Current issues in dose-finding designs: A response to the US Food and Drug Adminstrations's Oncology Center of Excellence Project Optimus

With the advent of targeted agents and immunological therapies, the medical research community has become increasingly aware that conventional methods for determining the best dose or schedule of a new agent are inadequate. It has been well established that conventional phase I designs cannot reliably identify safe and effective doses. This problem applies, generally, for cytotoxic agents, radiation therapy, targeted agents, and immunotherapies. To address this, the US Food and Drug Administration's Oncology Center of Excellence initiated Project Optimus, with the goal "to reform the dose optimization and dose selection paradigm in oncology drug development." As a response to Project Optimus, the articles in this special issue of Clinical Trials review recent advances in methods for choosing the dose or schedule of a new agent with an overall objective of informing clinical trialists of these innovative designs. This introductory article briefly reviews problems with conventional methods, the regulatory changes that encourage better dose optimization designs, and provides brief summaries of the articles that follow in this special issue.

Protocol for randomized personalized trial for stress management compared to standard of care

Stress is a significant public health burden in the United States, with most Americans reporting unhealthy levels of stress. Stress management techniques include various evidence-based treatments shown to be effective but with heterogeneous treatment responses, indicating a lack of uniform benefits for all individuals. Designed to assess a participant's response to a specific intervention, personalized (N-of-1) trials provide guidance for which treatment (s) work (s) best for the individual. Prior studies examining the effects of mindfulness meditation, yoga, and walking for stress reduction found all three interventions to be associated with significant reductions in self-reported measures of stress. Delivering these treatments using a personalized trial approach has the potential to assist clinicians in identifying the best stress management techniques for individuals with persistently high stress while fostering treatment decisions that consider their personal condition/barriers. This trial will evaluate a personalized approach compared to standard of care for three interventions (guided mindfulness meditation; guided yoga; and guided brisk walking) to manage perceived stress. Participants will respond to daily surveys and wear a Fitbit device for 18 weeks. After a 2-week baseline period, participants in the personalized trial groups will receive 12 weeks of interventions in randomized order, while participants in the standard-of-care group will have access to all interventions for self-directed stress management. After intervention, all participants will undergo 2 weeks of observation, followed by two additional weeks of the stress management intervention of their choosing while continuing outcome measurement. At study completion, all participants will be sent a satisfaction survey. The primary analysis will compare perceived stress levels between the personalized and standard of care arms. The results of this trial will provide further support for the use of personalized designs for managing stress. Clinical Trial Registration: clinicaltrials.gov, NCT05408832. Protocol version: 9/14/2022, 21-0968-MRB.

The effect of a multi-component behavior change technique intervention on medication adherence among individuals on primary prevention statin therapy: a dose-finding protocol

BACKGROUND

In the USA, the primary cause of death and morbidity continues to be cardiovascular disease (CVD). Numerous trials have shown that statin medication reduces the likelihood of CVD events; it is a cornerstone of CVD prevention. However, studies have also indicated that up to 60% of the estimated 26.8 million Americans prescribed primary prevention statin treatment are nonadherent during the first year. Multi-component behavioral change technique (BCT) therapies have shown moderate promise in improving medication adherence as well as other positive health behaviors (such as physical activity). However, no research has looked at the duration of multi-component BCT intervention needed to result in a clinically significant improvement in statin adherence behaviors. This study aims to determine the necessary dose of a multi-component BCT intervention (defined as duration in weeks) to promote adherence to statin medication among those on primary prevention statin treatment by utilizing the modified time-to-event continuous reassessment method (TiTE-CRM).

METHODS AND DESIGN

The study will utilize the modified TiTE-CRM in 42 participants, recruited in 14 cohorts of 3 participants each. The goal of this analysis is to identify the minimum effective dose (MED) of a multi-behavior change technique (BCT) intervention required to increase adherence to statins by 20% between baseline and follow-up periods. Using the TiTE-CRM method, the dose of the behavior intervention in weeks will be assigned to each cohort based on the performance of the prior cohort. At the end of the study, the intervention dose that has been found to be associated with a 20% increase in statin adherence among 80% of participants assigned to that dose will be identified as the MED.

DISCUSSION

If successful, the current trial will provide additional guidance to researchers and clinicians seeking to increase statin medication adherence using a BCT intervention by identifying the dose (i.e., the duration) of an intervention required to meaningfully increase adherence.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05273736. Registered on March 10, 2022. https://www.

CLINICALTRIALS

gov/ct2/show/NCT05273736.

A Series of Remote Melatonin Supplement Interventions for Poor Sleep: Protocol for a Feasibility Pilot Study for a Series of Personalized (N-of-1) Trials

BACKGROUND

Poor sleep, defined as short-duration or poor-quality sleep, is a frequently reported condition with many deleterious effects including poorer cognitive functioning, increased accidents, and poorer health. Melatonin has been shown to be an efficacious treatment to manage symptoms of poor sleep. However, the treatment effects of melatonin on sleep can vary greatly between participants. Personalized, or N-of-1, trial designs represent a method for identifying the best treatment for individual participants. Although using N-of-1 trials of melatonin to treat poor sleep is possible, the feasibility, acceptability, and effectiveness of N-of-1 trials using melatonin are unknown. Using the National Institutes of Health Stage Model for Behavioral Intervention Development, a stage IB (intervention refinement, modification, and adaptation and pilot testing) design appeared to be needed to address these feasibility questions.

OBJECTIVE

This trial series evaluates the feasibility, acceptability, and effectiveness of a series of personalized interventions for remote delivery of melatonin dose (3 and 0.5 mg) versus placebo supplements for self-reported poor sleep among 60 participants. The goal of this study is to provide valuable information about implementing remote N-of-1 randomized controlled trials to improve poor sleep.

METHODS

Participants will complete a 2-week baseline followed by six 2-week alternating intervention periods of 3 mg of melatonin, 0.5 mg of melatonin, and placebo. Participants will be randomly assigned to 2 intervention orders. The feasibility and acceptability of the personalized trial approach will be determined with participants' ratings of usability and satisfaction with the remote, personalized intervention delivery system. The effectiveness of the intervention will be measured using participants' self-reported sleep quality and duration and Fitbit tracker-measured sleep duration and efficiency. Additional measures will include ecological momentary assessment measures of fatigue, stress, pain, mood, concentration, and confidence as well as measures of participant adherence to the intervention, use of the Fitbit tracker, and survey data collection.

RESULTS

As of the submission of this protocol, recruitment for this National Institutes of Health stage IB personalized trial series is approximately 78.3% complete (47/60). We expect recruitment and data collection to be finalized by June 2023.

CONCLUSIONS

Evaluating the feasibility, acceptability, and effectiveness of a series of personalized interventions of melatonin will address the longer term aim of this program of research-is integrating N-of-1 trials useful patient care? The personalized trial series results will be published in a peer-reviewed journal and will follow the CONSORT (Consolidated Standards of Reporting Trials) extension for N-of-1 trials (CENT 2015) reporting guidelines. This trial series was approved by the Northwell Health institutional review board.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05349188; https://www.clinicaltrials.gov/study/NCT05349188.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/45313.

Breaking Up Prolonged Sitting to Improve Cardiometabolic Risk: Dose-Response Analysis of a Randomized Crossover Trial

PURPOSE

Sedentary time is ubiquitous in developed nations and is associated with deleterious health outcomes. Physical activity guidelines recommend reductions in sedentary time; however, quantitative guidelines that inform how often and how long sedentary time should be interrupted have not been provided. The purpose of this study was to examine the acute effects of multiple doses of a sedentary break intervention on cardiometabolic risk factors, concurrently evaluating efficacy of varying frequencies and durations of sedentary breaks.

METHODS

In a randomized crossover study, middle- and older-age adults ( n = 11) completed the following 8-h conditions on five separate days: 1 uninterrupted sedentary (control) condition and four acute (experimental) trials that entailed different sedentary break frequency/duration combinations: every 30 min for 1 min, every 30 min for 5 min, every 60 min for 1 min, and every 60 min for 5 min. Sedentary breaks entailed light-intensity walking. Glucose and blood pressure (BP) were measured every 15 and 60 min, respectively.

RESULTS

Compared with control, glucose incremental area under the curve was significantly attenuated only for the every 30 min for 5-min dose (-11.8[4.7]; P = 0.017). All sedentary break doses yielded significant net decreases in systolic BP from baseline compared with control ( P < 0.05). The largest reductions in systolic BP were observed for the every 60 min for 1 min (-5.2 [1.4] mm Hg) and every 30 min for 5 min (-4.3[1.4] mm Hg) doses.

CONCLUSIONS

The present study provides important information concerning efficacious sedentary break doses. Higher-frequency and longer-duration breaks (every 30 min for 5 min) should be considered when targeting glycemic responses, whereas lower doses may be sufficient for BP lowering.

