Post-disclosure distress among racial and ethnic groups in a preclinical AD trial

INTRODUCTION

Trialists need a thorough understanding of whether reactions to Alzheimer's disease (AD) biomarker information differ among racial and ethnic groups in preclinical AD trials.

METHODS

We used data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease Study to analyze cognitively unimpaired participants' responses on the Impact of Event Scale (IES) 24 to 72 hours after amyloid disclosure. We fit a linear regression model to test whether mean IES scores differed among participants from specific racial and ethnic groups. We considered potential effect modification by amyloid status.

RESULTS

Reactions to disclosure did not significantly differ among participant groups based on self-reported race and ethnicity. Although the results were not significant when stratified by amyloid status, all racial and ethnic groups except for participants self-reporting Hispanic/Latino ethnicity were observed to have higher mean IES in the elevated amyloid group.

DISCUSSION

These results support continued use of current disclosure methods in preclinical AD trials.

Retention of American Indian and Alaska Native participants in the National Alzheimer's Coordinating Center Uniform Data Set

INTRODUCTION

The number of American Indian and Alaska Native (AI/AN) elders is expected to double by 2060. Thus it is imperative to retain AI/AN participants in longitudinal research studies to identify novel risk factors and potential targets for intervention for Alzheimer's disease and related dementias in these communities.

METHODS

The National Alzheimer's Coordinating Center houses uniformly collected longitudinal data from the network of National Institute on Aging (NIA)-funded Alzheimer's Disease Research Centers (ADRCs). We used logistic regression to quantify participant retention at 43 ADRCs, comparing self-identified AI/AN participants to non-Hispanic White (NHW) participants, adjusting for potential confounding factors including baseline diagnosis, age, sex, education, and smoking.

RESULTS

The odds of AI/AN participant retention at the first follow-up visit were significantly lower than those for NHW participants (adjusted odds ratio [aOR]: 0.599; 95%: 0.46-0.78; p < 0.001).

DISCUSSION

These results suggest the need for improved strategies to retain AI/AN participants, perhaps including improved researcher-community relationships and community engagement and education.

HIGHLIGHTS

American Indian and Alaska Native (AI/AN) research participants were retained to the first follow-up appointment at lower rates than non-Hispanic White (NHW) participants. AI/AN participants are retained at lower rates than NHW participants for long-term follow-up. The majority of AI/AN participants were not retained to the second follow-up visit.

Alzheimer's Disease Biomarker Decision-Making among Patients with Mild Cognitive Impairment and Their Care Partners

BACKGROUND

Alzheimer's disease (AD) biomarker tests can be ordered as part of the diagnostic workup of patients with mild cognitive impairment (MCI). Little is known about how patients with MCI and their care partners decide whether to pursue testing.

OBJECTIVE

To examine factors that influence AD biomarker testing decisions among patients with MCI and their care partners.

DESIGN

We performed structured research interviews with patients with MCI and their study partners to assess the importance of eight factors in the decision whether to undergo AD biomarker testing (6-point Likert scale; 1-extremely unimportant to 6-extremely important): cost, fear of testing procedures, learning if AD is the cause of cognitive problems, concern about health insurance, instructing future planning, informing treatment decisions, family members' opinions, and doctor recommendation.

SETTING

Two researchers administered interviews with participants in-person (i.e., participant home, research center) or remotely (i.e., telephone, video-conference).

PARTICIPANTS

We completed interviews with 65 patients with a diagnosis of MCI and 57 study partners, referred by dementia specialist clinicians from the University of California, Irvine health system.

MEASUREMENTS

We used generalized estimating equations (GEE) to examine the mean importance of each factor among patients and study partners, and the mean difference in importance of each factor within dyads.

RESULTS

One third of participants reported the patient had previously undergone AD biomarker testing. Fifty-five percent of patients and 65% of study partners who reported no previous testing indicated a desire for the patient to be tested. GEE analyses found that patients and study partners rated the following factors with highest importance: informing treatment decisions (mean score 5.29, 95% CI: 5.06, 5.52 for patients; mean score 5.56, 95% CI: 5.41, 5.72 for partners); doctor recommendation (4.94, 95% CI: 4.73, 5.15 for patients; 5.16, 95% CI: 4.97, 5.34 for partners); and instructing future planning (4.88, 95% CI: 4.59, 5.16 for patients; 5.11, 95% CI: 4.86, 5.35 for partners). High dyadic agreement was observed for all factors except fear of testing, which patients rated with lower importance than their study partners.

CONCLUSIONS

Biomarker testing for AD in patients with MCI is a rapidly evolving practice and limited data exist on patient perspectives. In this study, most patients and their care partners were interested in testing to help inform treatment decisions and to plan for the future. Participants placed high importance on clinician recommendations for biomarker testing, highlighting the need for clear communication and education on the options, limitations, risks, and benefits of testing.

Study Partner Type and Adverse Event Reporting in Mild-to-Moderate Alzheimer's Disease Clinical Trials

Background

In randomized clinical trials (RCTs), monitoring adverse events (AEs) and serious AEs (SAEs) is critical. All Alzheimer's disease (AD) RCTs require participants to enroll with a study partner.

Objective

We examined AE reporting rates in mild-to-moderate AD trials and their associations with study partner type.

Methods

We estimated AE reporting rates using placebo data from seven independent RCTs conducted by the Alzheimer's Disease Cooperative Study. We assessed the heterogeneity of reporting rates as a function of visits using generalized estimating equations. In the primary analysis, we tested the hypotheses that the rates of reporting differed by study partner type and time they spent with the participant weekly using Poisson regression with robust variance estimation. In all regression models, log-transformed total patient years was included.

Results

The estimated reporting rates were 2.83 (95% CI: 2.66, 3.02), 1.18 (95% CI: 1.09, 1.28), 0.23 (95% CI: 0.19, 0.27), and 0.28 (95% CI: 0.24, 0.33) events per participant year for grade 1-3 AEs and SAEs, respectively. We estimated that greater number of visits per year was associated with increased reporting for grade 1-2 AEs and SAEs. We did not find evidence to suggest that AE reporting differed by study partner type or by time the study partner spent with the participant.

