzed by C2 N. RESULTS: Plasma Aß42/Aß40 demonstrated the highest association for Aß accumulation in the brain with an AUC 0.76 (95%CI = 0.69, 0.82) at C2 N and 0.80 (95%CI = 0.75, 0.86) at Shimadzu. Blood samples processed to plasma within 2 h after phlebotomy provided a better prediction of amyloid PET status than blood samples processed within 24 h (AUC 0.80 versus 0.64; p < 0.001). Age, sex, and APOE ɛ4 carrier status did not the diagnostic performance of plasma Aß42/Aß40 to predict amyloid PET positivity in A4 Study participants. CONCLUSION: Plasma Aß42/Aß40 may serve as a potential biomarker for predicting elevated amyloid in the brain. Utilizing blood testing over PET imaging may improve screening efficiency into clinical trials.

Associations between statins and adverse events in primary prevention of cardiovascular disease: systematic review with pairwise, network, and dose-response meta-analyses.

OBJECTIVE: To assess the associations between statins and adverse events in primary prevention of cardiovascular disease and to examine how the associations vary by type and dosage of statins. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Studies were identified from previous systematic reviews and searched in Medline, Embase, and the Cochrane Central Register of Controlled Trials, up to August 2020. REVIEW METHODS: Randomised controlled trials in adults without a history of cardiovascular disease that compared statins with non-statin controls or compared different types or dosages of statins were included. MAIN OUTCOME MEASURES: Primary outcomes were common adverse events: self-reported muscle symptoms, clinically confirmed muscle disorders, liver dysfunction, renal insufficiency, diabetes, and eye conditions. Secondary outcomes included myocardial infarction, stroke, and death from cardiovascular disease as measures of efficacy. DATA SYNTHESIS: A pairwise meta-analysis was conducted to calculate odds ratios and 95% confidence intervals for each outcome between statins and non-statin controls, and the absolute risk difference in the number of events per 10 000 patients treated for a year was estimated. A network meta-analysis was performed to compare the adverse effects of different types of statins. An Emax model based meta-analysis was used to examine the dose-response relationships of the adverse effects of each statin. RESULTS: 62 trials were included, with 120 456 participants followed up for an average of 3.9 years. Statins were associated with an increased risk of self-reported muscle symptoms (21 trials, odds ratio 1.06 (95% confidence interval 1.01 to 1.13); absolute risk difference 15 (95% confidence interval 1 to 29)), liver dysfunction (21 trials, odds ratio 1.33 (1.12 to 1.58); absolute risk difference 8 (3 to 14)), renal insufficiency (eight trials, odds ratio 1.14 (1.01 to 1.28); absolute risk difference 12 (1 to 24)), and eye conditions (six trials, odds ratio 1.23 (1.04 to 1.47); absolute risk difference 14 (2 to 29)) but were not associated with clinically confirmed muscle disorders or diabetes. The increased risks did not outweigh the reduction in the risk of major cardiovascular events. Atorvastatin, lovastatin, and rosuvastatin were individually associated with some adverse events, but few significant differences were found between types of statins. An Emax dose-response relationship was identified for the effect of atorvastatin on liver dysfunction, but the dose-response relationships for the other statins and adverse effects were inconclusive. CONCLUSIONS: For primary prevention of cardiovascular disease, the risk of adverse events attributable to statins was low and did not outweigh their efficacy in preventing cardiovascular disease, suggesting that the benefit-to-harm balance of statins is generally favourable. Evidence to support tailoring the type or dosage of statins to account for safety concerns before starting treatment was limited. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020169955.

Disparities by Race and Ethnicity Among Adults Recruited for a Preclinical Alzheimer Disease Trial.