Monotone response surface of multi-factor condition: estimation and Bayes classifiers

We formulate the estimation of monotone response surface of multiple factors as the inverse of an iteration of partially ordered classifier ensembles. Each ensemble (called PIPE-classifiers) is a projection of Bayes classifiers on the constrained space. We prove the inverse of PIPE-classifiers (iPIPE) exists, and propose algorithms to efficiently compute iPIPE by reducing the space over which optimisation is conducted. The methods are applied in analysis and simulation settings where the surface dimension is higher than what the isotonic regression literature typically considers. Simulation shows iPIPE-based credible intervals achieve nominal coverage probability and are more precise compared to unconstrained estimation.

Genome-wide association study of executive function in a multi-ethnic cohort implicates LINC01362: Results from the northern Manhattan study

Executive function is a cognitive domain with sizable heritability representing higher-order cognitive abilities. Genome-wide association studies (GWAS) of executive function are sparse, particularly in populations underrepresented in medical research. We performed a GWAS on a composite measure of executive function that included measures of mental flexibility and reasoning using data from the Northern Manhattan Study, a racially and ethnically diverse cohort (N = 1077, 69% Hispanic, 17% non-Hispanic Black and 14% non-Hispanic White). Four SNPs located in the long intergenic non-protein coding RNA 1362 gene, LINC01362, on chromosome 1p31.1, were significantly associated with the composite measure of executive function in this cohort (top SNP rs2788328, ß = 0.22, p = 3.1 × 10-10). The associated SNPs have been shown to influence expression of the tubulin tyrosine ligase like 7 gene, TTLL7 and the protein kinase CAMP-activated catalytic subunit beta gene, PRKACB, in several regions of the brain involved in executive function. Together, these findings present new insight into the genetic underpinnings of executive function in an understudied population.

Analysis of N-of-1 trials using Bayesian distributed lag model with autocorrelated errors

An N-of-1 trial is a multi-period crossover trial performed in a single individual, with a primary goal to estimate treatment effect on the individual instead of population-level mean responses. As in a conventional crossover trial, it is critical to understand carryover effects of the treatment in an N-of-1 trial, especially when no washout periods between treatment periods are instituted to reduce trial duration. To deal with this issue in situations where a high volume of measurements are made during the study, we introduce a novel Bayesian distributed lag model that facilitates the estimation of carryover effects, while accounting for temporal correlations using an autoregressive model. Specifically, we propose a prior variance-covariance structure on the lag coefficients to address collinearity caused by the fact that treatment exposures are typically identical on successive days. A connection between the proposed Bayesian model and penalized regression is noted. Simulation results demonstrate that the proposed model substantially reduces the root mean squared error in the estimation of carryover effects and immediate effects when compared to other existing methods, while being comparable in the estimation of the total effects. We also apply the proposed method to assess the extent of carryover effects of light therapies in relieving depressive symptoms in cancer survivors.

Integrating non-concurrent controls in the analyses of late-entry experimental arms in multi-arm trials with a shared control group in the presence of parameter drift

BACKGROUND

Under a master protocol, open platform trials allow new experimental treatments to enter an existing clinical trial. Whether late-entry experimental treatments should be compared to all available or concurrently randomized controls is not well established. Using all available data can increase power and precision; however, drift in population parameters can yield biased estimates and impact type I error rate.

METHODS

We explored the application of methods developed to incorporate historical controls in two-arm trials to the analysis of a late-entry arm in a simulated open platform trial under varying scenarios of parameter drift. Methods explored include test-then-pool, fixed power prior, dynamic power prior, and multi-source exchangeability model approaches.

RESULTS/CONCLUSIONS

Simulated trial results confirm that in the presence of no drift, naively pooling all controls increases power and produces more precise, unbiased estimates when compared to using concurrent controls only. However, under drift, pooling can result in type I error rate inflation or deflation and biased estimates. In the presence of parameter drift, methods that partially borrow non-concurrent data, either through a static weighting mechanism or through methods that allow the heterogeneity between non-concurrent and concurrent data to determine the degree of borrowing, are superior to naively pooling the data. However, compared to using concurrent controls only, these approaches cannot guarantee type I error control or unbiased estimates. Thus, concurrent controls should be used as comparators in confirmatory studies.

Telehealth After Stroke Care Pilot Randomized Trial of Home Blood Pressure Telemonitoring in an Underserved Setting

Background:

Hypertension is the most important modifiable stroke risk factor, but blood pressure (BP) remains poorly controlled after stroke, especially among Black and Hispanic patients. We tested the feasibility of TASC (Telehealth After Stroke Care), a post-acute stroke care model integrating nurse-supported home BP telemonitoring, tailored infographics, and multidisciplinary team video visits.

Methods:

Acute stroke patients with hypertension were randomized at discharge to usual care or usual care with TASC. Usual care patients received video visits with primary care and stroke. TASC included a tablet and monitor to wirelessly transmit BP data to the electronic health record, with telenursing support, tailored infographics to explain BP readings, and pharmacist visits. Outcomes assessment was blinded. Feasibility outcomes included recruitment, randomization, adherence, and retention. Systolic BP from baseline to 3 months after discharge was evaluated using generalized linear modeling.

Results:

Fifty patients (64±14 years; 36% women‚ 44% Hispanic, 32% Black, 54% ≤high school education, 30% private insurance), and 75% of all eligible were enrolled over 6.3 months. Baseline systolic BP was similar in both (TASC n=25, 140±19 mm Hg; usual care n=25, 142±19 mm Hg). At 3 months, adherence to video visits (91% versus 75%, P =0.14) and retention (84% versus 64%, P =0.11) were higher with TASC. Home systolic BP declined by 16±19 mm Hg from baseline in TASC and increased by 3±24 mm Hg in usual care ( P =0.01). Among Black patients, systolic BP control (<130 mm Hg) improved from 40% to 100% with TASC versus 14% to 29%, and among Hispanic patients, from 23% to 62% with TASC, versus 33% to 17% in usual care.

Conclusions:

Enhancing post-acute stroke care with home BP telemonitoring is feasible to improve hypertension in an underserved setting and should be tested in a definitive randomized clinical trial.

Registration:

URL: https://www.clinicaltrials.gov ; Unique identifier: NCT04640519.

Series of virtual light therapy interventions for fatigue: a feasibility pilot study protocol for a series of personalised (N-of-1) trials

INTRODUCTION

Fatigue is one of the most commonly recorded patient symptoms that can result in deficits in aspects of psychomotor functioning, cognition, work performance and mood. Research shows that bright light and dim light therapy may be an efficacious way to reduce symptoms of fatigue. Still, the feasibility, scalability, individual treatment effects and adverse event heterogeneity of these treatments are unknown.

METHODS AND ANALYSIS

The current study evaluates the feasibility, acceptability and effectiveness of a series of personalised (N-of-1) interventions for virtual delivery of bright light therapy and dim light therapy versus usual care treatment for fatigue in 60 participants. We hypothesise that this study will provide valuable information about implementing virtual, N-of-1 randomised controlled trials (RCTs) for fatigue. It will also offer results about determining participants' ratings of usability and satisfaction with the virtual, personalised intervention delivery system; evaluating participants' improvement of fatigue symptoms; and, in the long term, identify ways to integrate N-of-1 light therapy trials into patient care.

ETHICS AND DISSEMINATION

This trial was approved by the Northwell Health Institutional Review Board. The trial results will be published in a peer-reviewed journal. All publications resulting from this series of personalised trials will follow the Consolidated Standards of Reporting Trials extension for N-of-1 trials CENT 2015 reporting guidelines.

REGISTRATION DETAILS

This trial is registered in www.

CLINICALTRIALS

gov (number NCT04707846).

TRIAL REGISTRATION NUMBER

NCT04707846.

Introducing Data Sciences to N-of-1 Designs, Statistics, Use-Cases, the Future, and the Moniker 'N-of-1' Trial

This article, an introduction to HDSR's "Personalized (N-of-1) Trials: Methods, Applications, and Impact" special issue, describes the rationale for a primer of the methods, data types and management, designs, and use cases for personalized (N-of-1) trials. It explains that the design and implementation of personalized (N-of-1) trials is only useful if patients volunteer for research involving them and actively participate in clinical services that use them. However, 'N-of-1 trials' may be an inadequate name to enact such patient engagement. The authors briefly review what patients have reported about the 'N-of-1' label and propose a more consumer-friendly moniker for this type of research and clinical approach to improve evidence-based science.