Conclusions

Study partner type and time the study partner spent with the participant did not appear to impact AE reporting. Estimated reporting rates may be useful to evaluate safety in future studies, particularly those with no control arm and similar visit frequencies.

Estimating attrition in mild-to-moderate Alzheimer's disease and mild cognitive impairment clinical trials

BACKGROUND

Participant retention is a key factor that affects clinical trial integrity. Trial protocols estimate attrition as a function of sample size calculations. Alzheimer's disease (AD) is an area of active treatment development. We aimed to quantify the association between trial duration and completion rates and provide guidance for estimating attrition in AD trial protocols.

METHODS

Using the Alzforum and ClinicalTrials.gov databases, we analyzed retention data from 125 mild-to-moderate AD and 12 mild cognitive impairment (MCI) clinical trials. We compared the rates of completion between trial arms (active vs. control) and ran regression models to test the hypothesis that trials with longer study duration have lower trial completion using all available data and restricting to placebo data. Our primary outcome was the odds of trial completion for a 6-month increase in trial duration. From the regression model, we estimated the proportion of participants completing 6-, 12-, and 18-month trials.

RESULTS

We found that 21 (17%) mild-to-moderate AD trials and 1 (8%) MCI trial demonstrated greater dropout in treatment compared to placebo arms. For every 6-month increase in trial duration, there was a 27% decrease in the odds of trial completion (OR = 0.73; 95% CI 0.66, 0.81; p < 0.001) among participants in mild-to-moderate AD trials and a 55% decrease (OR = 0.45; 95% CI 0.36, 0.57; p < 0.001) among participants in MCI trials. The proportion of participants in the placebo group completing 6-, 12-, and 18-month trials were estimated to be 85.2%, 80.0%, and 73.3% for mild-to-moderate AD trials and 91.9%, 84.2%, and 71.3% for MCI trials, respectively.

CONCLUSIONS

Longer duration trials may be underpowered to demonstrate estimated treatment effects and may suffer from a greater risk of bias than do shorter trials.

Effects of informant replacement in Alzheimer's disease clinical trials

INTRODUCTION

Alzheimer's disease (AD) trials require enrollment with an informant.

METHODS

We assessed relationships between informant replacement and Alzheimer's Disease Cooperative Study Activities of Daily Living (ADCS-ADL) scores across four AD trials. Using generalized estimating equations, we examined associations between replacement and change in ADCS-ADL between successive visits. We used analysis of covariance to estimate the association between replacement and 18-month change from baseline, and an F-test to compare the variance of this change.

RESULTS

Among 1336 participants, 63 (≈5%) experienced replacement. Between-visit mean change in ADCS-ADL was 2.44 points lower comparing replacement to stable informants (95% confidence interval [CI]: -3.91, -0.98). The difference in between-visit mean absolute change was 2.38 points (95% CI: 1.24, 3.52). Replacement was not significantly associated with an 18-month change from baseline. The ratio of variances (replacement/stable) was 1.80 (95% CI: 1.19, 2.99).

DISCUSSION

Informant replacement is associated with bias and increased variability between visits and increased variance for overall ADCS-ADL.

Frameworks for estimating causal effects in observational settings: comparing confounder adjustment and instrumental variables

To estimate causal effects, analysts performing observational studies in health settings utilize several strategies to mitigate bias due to confounding by indication. There are two broad classes of approaches for these purposes: use of confounders and instrumental variables (IVs). Because such approaches are largely characterized by untestable assumptions, analysts must operate under an indefinite paradigm that these methods will work imperfectly. In this tutorial, we formalize a set of general principles and heuristics for estimating causal effects in the two approaches when the assumptions are potentially violated. This crucially requires reframing the process of observational studies as hypothesizing potential scenarios where the estimates from one approach are less inconsistent than the other. While most of our discussion of methodology centers around the linear setting, we touch upon complexities in non-linear settings and flexible procedures such as target minimum loss-based estimation and double machine learning. To demonstrate the application of our principles, we investigate the use of donepezil off-label for mild cognitive impairment. We compare and contrast results from confounder and IV methods, traditional and flexible, within our analysis and to a similar observational study and clinical trial.

Recruitment across two decades of NIH-funded Alzheimer's disease clinical trials

BACKGROUND

Timely accrual of a representative sample is a key factor in whether Alzheimer's disease (AD) clinical trials successfully answer the scientific questions under study. Studies in other fields have observed that, over time, recruitment to trials has become increasingly reliant on larger numbers of sites, with declines in the average per-site recruitment rate. Here, we examined the trends in recruitment over a 20-year period of NIH-funded AD clinical trials conducted by the Alzheimer's Disease Cooperative Study (ADCS), a temporally consistent network of sites devoted to interventional research.

METHODS

We performed retrospective analyses of eleven ADCS randomized clinical trials. To examine the recruitment planning, we calculated the expected number of participants to be enrolled per site for each trial. To examine the actual trial recruitment rates, we quantified the number of participants enrolled per site per month.

RESULTS

No effects of time were observed on recruitment planning or overall recruitment rates across trials. No trial achieved an overall recruitment rate greater than one subject per site per month. We observed the fastest recruitment rates in trials with no competition and the slowest in trials that overlapped in time. The highest recruitment rates were consistently seen early within trials and declined over the course of studies.

CONCLUSIONS

Trial recruitment projections should plan for fewer than one participant randomized per site per month and consider the number of other AD trials being conducted concurrently.

Cohort Effects in Alzheimer's Disease Trials: An Empirical Assessment Utilizing Data from the Alzheimer's Disease Cooperative Study

BACKGROUND

Cohort effects in study populations can impact clinical trial conclusions and generalizability, particularly in trials with planned interim analyses. Long recruitment windows may exacerbate these risks in Alzheimer's disease (AD) trials.

