Current issues in dose-finding designs: A response to the US Food and Drug Adminstration'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.

Adaptive evaluation of mHealth and conventional adherence support interventions to optimize outcomes with new treatment regimens for drug-resistant tuberculosis and HIV in South Africa (ADAP-TIV): study protocol for an adaptive randomized controlled trial.

BACKGROUND: Highly effective, short-course, bedaquiline-containing treatment regimens for multidrug-resistant tuberculosis (MDR-TB) and integrase strand transfer inhibitor (INSTI)-containing fixed dose combination antiretroviral therapy (ART) have radically transformed treatment for MDR-TB and HIV. However, without advances in adherence support, we may not realize the full potential of these therapeutics. The primary objective of this study is to compare the effect of adherence support interventions on clinical and biological endpoints using an adaptive randomized platform. METHODS: This is a prospective, adaptive, randomized controlled trial comparing the effectiveness of four adherence support strategies on a composite clinical outcome in adults with MDR-TB and HIV initiating bedaquiline-containing MDR-TB treatment regimens and receiving ART in KwaZulu-Natal, South Africa. Trial arms include (1) enhanced standard of care, (2) psychosocial support, (3) mHealth using cellular-enabled electronic dose monitoring, and (4) combined mHealth and psychosocial support. The level of support will be titrated using a differentiated service delivery (DSD)-informed assessment of treatment support needs. The composite primary outcome will include survival, negative TB culture, retention in care, and undetectable HIV viral load at month 12. Secondary outcomes will include individual components of the primary outcome and quantitative evaluation of adherence on TB and HIV treatment outcomes. DISCUSSION: This trial will evaluate the contribution of different modes of adherence support on MDR-TB and HIV outcomes with WHO-recommended all-oral MDR-TB regimens and ART in a high-burden operational setting. We will also assess the utility of a DSD framework to pragmatically adjust levels of MDR-TB and HIV treatment support. TRIAL REGISTRATION: ClinicalTrials.gov NCT05633056. Registered on 1 December 2022.

A Series of Personalized Virtual Light Therapy Interventions for Fatigue: Feasibility Randomized Crossover Trial for N-of-1 Treatment.

BACKGROUND: Fatigue is one of the most common symptoms treated in primary care and can lead to deficits in mental health and functioning. Light therapy can be an effective treatment for symptoms of fatigue; however, the feasibility, scalability, and individual-level heterogeneity of light therapy for fatigue are unknown. OBJECTIVE: This study aimed to evaluate the feasibility, acceptability, and effectiveness of a series of personalized (N-of-1) interventions for the virtual delivery of bright light (BL) therapy and dim light (DL) therapy versus usual care (UC) treatment for fatigue in 60 participants. METHODS: Participants completed satisfaction surveys comprising the System Usability Scale (SUS) and items assessing satisfaction with the components of the personalized trial. Symptoms of fatigue were measured using the Patient-Reported Outcomes Measurement Information System (PROMIS) daily, PROMIS weekly, and ecological momentary assessment (EMA) questionnaires delivered 3 times daily. Comparisons of fatigue between the BL, DL, and UC treatment periods were conducted using generalized linear mixed model analyses between participants and generalized least squares analyses within individual participants. RESULTS: Participants rated the usability of the personalized trial as acceptable (average SUS score=78.9, SD 15.6), and 92% (49/53) of those who completed satisfaction surveys stated that they would recommend the trial to others. The levels of fatigue symptoms measured using the PROMIS daily fatigue measure were lower or improved in the BL (B=-1.63, 95% CI -2.63 to -0.63) and DL (B=-1.44, 95% CI -2.50 to -0.38) periods relative to UC. The treatment effects of BL and DL on the PROMIS daily measure varied among participants. Similar findings were demonstrated for the PROMIS weekly and EMA measures of fatigue symptoms. CONCLUSIONS: The participant scores on the SUS and satisfaction surveys suggest that personalized N-of-1 trials of light therapy for fatigue symptoms are both feasible and acceptable. Both interventions produced significant (P<.05) reductions in participant-reported PROMIS and EMA fatigue symptoms relative to UC. However, the heterogeneity of these treatment effects across participants indicated that the effect of light therapy was not uniform. This heterogeneity along with high ratings of usability and satisfaction support the use of personalized N-of-1 research designs in evaluating the effect of light therapy on fatigue for each patient. Furthermore, the results of this trial provide additional support for the use of a series of personalized N-of-1 research trials. TRIAL REGISTRATION: ClinicalTrials.gov NCT04707846; https://clinicaltrials.gov/ct2/show/NCT04707846.