A NOVEL FRAMEWORK TO ESTIMATE MULTIDIMENSIONAL MINIMUM EFFECTIVE DOSES USING ASYMMETRIC POSTERIOR GAIN AND ϵ-TAPERING

In this article we address the problem of estimating minimum effective doses in dose-finding clinical trials of multidimensional treatment. We are motivated by a behavioral intervention trial where we introduce sedentary breaks to subjects with a goal to reduce their glucose level monitored over 8 hours. Each sedentary break regimen is defined by two elements: break frequency and break duration. The trial aims to identify minimum combinations of frequency and duration that shift mean glucose, that is, the minimum effective dose (MED) combinations. The means of glucose reduction associated with the dose combinations are only partially ordered. To circumvent constrained estimation due to partial ordering, we propose estimating the MED by maximizing a weighted product of combinationwise posterior gains. The estimation adopts an asymmetric gain function, indexed by a decision parameter ϵ , which defines the relative gains of a true negative decision and a true positive decision. We also introduce an adaptive ϵ -tapering algorithm to be used in conjunction with the estimation method. Simulation studies show that using asymmetric gain with a carefully chosen ϵ is critical to keeping false discoveries low, while ϵ -tapering adds to the probability of identifying truly effective doses (i.e., true positives). Under an ensemble of scenarios for the sedentary break study, ϵ -tapering yields consistently high true positive rates across scenarios and achieves about 90% true positive rate, compared to 68% by a nonadaptive design with comparable false discovery rate.

Genetic determinants of intracranial large artery stenosis in the northern Manhattan study

BACKGROUND

Intracranial stenosis is one of the most common causes of stroke worldwide. Several single nucleotide polymorphisms have been associated with intracranial atherosclerosis, which is inferred to be the most common underlying cause of intracranial large artery stenosis (ILAS). We previously reviewed known genetic variants related to ILAS in predominantly Asian cohorts, but their prevalence and role in ILAS among western multiethnic populations are uncertain.

METHODS

We leveraged existing imaging and genetic data from the Northern Manhattan Study, a multiethnic prospective cohort study. Based on literature review, we selected adiponectin Q (ADIPOQ) rs2241767 and rs182052, ring finger protein 213 (RNF213) rs112735431, apolipoprotein E (APOE) rs429358, phosphodiesterase 4D (PDE4D) rs2910829, lipoprotein lipase (LPL) rs320, and aldosterone synthase (CYP11B2) rs1799998 variants as candidates to explore. We defined ILAS as luminal stenosis >50% in any intracranial large artery using time-of-flight magnetic resonance angiography (MRA).

RESULTS

We included 1109 participants (mean age 70 ± 9 years, 70% Hispanic, 60% women) in this study. ILAS was identified in 81 (7%) NOMAS participants. Logistic regression analyses adjusted for age, sex, principal components, and vascular risk factors showed ILAS prevalence associated with CYP11B2 rs1799998 under the dominant model (OR = 0.56, 95%CI: 0.35-0.89) and LPL rs320 heterozygote genotype (OR = 1.68, 95%CI: 1.05-2.71). The genotype distributions of ADIPOQ rs2241767 and rs182052, APOE rs429358 and CYP11B2 rs1799998 variants were significantly different among non-Hispanic white and Black, and Hispanic groups. When participants were further stratified by race/ethnicity, the estimates were consistent for CYP11B2 rs1799998 across race/ethnic groups but not for LPL rs320.

CONCLUSION

The CYP11B2 rs1799998 variant may be a protective genetic factor for ILAS across race/ethnic groups, but the risk of ILAS associated with LPL rs320 varies by race/ethnic group. Further functional studies may help elucidate the role that these variants play in the pathophysiology of ILAS.

TASC (Telehealth After Stroke Care): a study protocol for a randomized controlled feasibility trial of telehealth-enabled multidisciplinary stroke care in an underserved urban setting

Background

Hypertension is the most important modifiable risk factor for recurrent stroke, and blood pressure (BP) reduction is associated with decreased risk of stroke recurrence. However, hypertension remains poorly controlled in many stroke survivors. Black and Hispanic patients have a higher prevalence of uncontrolled BP and higher rates of stroke. Limited access to care contributes to challenges in post-stroke care. Telehealth After Stroke Care (TASC) is a telehealth intervention that integrates remote BP monitoring (RBPM) including nursing telephone support, tailored BP infographics and telehealth video visits with a multidisciplinary team approach including pharmacy to improve post-stroke care and reduce stroke disparities.

Methods

In this pilot trial, 50 acute stroke patients with hypertension will be screened for inclusion prior to hospital discharge and randomized to usual care or TASC. Usual care patients will be seen by a primary care nurse practitioner at 1–2 weeks and a stroke neurologist at 1 and 3 months. In addition to these usual care visits, TASC intervention patients will see a pharmacist at 4 and 8 weeks and will be enrolled in RBPM consisting of home BP monitoring with interval calls by a centralized team of telehealth nurses. As part of RBPM, TASC patients will be provided with a home BP monitoring device and electronic tablet that wirelessly transmits home BP data to the electronic health record. They will also receive tailored BP infographics that help explain their BP readings. The primary outcome will be feasibility including recruitment, adherence to at least one video visit and retention rates. The clinical outcome for consideration in a subsequent trial will be within-patient change in BP from baseline to 3 months after discharge. Secondary outcomes will be medication adherence self-efficacy and satisfaction with post-stroke telehealth, both measured at 3 months. Additional patient reported outcomes will include depression, cognitive function, and socioeconomic determinants. Multidisciplinary team competency and fidelity measures will also be assessed.

Conclusions

Integrated team-based interventions may improve BP control and reduce racial/ethnic disparities in post-stroke care. TASC is a post-acute stroke care model that is novel in providing RBPM with tailored infographics, and a multidisciplinary team approach including pharmacy. Our pilot will determine if such an approach is feasible and effective in enhancing post-stroke BP control and promoting self-efficacy.

Trial registration

ClinicalTrials.gov NCT04640519

Supplementary Information

The online version contains supplementary material available at 10.1186/s40814-022-01025-z.

Leveraging electronic health record data for clinical trial planning by assessing eligibility criteria's impact on patient count and safety

OBJECTIVE

To present an approach on using electronic health record (EHR) data that assesses how different eligibility criteria, either individually or in combination, can impact patient count and safety (exemplified by all-cause hospitalization risk) and further assist with criteria selection for prospective clinical trials.

MATERIALS AND METHODS

Trials in three disease domains - relapsed/refractory (r/r) lymphoma/leukemia; hepatitis C virus (HCV); stages 3 and 4 chronic kidney disease (CKD) - were analyzed as case studies for this approach. For each disease domain, criteria were identified and all criteria combinations were used to create EHR cohorts. Per combination, two values were derived: (1) number of eligible patients meeting the selected criteria; (2) hospitalization risk, measured as the hazard ratio between those that qualified and those that did not. From these values, k-means clustering was applied to derive which criteria combinations maximized patient counts but minimized hospitalization risk.

RESULTS

Criteria combinations that reduced hospitalization risk without substantial reductions on patient counts were as follows: for r/r lymphoma/leukemia (23 trials; 9 criteria; 623 patients), applying no infection and adequate absolute neutrophil count while forgoing no prior malignancy; for HCV (15; 7; 751), applying no human immunodeficiency virus and no hepatocellular carcinoma while forgoing no decompensated liver disease/cirrhosis; for CKD (10; 9; 23893), applying no congestive heart failure.

CONCLUSIONS

Within each disease domain, the more drastic effects were generally driven by a few criteria. Similar criteria across different disease domains introduce different changes. Although results are contingent on the trial sample and the EHR data used, this approach demonstrates how EHR data can inform the impact on safety and available patients when exploring different criteria combinations for designing clinical trials.

Machine learning-based estimation of cognitive performance using regional brain MRI markers: the Northern Manhattan Study

High dimensional neuroimaging datasets and machine learning have been used to estimate and predict domain-specific cognition, but comparisons with simpler models composed of easy-to-measure variables are limited. Regularization methods in particular may help identify regions-of-interest related to domain-specific cognition. Using data from the Northern Manhattan Study, a cohort study of mostly Hispanic older adults, we compared three models estimating domain-specific cognitive performance: sociodemographics and APOE ε4 allele status (basic model), the basic model and MRI markers, and a model with only MRI markers. We used several machine learning methods to fit our regression models: elastic net, support vector regression, random forest, and principal components regression. Model performance was assessed with the RMSE, MAE, and R² statistics using 5-fold cross-validation. To assess whether prediction models with imaging biomarkers were more predictive than prediction models built with randomly generated biomarkers, we refit the elastic net models using 1000 datasets with random biomarkers and compared the distribution of the RMSE and R² in models using these random biomarkers to the RMSE and R² from observed models. Basic models explained ~ 31-38% of the variance in domain-specific cognition. Addition of MRI markers did not improve estimation. However, elastic net models with only MRI markers performed significantly better than random MRI markers (one-sided P < .05) and yielded regions-of-interest consistent with previous literature and others not previously explored. Therefore, structural brain MRI markers may be more useful for etiological than predictive modeling.