OBJECTIVES

To investigate the presence of cohort effects mild-to-moderate AD trials.

DESIGN

Retrospective analysis using pooled participant-level data from nine randomized, placebo-controlled trials conducted by the Alzheimer's Disease Cooperative Study (ADCS).

SETTING

Trials were multicenter studies conducted by an academic trial network.

PARTICIPANTS

The trials enrolled participants with mild, mild-to-moderate, or moderate AD who were over age 50 and had mini mental state exam scores between 12 and 26. Interventions/Exposure: We defined a participant's site-standardized enrollment time as the number of days between their screening date and the first screening date among randomized participants at their site within their study.

MAIN OUTCOME(S) AND MEASURE(S)

Our primary outcome was the 12-month change in the AD assessment scale - cognitive subscale (ADAS-Cog). Secondary outcomes were participant demographics and time to study discontinuation.

RESULTS

The pooled sample consisted of N=2,754 at baseline with N=2,191 participants completing a 12-month visit. We found no meaningful differences in the distributions of sex, race and ethnicity, age, years of education or baseline ADAS-Cog score across enrollment time. We found a significant association between enrollment time and 12-month change in ADAS-Cog, with participants enrolling 100 days later tending to experience an increase on the ADAS-Cog of 0.16 points greater (reflecting greater cognitive decline; 95% CI: (0.021, 0.294), p = 0.02), after controlling for potential confounding factors.

CONCLUSION

We found minimal evidence of clinically relevant cohort effects in ADCS trials. Our results reinforce the original findings of these trials.

A generalized interrupted time series model for assessing complex health care interventions

Assessing the impact of complex interventions on measurable health outcomes is a growing concern in health care and health policy. Interrupted time series (ITS) designs borrow from traditional case-crossover designs and function as quasi-experimental methodology able to retrospectively analyze the impact of an intervention. Statistical models used to analyze ITS designs primarily focus on continuous-valued outcomes. We propose the "Generalized Robust ITS" (GRITS) model appropriate for outcomes whose underlying distribution belongs to the exponential family of distributions, thereby expanding the available methodology to adequately model binary and count responses. GRITS formally implements a test for the existence of a change point in discrete ITS. The methodology proposed is able to test for the existence of and estimate the change point, borrow information across units in multi-unit settings, and test for differences in the mean function and correlation pre- and post-intervention. The methodology is illustrated by analyzing patient falls from a hospital that implemented and evaluated a new care delivery model in multiple units.

Dyadic Enrollment in a Phase 3 Mild Cognitive Impairment Clinical Trial

BACKGROUND

Dyadic enrollment of a participant and study partner is required in mild cognitive impairment (MCI) clinical trials, despite participants being functionally independent. Research examining how the study partner requirement impacts MCI trials remains limited.

METHODS

Using the Alzheimer's Disease Cooperative Study donepezil and vitamin E MCI trial data, we quantified the proportions of enrolled spouse, adult child, and other dyads. We used multinomial regression to identify which baseline participant characteristics (age, sex, race and ethnicity, apolipoprotein E ε4 status, education, residence type) were associated with dyad type.

RESULTS

Among 769 randomized dyads, 73% were spousal, 14% adult child, and 13% other dyads. Adjusting for multiple comparisons, underrepresented racial and ethnic background (eg, comparing Hispanic to non-Hispanic White participants: adult child vs. spouse odds ratio = 5.86; 95% confidence interval: 2.09, 16.5; other vs. spouse odds ratio = 4.95; 95% confidence interval: 1.83, 13.4), female sex, age, nonhouse residence, and apolipoprotein E ε4 noncarriage were each associated with a higher odds of having an adult child, as well as an other, study partner at enrollment.

DISCUSSION

Increasing participation among nonspousal dyads may facilitate more inclusive and representative MCI trial samples.

Strategies Associated with Retaining Participants in the Longitudinal National Alzheimer's Coordinating Center Uniform Data Set Study

BACKGROUND

Best approaches for retaining research participants in Alzheimer's disease cohort studies are understudied.

OBJECTIVE

Using data from the National Alzheimer's Coordinating Center Uniform Data Set, we evaluated the associations of unique strategies with participant retention across Alzheimer's Disease Research Centers and explored potential effect modification by race, ethnicity and diagnostic group.

METHODS

We examined retention at the first follow-up visit among participants enrolled during 2015-2017. Structured surveys ascertained 95 retention tactics among 12 strategies. Strategy-specific summary scores were created based on the number of implemented tactics for each strategy and grouped into tertiles. Generalized estimating equations were constructed to evaluate associations between strategy scores and the odds of retention, controlling for age, sex, education, study partner type, marital status, visit length, battery length, diagnostic group, race and ethnicity. Separate models were stratified by race, ethnicity and diagnostic group. Effect modification was formally tested with interaction terms.

RESULTS

Among 5,715 total participants enrolled, 4,515 were Non-Hispanic White (79%), 335 were Hispanic/Latino (6%), 651 were Non-Hispanic Black (11%), and 214 were Non-Hispanic Asian (4%). Compared to the lowest tertile of scores, the highest tertile of scores involving improvement in study personnel and communication of study requirements and details were associated with 61% higher odds of retention in fully adjusted models (adjusted Odds Ratios [aOR] = 1.61, 95% Confidence Interval [CI] = 1.05-2.47 and aOR = 1.55, 95% CI = 1.03-2.35, respectively). We did not find evidence for effect modification.

CONCLUSION

In the setting of limited resources, specific retention strategies may be more valuable than others.

Effect of Aducanumab Approval on Willingness to Participate in Preclinical Alzheimer's Disease Trials

BACKGROUND

Clinical trials now test promising therapies in the preclinical stages of Alzheimer's disease (AD). Participant willingness to enroll in different types of preclinical AD trials is understudied and whether the FDA approval of aducanumab affected these attitudes is unknown.