Importance: Underrepresentation of many racial/ethnic groups in Alzheimer disease (AD) clinical trials limits generalizability of results and hinders opportunities to examine potential effect modification of candidate treatments. Objective: To examine racial and ethnic differences in recruitment methods and trial eligibility in a multisite preclinical AD trial. Design, Setting, and Participants: This cross-sectional study analyzed screening data from the Anti-Amyloid in Asymptomatic AD study, collected from April 2014 to December 2017. Participants were categorized into 5 mutually exclusive ethnic/racial groups (ie, Hispanic, Black, White, Asian, and other) using participant self-report. Data were analyzed from May through December 2020 and included 5945 cognitively unimpaired older adults between the ages of 65 and 85 years screened at North American study sites. Main Outcomes and Measures: Primary outcomes included recruitment sources, study eligibility, and ineligibility reasons. To assess the probability of trial eligibility, regression analyses were performed for the likelihood of being eligible after the first screening visit involving clinical and cognitive assessments. Results: Screening data were included for 5945 participants at North American sites (mean [SD] age, 71.7 [4.9] years; 3524 women [59.3%]; 5107 White [85.9%], 323 Black [5.4%], 261 Hispanic [4.4%], 112 Asian [1.9%], and 142 [2.4%] who reported race or ethnicity as other). Recruitment sources differed by race and ethnicity. While White participants were recruited through a variety of sources, site local recruitment efforts resulted in the majority of Black (218 [69.2%]), Hispanic (154 [59.7%]), and Asian (61 [55.5%]) participants. Participants from underrepresented groups had lower mean years of education (eg, mean [SD] years: Hispanic participants, 15.5 [3.2] years vs White participants, 16.7 [2.8] years) and more frequently were women (226 [70.0%] Black participants vs 1364 [58.5%] White participants), were unmarried (184 [56.9%] Black participants vs 1364 [26.7%] White participants), and had nonspousal study partners (237 [73.4%] Black participants vs 2147 [42.0%] White participants). They were more frequently excluded for failure to meet cognitive inclusion criteria (eg, screen failures by specific inclusion criteria: 147 [45.5%] Black participants vs 1338 [26.2%] White participants). Compared with White participants, Black (odds ratio [OR], 0.43; 95% CI, 0.34-0.54; P < .001), Hispanic (OR, 0.53; 95% CI, 0.41-0.69; P < .001), and Asian participants (OR, 0.56; 95% CI, 0.38-0.82; P = .003) were less likely to be eligible after screening visit 1. Conclusions and Relevance: Racial/ethnic groups differed in sources of recruitment, reasons for screen failure, and overall probability of eligibility in a preclinical AD trial. These results highlight the need for improved recruitment strategies and careful consideration of eligibility criteria when planning preclinical AD clinical trials.

Predicting amyloid risk by machine learning algorithms based on the A4 screen data: Application to the Japanese Trial-Ready Cohort study.

BACKGROUND: Selecting cognitively normal elderly individuals with higher risk of brain amyloid deposition is critical to the success of prevention trials for Alzheimer's disease (AD). METHODS: Based on the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease study data, we built machine-learning models and applied them to our ongoing Japanese Trial-Ready Cohort (J-TRC) webstudy participants registered within the first 9 months (n = 3081) of launch to predict standard uptake value ratio (SUVr) of amyloid positron emission tomography. RESULTS: Age, family history, online Cognitive Function Instrument and CogState scores were important predictors. In a subgroup of J-TRC webstudy participants with known amyloid status (n = 37), the predicted SUVr corresponded well with the self-reported amyloid test results (area under the curve = 0.806 [0.619-0.992]). DISCUSSION: Our algorithms may be usable for automatic prioritization of candidate participants with higher amyloid risks to be preferentially recruited from the J-TRC webstudy to in-person study, maximizing efficiency for the identification of preclinical AD participants.

Instrumental activities of daily living, amyloid, and cognition in cognitively normal older adults screening for the A4 Study.