A randomized double-blind controlled trial of convalescent plasma in adults with severe COVID-19

BACKGROUNDAlthough convalescent plasma has been widely used to treat severe coronavirus disease 2019 (COVID-19), data from randomized controlled trials that support its efficacy are limited.METHODSWe conducted a randomized, double-blind, controlled trial among adults hospitalized with severe and critical COVID-19 at 5 sites in New York City (USA) and Rio de Janeiro (Brazil). Patients were randomized 2:1 to receive a single transfusion of either convalescent plasma or normal control plasma. The primary outcome was clinical status at 28 days following randomization, measured using an ordinal scale and analyzed using a proportional odds model in the intention-to-treat population.RESULTSOf 223 participants enrolled, 150 were randomized to receive convalescent plasma and 73 to receive normal control plasma. At 28 days, no significant improvement in the clinical scale was observed in participants randomized to convalescent plasma (OR 1.50, 95% confidence interval [CI] 0.83-2.68, P = 0.180). However, 28-day mortality was significantly lower in participants randomized to convalescent plasma versus control plasma (19/150 [12.6%] versus 18/73 [24.6%], OR 0.44, 95% CI 0.22-0.91, P = 0.034). The median titer of anti-SARS-CoV-2 neutralizing antibody in infused convalescent plasma units was 1:160 (IQR 1:80-1:320). In a subset of nasopharyngeal swab samples from Brazil that underwent genomic sequencing, no evidence of neutralization-escape mutants was detected.CONCLUSIONIn adults hospitalized with severe COVID-19, use of convalescent plasma was not associated with significant improvement in day 28 clinical status. However, convalescent plasma was associated with significantly improved survival. A possible explanation is that survivors remained hospitalized at their baseline clinical status.TRIAL REGISTRATIONClinicalTrials.gov, NCT04359810.FUNDINGAmazon Foundation, Skoll Foundation.

Contemporary use of real-world data for clinical trial conduct in the United States: a scoping review

OBJECTIVE

Real-world data (RWD), defined as routinely collected healthcare data, can be a potential catalyst for addressing challenges faced in clinical trials. We performed a scoping review of database-specific RWD applications within clinical trial contexts, synthesizing prominent uses and themes.

MATERIALS AND METHODS

Querying 3 biomedical literature databases, research articles using electronic health records, administrative claims databases, or clinical registries either within a clinical trial or in tandem with methodology related to clinical trials were included. Articles were required to use at least 1 US RWD source. All abstract screening, full-text screening, and data extraction was performed by 1 reviewer. Two reviewers independently verified all decisions.

RESULTS

Of 2020 screened articles, 89 qualified: 59 articles used electronic health records, 29 used administrative claims, and 26 used registries. Our synthesis was driven by the general life cycle of a clinical trial, culminating into 3 major themes: trial process tasks (51 articles); dissemination strategies (6); and generalizability assessments (34). Despite a diverse set of diseases studied, <10% of trials using RWD for trial process tasks evaluated medications or procedures (5/51). All articles highlighted data-related challenges, such as missing values.

DISCUSSION

Database-specific RWD have been occasionally leveraged for various clinical trial tasks. We observed underuse of RWD within conducted medication or procedure trials, though it is subject to the confounder of implicit report of RWD use.

CONCLUSION

Enhanced incorporation of RWD should be further explored for medication or procedure trials, including better understanding of how to handle related data quality issues to facilitate RWD use.

Clinical comparison between trial participants and potentially eligible patients using electronic health record data: A generalizability assessment method

OBJECTIVE

To present a generalizability assessment method that compares baseline clinical characteristics of trial participants (TP) to potentially eligible (PE) patients as presented in their electronic health record (EHR) data while controlling for clinical setting and recruitment period.

METHODS

For each clinical trial, a clinical event was defined to identify patients of interest using available EHR data from one clinical setting during the trial's recruitment timeframe. The trial's eligibility criteria were then applied and patients were separated into two mutually exclusive groups: (1) TP, which were patients that participated in the trial per trial enrollment data; (2) PE, the remaining patients. The primary outcome was standardized differences in clinical characteristics between TP and PE per trial. A standardized difference was considered prominent if its absolute value was greater than or equal to 0.1. The secondary outcome was the difference in mean propensity scores (PS) between TP and PE per trial, in which the PS represented prediction for a patient to be in the trial. Three diverse trials were selected for illustration: one focused on hepatitis C virus (HCV) patients receiving a liver transplantation; one focused on leukemia patients and lymphoma patients; and one focused on appendicitis patients.

RESULTS

For the HCV trial, 43 TP and 83 PE were found, with 61 characteristics evaluated. Prominent differences were found among 69% of characteristics, with a mean PS difference of 0.13. For the leukemia/lymphoma trial, 23 TP and 23 PE were found, with 39 characteristics evaluated. Prominent differences were found among 82% of characteristics, with a mean PS difference of 0.76. For the appendicitis trial, 123 TP and 242 PE were found, with 52 characteristics evaluated. Prominent differences were found among 52% of characteristics, with a mean PS difference of 0.15.

CONCLUSIONS

Differences in clinical characteristics were observed between TP and PE among all three trials. In two of the three trials, not all of the differences necessarily compromised trial generalizability and subsets of PE could be considered similar to their corresponding TP. In the remaining trial, lack of generalizability appeared present, but may be a result of other factors such as small sample size or site recruitment strategy. These inconsistent findings suggest eligibility criteria alone are sometimes insufficient in defining a target group to generalize to. With caveats in limited scalability, EHR data quality, and lack of patient perspective on trial participation, this generalizability assessment method that incorporates control for temporality and clinical setting promise to better pinpoint clinical patterns and trial considerations.

Comparison of Clinical Characteristics Between Clinical Trial Participants and Nonparticipants Using Electronic Health Record Data

IMPORTANCE

Assessing generalizability of clinical trials is important to ensure appropriate application of interventions, but most assessments provide minimal granularity on comparisons of clinical characteristics.

OBJECTIVE

To assess the extent of underlying clinical differences between clinical trial participants and nonparticipants by using a combination of electronic health record and trial enrollment data.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data obtained from a single academic medical center between September 1996 and January 2019 to identify 1645 clinical trial participants from a diverse set of 202 available trials conducted at the center. Using an aggregated resampling procedure, nonparticipants were matched to participants 1:1 based on trial conditions, number of recent visits to a health care professional, and calendar time.

EXPOSURES

Clinical trial enrollment vs no enrollment.

MAIN OUTCOMES AND MEASURES

The primary outcome was standardized differences in clinical characteristics between participants and nonparticipants in clinical trials stratified into the 4 most common disease domains.

RESULTS

This cross-sectional study included 1645 participants from 202 trials (929 [56.5%] male; mean [SD] age, 54.65 [21.38] years) and an aggregated set of 1645 nonparticipants (855 [52.0%] male; mean [SD] age, 57.24 [21.91] years). The most common disease domains for the selected trials were neoplastic disease (86 trials; 737 participants), disorders of the digestive system (31 trials; 321 participants), inflammatory disorders (28 trials; 276 participants), and disorders of the cardiovascular system (27 trials; 319 participants); trials could qualify for multiple disease domains. Among 31 conditions, the percentage of conditions for which the prevalence was lower among participants than among nonparticipants per standardized differences was 64.5% (20 conditions) for neoplastic disease trials, 61.3% (19) for digestive system trials, 58.1% (18) for inflammatory disorder trials, and 38.7% (12) for cardiovascular system trials. Among 17 medications, the percentage of medications for which use was less among participants than among nonparticipants per standardized differences was 64.7% (11) for neoplastic disease trials, 58.8% (10) for digestive system trials, 88.2% (15) for inflammatory disorder trials, and 52.9% (9) for cardiovascular system trials.

CONCLUSIONS AND RELEVANCE

Using a combination of electronic health record and trial enrollment data, this study found that clinical trial participants had fewer comorbidities and less use of medication than nonparticipants across a variety of disease domains. Combining trial enrollment data with electronic health record data may be useful for better understanding of the generalizability of trial results.

Cholinergic White Matter Lesions, AD-Signature Cortical Thickness, and Change in Cognition: The Northern Manhattan Study

BACKGROUND

How cerebrovascular disease and neurodegeneration affect each other to impact cognition is not yet known. We aimed to test whether Alzheimer's disease-signature (AD) cortical thickness mediates the association between cholinergic white matter lesion load and change in domain-specific cognition.

METHODS

Clinically stroke-free participants from the Northern Manhattan Study with both regional white matter hyperintensity volume (WMHV) and gray matter measurements were included (N = 894). Tract-specific WMHVs were quantified through FSL using the Johns Hopkins University white matter tract atlas. We used Freesurfer 5.1 to estimate regional cortical thickness. We fit structural equation models, including multiple indicator latent change score models, to examine associations between white matter hyperintensity volume (WMHV) in cholinergic tracts, AD-signature region cortical thickness (CT), and domain-specific cognition.

RESULTS

Our sample (N = 894) had a mean (SD) age = 70 (9) years, years of education = 10 (5), 63% women, and 67% Hispanics/Latinos. Greater cholinergic WMHV was significantly related to worse processing speed at baseline (standardized β = -0.17, SE = 0.05, p = .001) and over time (standardized β = -0.28, SE = 0.09, p = .003), with a significant indirect effect of AD-signature region CT (baseline: standardized β = -0.02, SE = 0.01, p = .023; change: standardized β = -0.03, SE = 0.02, p = .040).