OBJECTIVE

To evaluate preferences toward three preclinical AD trial scenarios and whether the FDA approval of aducanumab changed willingness to participate among potential trial participants.

METHODS

Through an electronic survey, we asked enrollees in a recruitment registry age 50-79 to rate their willingness (using a 6-point Likert scale) to enroll in three hypothetical preclinical AD trial scenarios: an in-clinic infused monoclonal antibody intervention, a home-infused monoclonal antibody intervention, and an oral BACE inhibitor intervention. We administered the survey before and after the FDA approval of aducanumab. We used a generalized estimating equation model to assess group differences in preference for the trial scenarios. We used a paired t-test to determine if willingness to participate (using total willingness across three scenarios as the outcome) changed after the FDA decision.

RESULTS

At baseline, the mean participant willingness was highest in the in-clinic infusion scenario. There was no significant change in willingness to participate, overall, after the FDA decision. Participants who were independently aware of the FDA's decision (prior to the second survey) demonstrated reduced willingness to participate; participants unaware of the FDA decision demonstrated no change.

CONCLUSION

Willingness to participate in preclinical AD trials may have been negatively affected by the FDA's decision to approve aducanumab among those aware of the decision.

Anxiety and Depressive Symptoms and Cortical Amyloid-β Burden in Cognitively Unimpaired Older Adults

BACKGROUND

There is evidence of relationships between behavioral symptoms and increased risk for Alzheimer's Disease and/or Alzheimer's Disease biomarkers. However, the nature of this relationship is currently unknown.

OBJECTIVES

To evaluate the relationship between anxiety and depressive symptoms and amyloid-β deposition in cognitively unimpaired older adults, and to assess mediating effects of either objective or subjective cognitive skills.

DESIGN

Cross-sectional analysis of screening data from participants enrolled in the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease (A4) Study (ClinicalTrials.gov Identifier: NCT02008357).

SETTING

Data analysis.

PARTICIPANTS

4492 cognitively unimpaired adults, age 65-85, enrolled in the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease (A4) Study.

MEASUREMENTS

We used linear regression to estimate the associations between amyloid-β standard uptake value ratio (SUVR) and Geriatric Depression Scale (GDS) and State Trait Anxiety Inventory (STAI) scores while adjusting for potential confounding factors as well as for Cognitive Function Index (CFI) or Preclinical Alzheimer's Cognitive Composite (PACC) scores as possible mediational variables.

RESULTS

4399 subjects with complete covariates were included (mean age: 71.3, 59% female), GDS ranged 0-13 (mean: 1.0), and STAI ranged 6-24 (mean: 9.9). Amyloid-β SUVR was modestly associated with STAI; mean STAI score was estimated to be 0.275 points higher (95% CI: 0.038, 0.526; p-value = 0.023) for each 0.5-point increase in cortical amyloid-β SUVR. Subjective cognitive decline (CFI) attenuated the relationship between SUVR and STAI, while objective cognitive function (PACC) did not. No statistically significant relationship between SUVR and GDS was observed (p = 0.326).

CONCLUSIONS

In cognitively unimpaired adults with low levels of depression and anxiety, cortical amyloid-β deposition is associated with anxiety but not depressive symptoms. Attenuation of this relationship by subjective cognitive difficulties suggests that anxiety may be partly due to such a perception resulting from cortical amyloid-β deposition.

Diversifying Recruitment Registries: Considering Neighborhood Health Metrics

BACKGROUND

Disparities in clinical research participation perpetuate broader health disparities. Recruitment registries are novel tools to address known challenges in accrual to clinical research. Registries may accelerate accrual, but the utility of these tools to improve generalizability is unclear.

OBJECTIVE

To examine the diversity of a local on-line recruitment registry using the Area Deprivation Index (ADI), a publicly available metric of neighborhood disadvantage.

DESIGN

Retrospective analysis.

SETTING

Data were collected in the University of California Irvine Consent-to-Contact Registry.

PARTICIPANTS

We categorized N=2,837 registry participants based on the ADI decile (collapsed into quintiles) using a state-based rankings.

MEASUREMENTS

We examined the proportion of enrollees per ADI quintile and quantified the demographics of these groups. We assessed willingness to participate in studies involving unique research procedures among the ADI groups.

RESULTS

Although registry enrollees represented the full spectrum of the ADI, they disproportionately represented less disadvantaged neighborhoods (lowest to highest quintiles: 42%, 30%, 15%, 6%, 7%). Compared to participants from less disadvantaged neighborhoods, participants from more disadvantaged neighborhoods were more often female, of non-white race, and Hispanic ethnicity. Despite demographic differences, ADI groups were observed to have similar willingness to participate in research studies.

CONCLUSIONS

People from more disadvantaged neighborhoods may be underrepresented in recruitment registries, increasing the risk that they will be underrepresented when using these tools to facilitate prospective recruitment to clinical research. Once enrolled in registries, participants from more disadvantaged neighborhoods may be equally willing to participate in research. Efforts to increase representation of participants from disadvantaged neighborhoods in registries could be an important first step toward increasing the generalizability of clinical research.

Censoring-robust time-dependent receiver operating characteristic curve estimators

Time-dependent receiver operating characteristic curves are often used to evaluate the classification performance of continuous measures when considering time-to-event data. When one is interested in evaluating the predictive performance of multiple covariates, it is common to use the Cox proportional hazards model to obtain risk scores; however, previous work has shown that when the model is mis-specified, the estimand corresponding to the partial likelihood estimator depends on the censoring distribution. In this manuscript, we show that when the risk score model is mis-specified, the AUC will also depend on the censoring distribution, leading to either over- or under-estimation of the risk score's predictive performance. We propose the use of censoring-robust estimators to remove the dependence on the censoring distribution and provide empirical results supporting the use of censoring-robust risk scores.