INTRODUCTION: We examined the associations among instrumental activities of daily living (IADL), cortical amyloid, and cognition in cognitively normal (CN) older adults. METHODS: CN participants screening for the A4 Study (n = 4486) underwent florbetapir (amyloid) positron emission tomography. IADL were assessed using the Alzheimer's Disease Cooperative Study Activities of Daily Living Prevention Instrument. Separate logistic regression models were run with cortical amyloid or cognition as independent variable and IADL as dependent variable, adjusting for age and sex. RESULTS: IADL difficulties were endorsed infrequently (≤16%). Overall IADL and four select IADL item difficulties ("remembering appointments," "finding belongings," "following TV programs," and "remembering current events") reported by both participant and study partner were significantly associated with greater amyloid burden and worse cognition. DISCUSSION: Although IADL deficits were infrequent in this CN cohort, greater participant and study partner report of overall IADL deficits and subtle difficulties in specific IADL items were associated with mildly higher amyloid burden and worse cognition.

Methods for meta-analysis of pharmacodynamic dose-response data with application to multi-arm studies of alogliptin.

Standard methods for meta-analysis of dose-response data in epidemiology assume a model with a single scalar parameter, such as log-linear relationships between exposure and outcome; such models are implicitly unbounded. In contrast, in pharmacology, multi-parameter models, such as the widely used Emax model, are used to describe relationships that are bounded above and below. We propose methods for estimating the parameters of a dose-response model by meta-analysis of summary data from the results of randomized controlled trials of a drug, in which each trial uses multiple doses of the drug of interest (possibly including dose 0 or placebo). We assume that, for each randomized arm of each trial, the mean and standard error of a continuous response measure and the corresponding allocated dose are available. We consider weighted least squares fitting of the model to the mean and dose pairs from all arms of all studies, and a two-stage procedure in which scalar inverse-variance meta-analysis is performed at each dose, and the dose-response model is fitted to the results by weighted least squares. We then compare these with two further methods inspired by network meta-analysis that fit the model to the contrasts between doses. We illustrate the methods by estimating the parameters of the Emax model to a collection of multi-arm, multiple-dose, randomized controlled trials of alogliptin, a drug for the management of diabetes mellitus, and further examine the properties of the four methods with sensitivity analyses and a simulation study. We find that all four methods produce broadly comparable point estimates for the parameters of most interest, but a single-stage method based on contrasts between doses produces the most appropriate confidence intervals. Although simpler methods may have pragmatic advantages, such as the use of standard software for scalar meta-analysis, more sophisticated methods are nevertheless preferable for their advantages in estimation.

A randomised controlled trial of time-limited individual placement and support: IPS-LITE trial.

BACKGROUND: Individual placement and support (IPS) has been repeatedly demonstrated to be the most effective form of mental health vocational rehabilitation. Its no-discharge policy plus fixed caseloads, however, makes it expensive to provide. AIMS: To test whether introducing a time limit for IPS would significantly alter its clinical effectiveness and consequently its potential cost-effectiveness. METHOD: Referrals to an IPS service were randomly allocated to either standard IPS or to time-limited IPS (IPS-LITE). IPS-LITE participants were referred back to their mental health teams if still unemployed at 9 months or after 4 months employment support. The primary outcome at 18 months was working for 1 day. Secondary outcomes comprised other vocational measures plus clinical and social functioning. The differential rates of discharge were used to calculate a notional increased capacity and to model potential rates and costs of employment. RESULTS: A total of 123 patients were randomised and data were collected on 120 patients at 18 months. The two groups (IPS-LITE = 62 and IPS = 61) were well matched at baseline. Rates of employment were equal at 18 months (IPS-LITE = 24 (41%) and IPS = 27 (46%)) at which time 57 (97%) had been discharged from the IPS-LITE service and 16 (28%) from IPS. Only 11 patients (4 IPS-LITE and 7 IPS) obtained their first employment after 9 months. There were no significant differences in any other outcomes. IPS-LITE discharges generated a potential capacity increase of 46.5% compared to 12.7% in IPS which would translate into 35.8 returns to work in IPS-LITE compared to 30.6 in IPS over an 18-month period if the rates remained constant. CONCLUSIONS: IPS-LITE is equally effective to IPS and only minimal extra employment is gained by persisting beyond 9 months. If released capacity is utilised with similar outcomes, IPS-LITE results in an increase by 17% in numbers gaining employment within 18 months compared to IPS and will increase with prolonged follow-up. IPS-LITE may be more cost-effective and should be actively considered as an alternative within public services.