CONCLUSIONS

Cholinergic tract WMHV is associated with worse processing speed, both directly and indirectly through its effect on AD-signature region CT.

SMARTAR: an R package for designing and analyzing Sequential Multiple Assignment Randomized Trials

This article introduces an R package, SMARTAR (Sequential Multiple Assignment Randomized Trial with Adaptive Randomization), by which clinical investigators can design and analyze a sequential multiple assignment randomized trial (SMART) for comparing adaptive treatment strategies. Adaptive treatment strategies are commonly used in clinical practice to personalize healthcare in chronic disorder management. SMART is an efficient clinical design for selecting the best adaptive treatment strategy from a family of candidates. Although some R packages can help in adaptive treatment strategies research, they mainly focus on secondary data analysis for observational studies, instead of clinical trials. SMARTAR is the first R package provides functions that can support clinical investigators and data analysts at every step of the statistical work pipeline in clinical trial practice. In this article, we demonstrate how to use this package, using a real data example.

Systolic Blood Pressure and Cognition in the Elderly: The Northern Manhattan Study

BACKGROUND

Increasing evidence suggests that hypertension is a risk factor for cognitive impairment and dementia. The relationship between blood pressure and cognition in a racially and ethnically diverse population remains unclear.

OBJECTIVE

To study association of blood pressure with cognition cross-sectionally and longitudinally in the elderly.

METHODS

Participants are stroke-free individuals from the racially and ethnically diverse Northern Manhattan Study (NOMAS) (n = 1215). General linear models are constructed to examine blood pressure in relation to cognition cross-sectionally and longitudinally at a five-year follow-up.

RESULTS

We found a cross-sectional association of systolic blood pressure (SBP) with word fluency/semantic memory, executive function, and processing speed/visual motor integration (VMI) function. This association was independent of demographics, vascular risk factors, white matter hyperintensity volume (WMHV), and carotid intima-media thickness (cIMT). The cross-sectional association of SBP with processing speed/VMI and executive function was attenuated after adjusting anti-hypertension medications in the models. Baseline SBP was associated with the change of processing speed/VMI function after adjusting vascular risk factors, WMHV, and cIMT at a 5-year follow-up. This longitudinal association was not found after adjusting anti-hypertension medications in the models. Further analyses revealed that individuals with category SBP from < 120 mmHg to≥140 mmHg had a linear decline in processing speed/VMI function at a 5-year follow-up.

CONCLUSION

We show that SBP is negatively associated with cognition cross-sectionally and longitudinally in the elderly. Anti-hypertension treatment eliminates the negative association of SBP with processing speed/VMI function longitudinally. Our findings support the treatment of stage 1 systolic hypertension in the elderly.

Race/Ethnic Disparities in Mild Cognitive Impairment and Dementia: The Northern Manhattan Study

BACKGROUND

Variability in dementia rates across racial and ethnic groups has been estimated at 60%. Studies suggest disparities in Caribbean Hispanic and Black populations, but community-based data are limited.

OBJECTIVE

Estimate the prevalence of mild cognitive impairment (MCI) and dementia in the racially and ethnically diverse community-based Northern Manhattan Study cohort and examine sociodemographic, vascular risk factor, and brain imaging correlates.

METHODS

Cases of MCI and dementia were adjudicated by a team of neuropsychologists and neurologists and prevalence was estimated across race/ethnic groups. Ordinal proportional odds models were used to estimate race/ethnic differences in the prevalence of MCI or dementia adjusting for sociodemographic variables (model 1), model 1 plus potentially modifiable vascular risk factors (model 2), and model 1 plus structural imaging markers of brain integrity (model 3).

RESULTS

There were 989 participants with cognitive outcome determinations (mean age 69±9 years; 68% Hispanic, 16% Black, 14% White; 62% women; mean (±SD) follow-up five (±0.6) years). Hispanic and Black participants had greater likelihood of MCI (20%) and dementia (5%) than White participants accounting for age and education differences. Hispanic participants had greater odds of MCI or dementia than both White and Black participants adjusting for sociodemographic variables, vascular risk factors, and brain imaging factors. White matter hyperintensity burden was significantly associated with greater odds of MCI or dementia (OR = 1.3, 1.1 to 1.6), but there was no significant interaction by race/ethnicity.

CONCLUSION

In this diverse community-based cohort, cross-sectional data revealed significant race/ethnic disparities in the prevalence of MCI and dementia. Longer follow-up and incidence data are needed to further clarify these relationships.

Obesity Measures in Relation to Cognition in the Northern Manhattan Study

BACKGROUND

Mid-life obesity is associated with cognitive impairment, though the relationship for late-life obesity is equivocal, and may depend on the anthropometric measure.

OBJECTIVE

We examined the relationship between adiposity and cognition across age categories, cognitive domains, and by measures of obesity in a multi-ethnic population-based cohort.

METHODS

The study included 1,179 Northern Manhattan Study participants with obesity measures at baseline (44% overweight, 30% obese), an initial neuropsychological assessment conducted within 7 years (mean age = 70), and a second cognitive assessment conducted on average 6 years later. Z-scores were derived for cognitive domains (episodic and semantic memory, executive function, processing speed) and averaged to calculate global cognition. Body mass index (BMI) and waist:hip ratio (WHR) were examined in relation to cognitive performance and change over time, stratified by age, using linear regression models adjusting for vascular risk factors.

RESULTS

Among those age<65 years at baseline, greater WHR was associated with worse global cognitive performance at initial assessment and directly associated with decline in performance between assessments. The association with initial performance was strongest for non-Hispanic Whites (beta = -0.155/standard deviation, p = 0.04), followed by non-Hispanic Black/African Americans (beta = -0.079/standard deviation, p = 0.07), and Hispanics (beta = -0.055/standard deviation, p = 0.03). The associations were most apparent for the domains of processing speed and executive function. There was no association for BMI among those <65 years. Among those age ≥65, there was no association for BMI or WHR with cognitive performance at initial assessment nor decline over time.

CONCLUSION

Our results support the detrimental effect of mid-life rather than later life obesity, particularly abdominal adiposity, on cognitive impairment and decline.

Personalized Policy Learning using Longitudinal Mobile Health Data

Personalized policy represents a paradigm shift from one-decision-rule-for-all users to an individualized decision rule for each user. Developing personalized policy in mobile health applications imposes challenges. First, for lack of adherence, data from each user are limited. Second, unmeasured contextual factors can potentially impact on decision making. Aiming to optimize immediate rewards, we propose using a generalized linear mixed modeling framework where population features and individual features are modeled as fixed and random effects, respectively, and synthesized to form the personalized policy. The group lasso type penalty is imposed to avoid overfitting of individual deviations from the population model. We examine the conditions under which the proposed method work in the presence of time-varying endogenous covariates, and provide conditional optimality and marginal consistency results of the expected immediate outcome under the estimated policies. We apply our method to develop personalized push ("prompt") schedules in 294 app users, with the goal to maximize the prompt response rate given past app usage and other contextual factors. The proposed method compares favorably to existing estimation methods including using the R function "glmer" in a simulation study.

APOE ϵ4 modifies the relationship between infectious burden and poor cognition

OBJECTIVE

We investigated whether APOE ϵ4 is an effect modifier of the association between infectious burden (IB) and poor cognition in a multiethnic cohort, the Northern Manhattan Study.

METHODS

IB was assessed by a quantitative weighted index of exposure to common pathogens associated with vascular risk, infectious burden index (IBI), and by serology for individual infections. Cognition was assessed by completion of the Mini-Mental State Examination at baseline and a full neuropsychological test battery after a median follow-up of approximately 6 years. Adjusted linear and logistic regressions estimated the association between IBI and cognition, with a term included for the interaction between APOE ϵ4 and IBI.

RESULTS

Among those with full neuropsychological test results (n = 569), there were interactions between IBI and APOE ϵ4 (p = 0.07) and herpes simplex virus 1 (HSV-1) and APOE ϵ4 (p = 0.02) for processing speed. IBI was associated with slower processing speed among non-ϵ4 carriers (β = -0.08 per SD change in IBI, 95% confidence interval [CI] -0.16 to -0.01), but not among APOE ϵ4 carriers (β = 0.06 per SD change in IBI, 95% CI -0.08 to 0.19). HSV-1 positivity was associated with slower processing speed among non-ϵ4 carriers (β = -0.24, 95% CI -0.45 to -0.03), but not among APOE ϵ4 carriers (β = 0.27, 95% CI -0.09 to 0.64).

CONCLUSIONS

Potential effect modification by the APOE ϵ4 allele on the relationship of infection, and particularly viral infection, to cognitive processing speed warrants further investigation.

Personal preferences for Personalised Trials among patients with chronic diseases: an empirical Bayesian analysis of a conjoint survey

OBJECTIVE

To describe individual patient preferences for Personalised Trials and to identify factors and conditions associated with patient preferences.