On the design of early-phase Alzheimer's disease clinical trials with cerebrospinal fluid tau outcomes

BACKGROUND/AIMS

The focus of Alzheimer's disease studies has shifted to earlier disease stages, including mild cognitive impairment. Biomarker inclusion criteria are often incorporated into mild cognitive impairment clinical trials to identify individuals with "prodromal Alzheimer's disease" to ensure appropriate drug targets and enrich for participants likely to develop Alzheimer's disease dementia. The use of these eligibility criteria may affect study power.

METHODS

We investigated outcome variability and study power in the setting of proof-of-concept prodromal Alzheimer's disease trials that incorporate cerebrospinal fluid levels of total tau (t-tau) and phosphorylated (p-tau) as primary outcomes and how differing biomarker inclusion criteria affect power. We used data from the Alzheimer's Disease Neuroimaging Initiative to model trial scenarios and to estimate the variance and within-subject correlation of total and phosphorylated tau. These estimates were then used to investigate the differences in study power for trials considering these two surrogate outcomes.

RESULTS

Patient characteristics were similar for all eligibility criteria. The lowest outcome variance and highest within-subject correlation were obtained when phosphorylated tau was used as an eligibility criterion, compared to amyloid beta or total tau, regardless of whether total tau or phosphorylated tau were used as primary outcomes. Power increased when eligibility criteria were broadened to allow for enrollment of subjects with either low amyloid beta or high phosphorylated tau.

CONCLUSION

Specific biomarker inclusion criteria may impact statistical power in trials using total tau or phosphorylated tau as the primary outcome. In concert with other important considerations such as treatment target and population of clinical interest, these results may have implications to the integrity and efficiency of prodromal Alzheimer's disease trial designs.

Reasons for undergoing amyloid imaging among cognitively unimpaired older adults

OBJECTIVES

Preclinical Alzheimer's disease (AD) clinical trials screen cognitively unimpaired older adults for biomarker criteria and disclose their results. We examined whether participants in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's disease Study with "elevated" and "not elevated" amyloid differed in scores on the "Views and Perceptions of Amyloid Imaging" questionnaire. We hypothesized that, prior to disclosure, those with elevated amyloid would score higher than those with not elevated amyloid. We also quantified how responses changed after result disclosure.

METHODS

We assessed data from 4327 individuals who completed the questionnaire at screening visit 1 and after amyloid disclosure. We used linear regression models to assess the relationship between questionnaire category scores and amyloid status. We also quantified the relationship between category score changes and amyloid status.

RESULTS

Overall, participants scored altruism and contribution to research as the strongest motivations for undergoing amyloid imaging. Those with elevated amyloid scored 0.23 points higher in the Perceived Risk category, on average, than those who had not elevated amyloid prior to disclosure; this effect attenuated towards zero after adjusting for Cognitive Function Instrument score. After disclosure, participants with elevated amyloid demonstrated less within-subject change in Perceived Risk, on average, compared to those with similar pre-disclosure scores who had not elevated amyloid, while demonstrating greater changes in the altruism and planning categories.

INTERPRETATION

Altruism and learning disease risk motivated enrollment in this preclinical AD trial. Participants with elevated amyloid differed from their not elevated counterparts in their perceptions of amyloid imaging, even before undergoing the procedure.

RITS: a toolbox for assessing complex interventions via interrupted time series models

BACKGROUND

Various interacting and interdependent components comprise complex interventions. These components create difficulty in assessing the true impact of interventions designed to improve patient-centered outcomes. Interrupted time series (ITS) designs borrow from case-crossover designs and serve as quasi-experimental methodology able to retrospectively assess the impact of an intervention while accounting for temporal correlation. While ITS designs are aptly situated for studying the impacts of large-scale public health policies, existing ITS software implement rigid ITS methodology that often assume the pre- and post-intervention phases are fully differentiated (by a known change-point or set of time points) and do not allow for changes in both the mean functions and correlation structure.

RESULTS

This article describes the Robust Interrupted Time Series (RITS) toolbox, a stand-alone user-friendly application researchers can use to implement flexible ITS models that estimate the lagged effect of an intervention on an outcome, level and trend changes, and post-intervention changes in the correlation structure, for single and multiple ITS. The RITS toolbox incorporates a formal test for the existence of a change in the outcome and estimates a change-point over a set of possible change-points defined by the researcher. In settings with multiple ITS, RITS provides a global over-all units change-point and allows for unit-specific changes in the mean functions and correlation structures.

CONCLUSIONS

The RITS toolbox is the first piece of software that allows researchers to use flexible ITS models that test for the existence of a change-point, estimate the change-point (if estimation is desired), and allow for changes in both the mean functions and correlation structures at the change point. RITS does not require any knowledge of a statistical (or otherwise) programming language, is freely available to the community, and may be downloaded and used on a local machine to ensure data protection.

Evaluation of the Safety and Efficacy of a Novel Thrombin Containing Combination Hemostatic Powder Using a Historical Control

This clinical study compares 2 hemostatic agents, a novel combination powder (CP) (HEMOBLAST^™ Bellows) and an established polysaccharide starch powder (PP) (Arista^™ AH) to assess the usefulness of CP. Retrospective comparative analysis of CP (July 2018 to July 2019, 68 patients) to PP (January 2011 to January 2013, 94 patients) in cardiothoracic patients was performed using linear regression models adjusting for age, sex, and procedure type for the endpoints: blood loss; protamine to skin closure time (hemostasis time); chest tube output and blood products required 48 hours postoperatively; ICU stay; postoperative comorbidities; and 30 day mortality. 162 patients (108 M: 54 F) underwent 162 cardiothoracic surgical procedures including: transplantation (n = 44), placement of ventricular assist device (n = 87), and others (n = 31). Use of CP compared to PP (Estimated Mean Difference [95% CI], P-value) produced significant reductions: blood loss (mL) (-886.51 [-1457.76, -312.26], P = 0.003); protamine to skin closure time (min) (-16.81 [-28.03, -5.59], P = 0.004); chest tube output (48 hrs, mL) (-445.76 [-669.38, -222.14], P < 0.001); packed red blood cell transfusions (units) (-0.98 [-1.56, -0.4], P = 0.001); and postoperative comorbidities (-0.31 [-0.55, -0.07], P = 0.012). There were no differences in the ICU stay (4.07 [-2.01, 10.15], P = 0.188) or 30-day mortality (0.57 [0.20, 1.63], P = 0.291). The use of CP in complex cardiothoracic operations resulted in improved hemostasis and significant clinical benefits in blood loss, transfusion requirements, morbidity, and time in operating room.

Using Direct-to-Consumer Genetic Testing Results to Accelerate Alzheimer Disease Clinical Trial Recruitment

INTRODUCTION

The apolipoprotein E (APOE) gene is the strongest known genetic risk factor for sporadic Alzheimer disease (AD). APOE can be used as an enrichment strategy or inclusion criterion for AD prevention trials. Personal genomics companies market direct-to-consumer (DTC) genetic tests, including APOE. We assessed DTC APOE testing usage among enrollees of the University of California Irvine Consent-to-Contact Registry, an online recruitment registry, and attitudes toward using this information in clinical trial recruitment.

METHODS

We emailed links to an electronic survey to registry enrollees age 50 years or older. We assessed participants' use of DTC services, willingness to learn APOE status, and willingness to share genetic information. Logistic regression models assessed relationships between DTC testing usage and demographic characteristics, and with willingness to share results to assist trial recruitment.

RESULTS

Among 1312 responders (57% response rate), few (7%) had used DTC testing for APOE. Non-Hispanic Asian enrollees were 93% less likely to have used DTC testing, compared with non-Hispanic Whites [95% confidence interval: (0.01, 0.67)]. Willingness to share APOE information for study recruitment was >90% for both users and nonusers.

CONCLUSIONS

Matching participants to trials on the basis of DTC APOE information may be an effective way to streamline AD prevention trial recruitment.

Placental Corticotrophin-Releasing Hormone is a Modulator of Fetal Liver Blood Perfusion

CONTEXT

Variation in fetal liver blood flow influences fetal growth and postnatal body composition. Placental corticotrophin-releasing hormone has been implicated as a key mediator of placental-fetal perfusion.

OBJECTIVE

To determine whether circulating levels of placental corticotrophin-releasing hormone across gestation are associated with variations in fetal liver blood flow.

DESIGN

Prospective cohort study.

METHODS

Fetal ultrasonography was performed at 30 weeks' gestation to characterize fetal liver blood flow (quantified by subtracting ductus venosus flow from umbilical vein flow). Placental corticotrophin-releasing hormone was measured in maternal circulation at approximately 12, 20, and 30 weeks' gestation. Multiple regression analysis was used to determine the proportion of variation in fetal liver blood flow explained by placental corticotrophin-releasing hormone. Covariates included maternal age, parity, pre-pregnancy body mass index, gestational weight gain, and fetal sex.

RESULTS

A total of 79 uncomplicated singleton pregnancies were analyzed. Fetal liver blood flow was 68.4 ± 36.0 mL/min (mean ± SD). Placental corticotrophin-releasing hormone concentrations at 12, 20, and 30 weeks were 12.5 ± 8.1, 35.7 ± 24.5, and 247.9 ± 167.8 pg/mL, respectively. Placental corticotrophin-releasing hormone at 30 weeks, but not at 12 and 20 weeks, was significantly and positively associated with fetal liver blood flow at 30 weeks (r = 0.319; P = 0.004) and explained 10.4% of the variance in fetal liver blood flow.

CONCLUSIONS

Placental corticotrophin-releasing hormone in late gestation is a possible modulator of fetal liver blood flow and may constitute a biochemical marker in clinical investigations of fetal growth and body composition.

Recruitment and retention of participant and study partner dyads in two multinational Alzheimer's disease registration trials

BACKGROUND

Early study exit is detrimental to statistical power and increases the risk for bias in Alzheimer's disease clinical trials. Previous analyses in early phase academic trials demonstrated associations between rates of trial incompletion and participants' study partner type, with participants enrolling with non-spouse study partners being at greater risk.

METHODS

We conducted secondary analyses of two multinational phase III trials of semagacestat, an oral gamma secretase inhibitor, for mild-to-moderate AD dementia. Cox's proportional hazards regression model was used to estimate the relationship between study partner type and the risk of early exit from the trial after adjustment for a priori identified potential confounding factors. Additionally, we used a random forest model to identify top predictors of dropout.

RESULTS

Among participants with spousal, adult child, and other study partners, respectively, 35%, 38%, and 36% dropped out or died prior to protocol-defined study completion, respectively. In unadjusted models, the risk of trial incompletion differed by study partner type (unadjusted p value = 0.027 for test of differences by partner type), but in models adjusting for potential confounding factors, the differences were not statistically significant (p value = 0.928). In exploratory modeling, participant age was identified as the primary characteristic to explain the relationship between study partner type and the risk of failing to complete the trial. Participant age was also the strongest predictor of trial incompletion in the random forest model.

CONCLUSIONS

After adjustment for age, no differences in the risk of incompletion were observed when comparing participants with different study partner types in these trials. Differences between our findings and the findings of previous studies may be explained by differences in trial phase, size, geographic regions, or the composition of academic and non-academic sites.

Is Reluctance to Share Alzheimer's Disease Biomarker Status with a Study Partner a Barrier to Preclinical Trial Recruitment?

BACKGROUND

Preclinical Alzheimer's disease clinical trials test candidate treatments in individuals with biomarker evidence but no cognitive impairment. Participants are required to co-enroll with a knowledgeable study partner, to whom biomarker information is disclosed.

OBJECTIVE

We investigated whether reluctance to share biomarker results is associated with viewing the study partner requirement as a barrier to preclinical trial enrollment.

DESIGN

We developed a nine-item assessment on views toward the study partner requirement and performed in-person interviews based on a hypothetical clinical trial requiring biomarker testing and disclosure.

SETTING

We conducted interviews on campus at the University of California, Irvine.