DESIGN

Each participant was presented with 18 conjoint questions via an online survey. Each question provided two choices of Personalised Trials that were defined by up to eight attributes, including treatment types, clinician involvement, study logistics and trial burden on a patient.

SETTING

Online survey of adults with at least two common chronic conditions in the USA.

PARTICIPANTS

A nationally representative sample of 501 individuals were recruited from the Chronic Illness Panel by Harris Poll Online. Participants were recruited from several sources, including emails, social media and telephone recruitment of the target population.

MAIN OUTCOME MEASURES

The choice of Personalised Trial design that the participant preferred with each conjoint question.

RESULTS

There was large variability in participants' preferences for the design of Personalised Trials. On average, they preferred certain attributes, such as a short time commitment and no cost. Notably, a population-level analysis correctly predicted 62% of the conjoint responses. An empirical Bayesian analysis of the conjoint data, which supported the estimation of individual-level preferences, improved the accuracy to 86%. Based on estimates of individual-level preferences, patients with chronic pain preferred a long study duration (p≤0.001). Asthma patients were less averse to participation burden in terms of data-collection frequency than patients with other conditions (p=0.002). Patients with hypertension were more cost-sensitive (p<0.001).

CONCLUSION

These analyses provide a framework for elucidating individual-level preferences when implementing novel patient-centred interventions. The data showed that patient preference in Personalised Trials is highly variable, suggesting that individual differences must be accounted for when marketing Personalised Trials. These results have implications for advancing precise interventions in Personalised Trials by indicating when rigorous scientific principles, such as frequent monitoring, is feasible in a substantial subset of patients.

Distinct trajectories of moderate to vigorous physical activity and sedentary behavior following a breast cancer diagnosis: the Pathways Study

PURPOSE

To identify distinct trajectories of total moderate-to-vigorous physical activity (MVPA) and sedentary behavior following a breast cancer diagnosis and their correlates.

METHODS

The analysis examined 3000 female breast cancer survivors within Kaiser Permanente Northern California between 2006 and 2013. Self-reported time spent on total MVPA and sedentary behaviors were assessed at baseline (mean = 1.8 months post-diagnosis) and at 6 and 24 months follow up. Trajectory groups were identified using group-based trajectory modeling and K-means for longitudinal data analysis. Trajectory groups were named by baseline activity level (high, medium, or low) and direction of change (increaser, decreaser, or maintainer).

RESULTS

Trajectory analyses identified three MVPA trajectories [high decreaser (7%), medium decreaser (35%), low maintainer (58%)] and four sedentary behavior trajectories [high maintainer (18%), high decreaser (27%), low increaser (24%), and low maintainer (31%)]. Women with higher education (ORs: 1.63-4.37), income (OR: 1.37), dispositional optimism (ORs: 1.60-1.86), and social support (OR: 1.33) were more likely to be high or medium decreasers of MVPA (all P < 0.05). High maintainers and high decreasers of sedentary behavior were more likely to have higher education (OR: 1.84) and social support (ORs: 1.42-1.86), but lower income (OR: 0.66; all P < 0.05).

CONCLUSIONS

In the 24 months following breast cancer diagnosis, 42% of survivors decreased MVPA and 73% maintained or increased time on sedentary behavior. Socioeconomic status and stress coping at diagnosis predicted subsequent PA trajectory.

IMPLICATIONS FOR CANCER SURVIVORS

It is important to prioritize exercise intervention and counseling during early stage of breast cancer survivorship, especially in survivors who are at high risk of becoming physically inactive post-diagnosis.

A generalization of functional clustering for discrete multivariate longitudinal data

This paper presents a new model-based generalized functional clustering method for discrete longitudinal data, such as multivariate binomial and Poisson distributed data. For this purpose, we propose a multivariate functional principal component analysis (MFPCA)-based clustering procedure for a latent multivariate Gaussian process instead of the original functional data directly. The main contribution of this study is two-fold: modeling of discrete longitudinal data with the latent multivariate Gaussian process and developing of a clustering algorithm based on MFPCA coupled with the latent multivariate Gaussian process. Numerical experiments, including real data analysis and a simulation study, demonstrate the promising empirical properties of the proposed approach.

Cognitive Impairment Correlates Linearly with Mean Flow Velocity by Transcranial Doppler below a Definable Threshold

INTRODUCTION

Low cerebral blood flow can affect cognition in patients with high-grade asymptomatic internal carotid artery stenosis. Current clinical algorithms use stroke risk to determine which patients should undergo revascularization without considering cognitive decline. Although correlations between low-flow and cognitive impairment have been reported, it is not known whether a threshold exists below which such a correlation expresses itself. Such information would be critical in treatment decisions about whether to intervene in patients with high-grade carotid artery stenosis who are at risk for cognitive decline.

OBJECTIVE

To determine how reduced blood flow correlates with lower cognitive scores.

METHODS

Patients with ≥80% unilateral internal carotid artery stenosis with no history of stroke were recruited from inpatient and outpatient practices at a single, large, comprehensive stroke center. Patients underwent bilateral insonation of middle cerebral arteries with standard 2-Hz probes over the temporal windows with transcranial Doppler. Cognitive assessments were performed by an experienced neuropsychologist using a cognitive battery comprising 14 standardized tests with normative samples grouped by age. Z-scores were generated for each test and averaged to obtain a composite Z-score for each patient. Multivariable linear regression examined associations between mean flow velocity (MFV) and composite Z-score, adjusting for age, education, and depression. The Davies test was used to determine if there was a breakpoint for a non-zero difference in slope of a segmented relationship over the range of composite Z-score values.

RESULTS

Forty-two patients with unilateral high-grade internal carotid artery stenosis without stroke were enrolled (26 males, age = 74 ± 9 years, education = 16 ± 3 years). Average composite Z-score was -0.31 SD below the age-specific normative mean (range -2.8 to +1.2 SD). In linear regression adjusted for age, education, and depression, MFV correlated with cognitive Z-score (β = 0.308, p = 0.043). A single breakpoint in the range of composite Z-scores was identified at 45 cm/s. For MFV <45 cm/s, Z-score decreased 0.05 SD per cm/s MFV (95% CI: 0.01-0.10). For MFV >45 cm/s, Z-score change was nonsignificant (95% CI: -0.07 to 0.05).

CONCLUSIONS

In high-grade, asymptomatic carotid artery stenosis, cognitive impairment correlated linearly with lower flow in the hemisphere fed by the occluded internal carotid artery, but only below a threshold of MFV = 45 cm/s. Identifying a hemodynamic threshold for cognitive decline using a simple, noninvasive method may influence revascularization decision-making in otherwise "asymptomatic" carotid disease.

Ensemble clustering for step data via binning

This paper considers the clustering problem of physical step count data recorded on wearable devices. Clustering step data give an insight into an individual's activity status and further provide the groundwork for health-related policies. However, classical methods, such as K-means clustering and hierarchical clustering, are not suitable for step count data that are typically high-dimensional and zero-inflated. This paper presents a new clustering method for step data based on a novel combination of ensemble clustering and binning. We first construct multiple sets of binned data by changing the size and starting position of the bin, and then merge the clustering results from the binned data using a voting method. The advantage of binning, as a critical component, is that it substantially reduces the dimension of the original data while preserving the essential characteristics of the data. As a result, combining clustering results from multiple binned data can provide an improved clustering result that reflects both local and global structures of the data. Simulation studies and real data analysis were carried out to evaluate the empirical performance of the proposed method and demonstrate its general utility.

Race and Ethnic Disparities in Stroke Incidence in the Northern Manhattan Study

Background and Purpose- An excess incidence of strokes among blacks versus whites has been shown, but data on disparities related to Hispanic ethnicity remain limited. This study examines race/ethnic differences in stroke incidence in the multiethnic, largely Caribbean Hispanic, NOMAS (Northern Manhattan Study), and whether disparities vary by age. Methods- The study population included participants in the prospective population-based NOMAS, followed for a mean of 14±7 years. Multivariable-adjusted Cox proportional hazards models were constructed to estimate the association between race/ethnicity and incident stroke of any subtype and ischemic stroke, stratified by age. Results- Among 3298 participants (mean baseline age 69±10 years, 37% men, 24% black, 21% white, 52% Hispanic), 460 incident strokes accrued (400 ischemic, 43 intracerebral hemorrhage, 9 subarachnoid hemorrhage). The most common ischemic subtype was cardioembolic, followed by lacunar infarcts, then cryptogenic. The greatest incidence rate was observed in blacks (13/1000 person-years), followed by Hispanics (10/1000 person-years), and lowest in whites (9/1000 person-years), and this order was observed for crude incidence rates until age 75. By age 85, the greatest incidence rate was in Hispanics. Blacks had an increased risk of stroke versus whites overall in multivariable models that included sociodemographics (hazard ratio, 1.51 [95% CI, 1.13-2.02]), and stratified analyses showed that this disparity was driven by women of age ≥70. The increased rate of stroke among Hispanics (age/sex-adjusted hazard ratio, 1.48 [95% CI, 1.13-1.93]) was largely explained by education and insurance status (a proxy for socieoeconomic status; hazard ratio after further adjusting for these variables, 1.17 [95% CI, 0.85-1.62]) but remained significant for women age ≥70. Conclusions- This study provides novel data regarding the increased stroke risk among Caribbean Hispanics in this elderly population. Results highlight the need to create culturally tailored campaigns to reach black and Hispanic populations to reduce race/ethnic stroke disparities and support the important role of low socioeconomic status in driving an elevated risk among Caribbean Hispanics.