PARTICIPANTS

Two hundred cognitively unimpaired older adults recruited from the University of California, Irvine Consent-to-Contact Registry participated in the study.

MEASUREMENTS

We used logistic regression models, adjusting for potential confounders, to examine potential associations with viewing the study partner requirement as a barrier to preclinical trial enrollment.

RESULTS

Eighteen percent of participants reported strong agreement that the study partner requirement was a barrier to enrollment. Ten participants (5%) agreed at any level that they would be reluctant to share their biomarker result with a study partner. The estimated odds of viewing the study partner requirement as a barrier to enrollment were 26 times higher for these participants (OR=26.3, 95% CI 4.0, 172.3), compared to those who strongly disagreed that they would be reluctant to share their biomarker result. Overall, participants more frequently agreed with positive statements than negative statements about the study partner requirement, including 76% indicating they would want their study partner with them when they learned biomarker results.

CONCLUSIONS

This is one of the first studies to explore how potential preclinical Alzheimer's disease trial participants feel about sharing their personal biomarker information with a study partner. Most participants viewed the study partner as an asset to trial enrollment, including having a partner present during biomarker disclosure.

Direct Mail Recruitment to a Potential Participant Registry

Recruitment registries are novel tools to accelerate Alzheimer disease research accrual. Optimal methods to populate such registries remain largely unstudied. We sent postcards with 3 unique taglines (Alzheimer's Prevention Research, brain health research, general research) to 100,000 local residents aged 50 years and older to assess the effectiveness of recruiting to an online recruitment registry by mail. The postcard campaign recruited 273 new registry enrollees (0.27% overall response rate). Neither the response rate nor the demographic characteristics of recruited participants differed by the postcard tagline. These results suggest that direct mail may not be the most cost-effective approach to recruit participants to online registries.

A stratified generalized additive model and permutation test for temporal heterogeneity of smoothed bivariate spatial effects

Generalized additive models (GAMs) with bivariate smoothers are frequently used to map geographic disease risks in epidemiology studies. A challenge in identifying health disparities has been the lack of intuitive and computationally feasible methods to assess whether the pattern of spatial effects varies over time. In this research, we accommodate time-stratified smoothers into the GAM framework to estimate time-specific spatial risk patterns while borrowing information from confounding effects across time. A backfitting algorithm for model estimation is proposed along with a permutation testing framework for assessing temporal heterogeneity of geospatial risk patterns across two or more time points. Simulation studies show that our proposed permuted mean squared difference (PMSD) test performs well with respect to type I error and power in various settings when compared with existing methods. The proposed model and PMSD test are used geospatial risk patterns of patent ductus arteriosus (PDA) in the state of Massachusetts over 2003-2009. We show that there is variation over time in spatial patterns of PDA risk, adjusting for other known risk factors, suggesting the presence of potential time-varying and space-related risk factors other than the adjusted ones.

Robust estimation in the nested case-control design under a misspecified covariate functional form

The Cox proportional hazards model is typically used to analyze time-to-event data. If the event of interest is rare and covariates are difficult or expensive to collect, the nested case-control (NCC) design provides consistent estimates at reduced costs with minimal impact on precision if the model is specified correctly. If our scientific goal is to conduct inference regarding an association of interest, it is essential that we specify the model a priori to avoid multiple testing bias. We cannot, however, be certain that all assumptions will be satisfied so it is important to consider robustness of the NCC design under model misspecification. In this manuscript, we show that in finite sample settings where the functional form of a covariate of interest is misspecified, the estimates resulting from the partial likelihood estimator under the NCC design depend on the number of controls sampled at each event time. To account for this dependency, we propose an estimator that recovers the results obtained using using the full cohort, where full covariate information is available for all study participants. We present the utility of our estimator using simulation studies and show the theoretical properties. We end by applying our estimator to motivating data from the Alzheimer's Disease Neuroimaging Initiative.

Longitudinal Mapping of Cortical Thickness Measurements: An Alzheimer's Disease Neuroimaging Initiative-Based Evaluation Study

Longitudinal studies of development and disease in the human brain have motivated the acquisition of large neuroimaging data sets and the concomitant development of robust methodological and statistical tools for quantifying neurostructural changes. Longitudinal-specific strategies for acquisition and processing have potentially significant benefits including more consistent estimates of intra-subject measurements while retaining predictive power. Using the first phase of the Alzheimer's Disease Neuroimaging Initiative (ADNI-1) data, comprising over 600 subjects with multiple time points from baseline to 36 months, we evaluate the utility of longitudinal FreeSurfer and Advanced Normalization Tools (ANTs) surrogate thickness values in the context of a linear mixed-effects (LME) modeling strategy. Specifically, we estimate the residual variability and between-subject variability associated with each processing stream as it is known from the statistical literature that minimizing the former while simultaneously maximizing the latter leads to greater scientific interpretability in terms of tighter confidence intervals in calculated mean trends, smaller prediction intervals, and narrower confidence intervals for determining cross-sectional effects. This strategy is evaluated over the entire cortex, as defined by the Desikan-Killiany-Tourville labeling protocol, where comparisons are made with the cross-sectional and longitudinal FreeSurfer processing streams. Subsequent linear mixed effects modeling for identifying diagnostic groupings within the ADNI cohort is provided as supporting evidence for the utility of the proposed ANTs longitudinal framework which provides unbiased structural neuroimage processing and competitive to superior power for longitudinal structural change detection.

Education and Message Framing Increase Willingness to Undergo Research Lumbar Puncture: A Randomized Controlled Trial

Reluctance to undergo lumbar puncture (LP) is a barrier to neurological disease biomarker research. We assessed whether an educational intervention increased willingness to consider research LP and whether message framing modified intervention effectiveness. We randomly assigned 851 recruitment registry enrollees who had previously indicated they were unwilling to be contacted about studies requiring LP to gain or loss framed video educational interventions describing the procedure and the probability of experiencing adverse events. The gain framed intervention emphasized the proportion of individuals free of adverse events; the loss frame emphasized the proportion experiencing adverse events. The primary outcome for the study was the participant's post-intervention agreement to be contacted about studies requiring LP. Participants were mean (SD) age 60.1 years (15.7), 69% female (n = 591), and mostly college educated and white. Among the 699 participants who completed the study, 43% (95% CI: 0.39, 0.47; n = 301) changed their response to agree to be contacted about studies requiring LP. We estimated that participants randomized to the gain framed intervention had 67% higher odds of changing their response compared to those randomized to the loss frame (Odds Ratio = 1.67; 95% CI: 1.24, 2.26; p < 0.001). A classification and regression tree model identified participants' pre-intervention willingness as the strongest predictor of changing response. Education, in particular education that alerts participants to the probability of not experiencing adverse events, may be an effective tool to increase participation rates in research requiring LP.

Anterolateral entorhinal cortex thickness as a new biomarker for early detection of Alzheimer's disease

INTRODUCTION

Loss of entorhinal cortex (EC) layer II neurons represents the earliest Alzheimer's disease (AD) lesion in the brain. Research suggests differing functional roles between two EC subregions, the anterolateral EC (aLEC) and the posteromedial EC (pMEC).

METHODS

We use joint label fusion to obtain aLEC and pMEC cortical thickness measurements from serial magnetic resonance imaging scans of 775 ADNI-1 participants (219 healthy; 380 mild cognitive impairment; 176 AD) and use linear mixed-effects models to analyze longitudinal associations among cortical thickness, disease status, and cognitive measures.

RESULTS

Group status is reliably predicted by aLEC thickness, which also exhibits greater associations with cognitive outcomes than does pMEC thickness. Change in aLEC thickness is also associated with cerebrospinal fluid amyloid and tau levels.

DISCUSSION

Thinning of aLEC is a sensitive structural biomarker that changes over short durations in the course of AD and tracks disease severity-it is a strong candidate biomarker for detection of early AD.

SPOT GRADE II: Clinical Validation of a New Method for Reproducibly Quantifying Surgical Wound Bleeding: Prospective, Multicenter, Multispecialty, Single-Arm Study

The SPOT GRADE (SG), a Surface Bleeding Severity Scale, is a unique visual method for assessing bleeding severity based on quantitative determinations of blood flow. This study assessed the reliability of the SG scale in a clinical setting and collected initial data on the safety and efficacy of HEMOBLAST Bellows (HB), a hemostatic agent, in abdominal and orthopedic operations. Twenty-seven patients were enrolled across 3 centers and received the investigational device. Bleeding severity and hemostasis were independently assessed by 2 surgical investigators at baseline and at 3, 6, and 10 minutes after application of HB and compared for agreement. The mean paired κ statistic for assignment of SG scores was .7754. The mean paired κ statistics for determining eligibility for participation in the trial based on bleeding severity and the mean paired κ statistics determining the presence of hemostasis were .9301 and .9301, respectively. The proportion of patients achieving hemostasis within 3, 6, and 10 minutes of HB application were 50.0%, 79.2%, and 91.7%, respectively. There were no unanticipated adverse device effects and one possible serious adverse device effect, as determined by the Independent Data Monitoring Committee (IDMC). The reliability of the SG scale was validated in a clinical setting. Initial data on the safety and efficacy of HB in abdominal and orthopedic operations were collected, and there were no concerns raised by the investigators or the IDMC.

Statin Therapy Before Transition to End-Stage Renal Disease With Posttransition Outcomes

Background Although studies have shown that statin therapy in patients with non-dialysis-dependent chronic kidney disease was associated with a lower risk of death, this was not observed in dialysis patients newly initiated on statins. It is unclear if statin therapy benefits administered during the predialysis period persist after transitioning to end-stage renal disease. Methods and Results In 47 720 veterans who transitioned to end-stage renal disease during 2007 to 2014, we examined the association of statin therapy use 1 year before transition with posttransition all-cause and cardiovascular mortality and hospitalization incidence rates over the first 12 months of follow-up. Associations were examined using multivariable adjusted Cox proportional hazard models and negative binomial regressions. Sensitivity analyses included propensity score and subgroup analyses. The cohort's mean± SD age was 71±11 years, and the cohort included 4% women, 23% blacks, and 66% diabetics. Over 12 months of follow-up, there were 13 411 deaths, with an incidence rate of 35.3 (95% CI , 34.7-35.8) deaths per 100 person-years. In adjusted models, statin therapy compared with no statin therapy was associated with lower risks of 12-month all-cause (hazard ratio [95% CI], 0.79 [0.76-0.82]) and cardiovascular (hazard ratio [95% CI ], 0.83 [0.78-0.88]) mortality, as well as with a lower rate of hospitalizations (incidence rate ratio [95% CI ], 0.89 [0.87-0.92]) after initiating dialysis. These lower outcome risks persisted across strata of clinical characteristics, and in propensity score analyses. Conclusions Among veterans with non-dialysis-dependent chronic kidney disease, treatment with statin therapy within the 1 year before transitioning to end-stage renal disease is associated with favorable early end-stage renal disease outcomes.

Variance estimation for the Kappa statistic in the presence of clustered data and heterogeneous observations

We present a methodology motivated by a controlled trial designed to validate SPOT GRADE, a novel surgical bleeding severity scale. Briefly, the study was designed to quantify inter- and intra-surgeon agreement for characterizing the severity of surgical bleeds via a Kappa statistic. Multiple surgeons were presented with a randomized sequence of controlled bleeding videos and asked to apply the rating system to characterize each wound. Each video was shown multiple times to quantify intra-surgeon reliability, creating clustered data. In addition, videos within the same category may have had different classification probabilities due to changes in blood flow rates and wound sizes. In this work, we propose a new variance estimator for the Kappa statistic, for use in clustered data as well as heterogeneity among items within the same classification category. We then apply this methodology to data from the SPOT GRADE trial.