Abstract 90: Race, Ethnic, and Sex Disparities in Stroke Incidence in the Northern Manhattan Study

Background: An excess incidence of strokes among blacks vs whites has been shown previously, but data on disparities related to Hispanic ethnicity remains limited. This study examines race, ethnic, and sex differences in stroke incidence in the multi-ethnic, yet largely Caribbean Hispanic, Northern Manhattan Study (NOMAS).

Methods: The study population included participants in the prospective population-based NOMAS, followed for a mean of 13±7 years. Cox proportional hazards models were constructed to estimate the hazard ratios and 95% confidence intervals (HR, 95%CI) for the association between race/ethnicity and sex with confirmed incident stroke of any subtype and ischemic stroke, stratified by age and adjusting for sociodemographics and vascular risk factors.

Results: Among 3,298 participants (mean baseline age 69±10, 37% men, 24% black, 21% white, 52% Hispanic), 477 incident strokes accrued (394 ischemic, 43 ICH, 9 SAH). The most common ischemic subtype was cardioembolic, followed by lacunar infarcts, then cryptogenic. The greatest incidence rate was observed in blacks (13/1000 person-years [PY]), followed by Hispanics (11/1000 PY), and lowest in whites (8/1000 PY), and this order was observed for crude incidence rates until age 75. By age 85 the greatest incidence rate was in Hispanics. Blacks had an increased stroke risk vs whites overall in fully adjusted models (HR=1.37, 95% CI=1.02-1.84), and stratified analyses showed that this disparity was driven by women age ≥70 (HR=1.69, 1.05-2.73). The increased rate of stroke observed for Hispanics (age/sex-adjusted HR=1.50, 1.15-1.94) was largely explained by education and insurance status (a proxy for socieoeconomic status; HR after further adjusting for these variables=1.15, 0.84-1.58), but remained significant for women age ≥70. Men had an increased rate of stroke compared to women (fully adjusted HR=1.48, 1.21-1.81).

Conclusions: This study provides novel data regarding the increased stroke risk among Caribbean Hispanics. Results highlight the need to create culturally-tailored campaigns to reach blacks and Hispanic populations to reduce race/ethnic stroke disparities, and support the important role of low socioeconomic status in driving an elevated risk among Caribbean Hispanics.

Diastolic Blood Pressure Is Associated With Regional White Matter Lesion Load: The Northern Manhattan Study

Background and Purpose- Few studies have examined the separate contributions of systolic blood pressure and diastolic blood pressures (DBP) on subclinical cerebrovascular disease, especially using the 2017 American College of Cardiology/American Heart Association Blood Pressure Guidelines. Furthermore, associations with region-specific white matter hyperintensity volume (WMHV) are underexplored. Methods- Using data from the NOMAS (Northern Manhattan Study), a prospective cohort study of stroke risk and cognitive aging, we examined associations between systolic blood pressure and DBP, defined by the 2017 American College of Cardiology/American Heart Association guidelines, with regional WMHV. We used a linear mixed model approach to account for the correlated nature of regional brain measures. Results- The analytic sample (N=1205; mean age 64±8 years) consisted of 61% women and 66% Hispanics/Latinos. DBP levels were significantly related to WMHV differentially across regions (P for interaction<0.05). Relative to those with DBP 90+ mm Hg, participants with DBP <80 mm Hg had 13% lower WMHV in the frontal lobe (95% CI, -21% to -3%), 11% lower WMHV in the parietal lobe (95% CI, -19% to -1%), 22% lower WMHV in the anterior periventricular region (95% CI, -30% to -14%), and 16% lower WMHV in the posterior periventricular region (95% CI, -24% to -6%). Participants with DBP 80 to 89 mm Hg also exhibited about 12% (95% CI, -20% to -3%) lower WMHV in the anterior periventricular region and 9% (95% CI, -18% to -0.4%) lower WMHV in the posterior periventricular region, relative to participants with DBP 90≥ mm Hg. Post hoc pairwise t tests showed that estimates for periventricular WMHV were significantly different from estimates for temporal WMHV (Holms stepdown-adjusted P<0.05). Systolic blood pressure was not strongly related to regional WMHV. Conclusions- Lower DBP levels, defined by the 2017 American College of Cardiology/American Heart Association guidelines, were related to lower white matter lesion load, especially in the periventricular regions relative to the temporal region.

Effect of Depression Screening After Acute Coronary Syndromes on Quality of Life: The CODIACS-QoL Randomized Clinical Trial

IMPORTANCE

Patients with acute coronary syndrome (ACS) and elevated depressive symptoms are at increased risk for recurrent cardiovascular events and mortality, worse quality of life, and higher health care costs. These observational findings prompted multiple scientific panels to advise universal depression screening in survivors of ACS prior to evidence from randomized screening trials.

OBJECTIVE

To determine whether systematically screening for depression in survivors of ACS improves quality of life and depression compared with usual care.

DESIGN, SETTING, AND PARTICIPANTS

A 3-group multisite randomized trial enrolled 1500 patients with ACS from 4 health care systems between November 1, 2013, and March 31, 2017, with follow-up ending July 31, 2018. Patients were eligible if they had been hospitalized for ACS in the previous 2 to 12 months and had no prior history of depression. All analyses were performed on an intention-to-treat basis.

INTERVENTIONS

Patients with ACS were randomly assigned 1:1:1 to receive (1) systematic depression screening using the 8-item Patient Health Questionnaire, with notification of primary care clinicians and provision of centralized, patient-preference, stepped depression care for those with positive screening results (8-item Patient Health Questionnaire score ≥10; screen, notify, and treat, n = 499); (2) systematic depression screening, with notification of primary care clinicians for those with positive screening results (screen and notify, n = 501); and (3) usual care (no screening, n = 500).

MAIN OUTCOMES AND MEASURES

The primary outcome was change in quality-adjusted life-years. The secondary outcome was depression-free days. Adverse effects and mortality were assessed by patient interview and hospital records.

RESULTS

A total of 1500 patients (424 women and 1076 men; mean [SD] age, 65.9 [11.5] years) were randomized in the 18-month trial. Only 71 of 1000 eligible survivors of ACS (7.1%) had elevated 8-item Patient Health Questionnaire scores indicating depressive symptoms at screening. There were no differences in mean (SD) change in quality-adjusted life-years (screen, notify and treat, -0.06 [0.20]; screen and notify, -0.06 [0.20]; no screen, -0.06 [0.18]; P = .98) or cumulative mean (SD) depression-free days (screen, notify and treat, 343.1 [179.0] days; screen and notify, 351.3 [175.0] days; no screen, 339.0 [176.6] days; P = .63). Harms including death, bleeding, or sleep difficulties did not differ among groups.

CONCLUSIONS AND RELEVANCE

In patients with ACS without a history of depression, systematic depression screening with or without providing depression treatment did not alter quality-adjusted life-years, depression-free days, or harms.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01993017.

Distinct trajectories of fruits and vegetables, dietary fat, and alcohol intake following a breast cancer diagnosis: the Pathways Study

PURPOSE

To identify distinct diet trajectories after breast cancer (BC) diagnosis, and to examine the characteristics associated with diet trajectories.

METHODS

We analyzed 2865 Pathways Study participants who completed ≥ 2 food frequency questionnaires at the time of BC diagnosis (baseline), and at 6 and 24 months after baseline. Trajectory groups of fruit and vegetable (F/V) intake, % calories from dietary fat, and alcohol intake over 24 months were identified using group-based trajectory modeling. Associations between diet trajectories and sociodemographic, psychosocial, and clinical factors were analyzed using multinomial logistic regression.

RESULTS

Analyses identified 3 F/V trajectory groups, 4 dietary fat groups, and 3 alcohol groups. All 3 F/V trajectory groups reported slightly increased F/V intake post-diagnosis (mean increase = 0.2-0.5 serving/day), while 2 groups (48% of participants) persistently consumed < 4 servings/day of F/V. Dietary fat intake did not change post-diagnosis, with 45% of survivors maintaining a high-fat diet (> 40% of calories from fat). While most survivors consumed < 1 drink/day of alcohol at all times, 21% of survivors had 1.4-3.0 drinks/day at baseline and temporarily decreased to 0.1-0.5 drinks/day at 6 months. In multivariable analysis, diet trajectory groups were significantly associated with education (ORs: 1.93-2.49), income (ORs: 1.32-2.57), optimism (ORs: 1.93-2.49), social support (OR = 1.82), and changes in physical well-being (ORs: 0.58-0.61) and neuropathy symptoms after diagnosis (ORs: 1.29-1.66).

CONCLUSIONS

Pathways Study participants reported slightly increasing F/V and decreasing alcohol intake after BC diagnosis. Nearly half of survivors consumed insufficient F/V and excessive dietary fat. It is important to prioritize nutrition counseling and education in BC survivors.

N-of-1 Randomized Intervention Trials in Health Psychology: A Systematic Review and Methodology Critique

Background

Single-patient, multiple cross-over designs (N-of-1 or single-case randomized clinical trials) with systematic data collection on treatment effects may be useful for increasing the precision of treatments in health psychology.

Purposes

To assess the quality of the methods and statistics, describe interventions and outcomes, and explore the heterogeneity of treatment effect of health psychology N-of-1 trials.

Methods

We conducted a systematic review of N-of-1 trials from electronic database inception through June 1, 2015. Potentially relevant articles were identified by searching the biomedical electronic databases Ovid, MEDLINE, EMBASE, all six databases in the Cochrane Library, CINAHL, and PsycINFO, and conference proceedings, dissertations, ongoing studies, Open Grey, and the New York Academy's Grey Literature Report. Studies were included if they had health behavior or psychological outcomes and the order of interventions was randomized. We abstracted study characteristics and analytic methods and used the Consolidated Standards of Reporting Trials extension for reporting N-of-1 trials as a quality checklist.

Results

Fifty-four N-of-1 trial publications composed of 1,193 participants were included. Less than half of these (36%) reported adequate information to calculate the heterogeneity of treatment effect. Nearly all (90%) provided some quantitative information to determine the superior treatment; 79% used an a priori statistical cutoff, 12% used a graph, and 10% used a combination.

Conclusions

N-of-1 randomized trials could be the next major advance in health psychology for precision therapeutics. However, they must be conducted with more methodologic and statistical rigor and must be transparently and fully reported.

Optimizing Hippocampal-Cortical Network Modulation via Repetitive Transcranial Magnetic Stimulation: A Dose-Finding Study Using the Continual Reassessment Method

OBJECTIVE

Repetitive transcranial magnetic stimulation (rTMS) can cause potentially useful changes in brain functional connectivity (FC), but the number of treatment sessions required is unknown. We applied the continual reassessment method (CRM), a Bayesian, adaptive, dose-finding procedure to a rTMS paradigm in an attempt to answer this question.

MATERIALS AND METHODS

The sample size was predetermined at 15 subjects and the cohort size was set with three individuals (i.e., five total cohorts). In a series of consecutive daily sessions, we delivered rTMS to the left posterior parietal cortex and measured resting-state FC with fMRI in a predefined hippocampal network in the left hemisphere. The session number for each successive cohort was determined by the CRM algorithm. We set a response criterion of a 0.028 change in FC between the hippocampus and the parietal cortex, which was equal to the increase seen in 87.5% of participants in a previous study using five sessions.

RESULTS

A ≥criterion change was observed in 9 of 15 participants. The CRM indicated that greater than four sessions are required to produce the criterion change reliably in future studies.

CONCLUSIONS

The CRM can be adapted for rTMS dose finding when a reliable outcome measure, such as FC, is available. The minimum effective dose needed to produce a criterion increase in FC in our hippocampal network of interest at 87.5% efficacy was estimated to be greater than four sessions. This study is the first demonstration of a Bayesian, adaptive method to explore a rTMS parameter.

Early-Phase Platform Trials: A New Paradigm for Dose Finding and Treatment Screening in the Era of Precision Oncology

Applications in early-phase cancer trials have motivated the development of many statistical designs since the late 1980s, including dose-finding methods, futility screening, treatment selection, and early stopping rules. These methods are often proposed to address the conventional cytotoxic therapeutics for neoplastic diseases and cancer. Recent advances in precision medicine have motivated novel trial designs, most notably the idea of master protocol (eg, platform trial, basket trial, umbrella trial, N-of-1 trial), for the evaluation of molecularly targeted cancer therapies. In this article, we review the concepts and methodology of early-phase cancer trial designs with a focus on dose finding and treatment screening and put these methods in the context of platform trials of molecularly targeted cancer therapies. Because most cancer trial designs have been developed for cytotoxic agents, we will discuss how these time-tested design principles hold relevance for targeted cancer therapies, and we will delineate how a master protocol may serve as an efficient platform for safety and efficacy evaluations of novel targeted therapies.

Dose-finding designs for cumulative toxicities using multiple constraints

This article addresses the concern regarding late-onset dose-limiting toxicities (DLT), moderate toxicities below the threshold of a DLT and cumulative toxicities that may lead to a DLT, which are mostly disregarded or handled in an ad hoc manner when determining the maximum tolerated dose (MTD) in dose-finding cancer clinical trials. An extension of the Time-to-Event Continual Reassessment Method (TITE-CRM) which allows for the specification of toxicity constraints on both DLT and moderate toxicities, and can account for partial information is proposed. The method is illustrated in the context of an Erlotinib dose-finding trial with low DLT rates, but a significant number of moderate toxicities leading to treatment discontinuation in later cycles. Based on simulations, our method performs well at selecting the dose level that satisfies both the DLT and moderate-toxicity constraints. Moreover, it has similar probability of correct selection compared to the TITE-CRM when the true MTD based on DLT only and the true MTD based on grade 2 or higher toxicities alone coincide, but reduces the probability of recommending a dose above the MTD.

Measures of obesity are associated with MRI markers of brain aging: The Northern Manhattan Study

OBJECTIVE

To examine associations between measures of obesity in middle to early-old age with later-life MRI markers of brain aging.

METHODS

We analyzed data from the Northern Manhattan MRI Sub-Study (n = 1,289). Our exposures of interest were body mass index (BMI), waist circumference (WC), waist-to-hip ratio, and plasma adiponectin levels. Our outcomes of interest were total cerebral volume (TCV), cortical thickness, white matter hyperintensity volume (WMHV), and subclinical brain infarcts (SBI). Using multivariable linear and logistic regression models adjusted for sociodemographics, health behaviors, and vascular risk factors, we estimated β coefficients (or odds ratios) and 95% confidence intervals (CIs) and tested interactions with age, sex, and race/ethnicity.

RESULTS

On average at baseline, participants were aged 64 years and had 10 years of education; 60% were women and 66% were Caribbean Hispanic. The mean (SD) time lag between baseline and MRI was 6 (3) years. Greater BMI and WC were significantly associated with thinner cortices (BMI β [95% CI] -0.089 [-0.153, -0.025], WC β [95% CI] -0.103 [-0.169, -0.037]) in fully adjusted models. Similarly, compared to those with BMI <25, obese participants (BMI ≥30) exhibited smaller cortical thickness (β [95% CI] -0.207 [-0.374, -0.041]). These associations were particularly evident for those aged <65 years. Similar but weaker associations were observed for TCV. Most associations with WMHV and SBI did not reach statistical significance.

CONCLUSIONS

Adiposity in early-old age is related to reduced global gray matter later in life in this diverse sample. Future studies are warranted to elucidate causal relationships and explore region-specific associations.

Types of Sedentary Behavior and Risk of Cardiovascular Events and Mortality in Blacks: The Jackson Heart Study

Background

Previous cross‐sectional studies have shown conflicting results regarding the effects of television viewing and occupational sitting on cardiovascular disease (CVD) risk factors. The purpose of this study was to compare the association of both television viewing and occupational sitting with CVD events and all‐cause mortality in blacks.

Methods and Results

Participants included 3592 individuals enrolled in the Jackson Heart Study, a community‐based study of blacks residing in Jackson, Mississippi. Television viewing (<2, 2–4, and >4 h/day) and occupational sitting (never/seldom, sometimes, often/always) were self‐reported. Over a median follow‐up of 8.4 years, there were 129 CVD events and 205 deaths. The highest category of television viewing (>4 h/day) was associated with a greater risk for a composite CVD events/all‐cause mortality end point compared with the lowest category (<2 h/day; hazard ratio, 1.49; 95% CI, 1.13–1.97). In contrast, the highest category of occupational sitting (often/always) was not associated with risk for a composite CVD events/all‐cause mortality end point compared with the lowest category (never/seldom; hazard ratio, 0.90; 95% CI, 0.69–1.18). Moderate‐to‐vigorous physical activity moderated the association of television viewing with CVD events/all‐cause mortality such that television viewing was not associated with greater risk among those with high moderate‐to‐vigorous physical activity levels.

Conclusions

Television viewing was associated with greater risk of CVD events and all‐cause mortality, while occupational sitting had no association with these outcomes. These findings suggest that minimizing television viewing may be more effective for reducing CVD and mortality risk in blacks compared with reducing occupational sedentary behavior.