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.

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.

Protocol of a feasibility study of a virtual personalized (N-of-1) trial for increasing low-intensity physical activity in older adults via habit formation.

Background: Personalized interventions that can be delivered remotely are needed to increase physical activity (PA) in older adults to reduce risk of CV disease and mortality. Prior research indicates that Behavioral Change Techniques (BCTs) (e.g., goal setting, self-monitoring, behavioral repetition) can instill a habit for increasing daily walking. However, past interventions relied on between-subject randomized clinical trials, which can only only be informative about response of the hypothetical average person. Personalized trial designs can identify the benefits of an intervention for a specific individual although extended periods are required for collecting frequent measurements within-subject. Advances in remote, virtual technologies (e.g., text messaging, activity trackers), integrated with automatic platforms, can meet these requirements because they capacitate delivery of BCT interventions, and collection of data during daily life without personal contact. This Stage I-b trial is designed test whether a virtual, personalized intervention is feasible and acceptable to older adults, can elicit participant adherence and exhibit preliminary evidence for efficacy. Methods: A series of up to 60 single-arm, personalized trials, involving no personal contact, will recruit adults, 45-75 years of age, to wear an activity tracker during a 2-week baseline and a 10-week intervention. Five BCT prompts to execute a walking plan will be delivered on a daily basis during the intervention phase. Participants will rate satisfaction with personalized trial components and whether automaticity of the walking plan can be achieved. Step-counts, adherence to the walking plan and self-monitoring of step-count will also be recorded.

The effect of a multi-component behavior change technique intervention on physical activity among individuals on primary prevention statin therapy: A dose-finding trial protocol.

BACKGROUND: Statin therapy is a mainstay of cardiovascular disease (CVD) prevention, but research shows that statin therapy alone is insufficient for preventing incident CVD and mortality. Combining statin medication with increased physical activity (PA) can lower mortality risk more than either statin or PA alone. However, PA levels often remain the same and may even decline following statin prescription. Additional information is needed to identify how to increase PA among statin users and determine the minimal length of an intervention (i.e., intervention dose) necessary to increase PA. OBJECTIVE: The study aims to identify the required dose of a behavior change technique (BCT) intervention to increase PA among individuals on primary prevention statin therapy who have an elevated risk for cardiovascular disease (CVD). METHODS: The study will utilize the modified time-to-event continual reassessment method (TiTE-CRM) in 42 participants. We expect insights relating to dose-efficacy models and BCTs (Behavior Change Techniques) to improve PA in adults at risk for CVD. This trial will also examine potential mechanisms of action (MoAs) for interventions to increase PA, identify any effect a PA intervention may have on medication adherence, and determine whether participants respond uniformly to their respective behavioral interventions. ETHICS AND DISSEMINATION: This trial was approved by the Northwell Health Institutional Review Board (IRB) and all participants will complete informed consent. The trial results will be published in a peer-reviewed journal. All publications resulting from this series of personalized trials will follow the CONSORT reporting guidelines. REGISTRATION DETAILS: This trial is registered on www. CLINICALTRIALS: gov (Number NCT05273723).

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.

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.

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.

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.

Feasibility Test of Personalized (N-of-1) Trials for Increasing Middle-Aged and Older Adults' Physical Activity.

Purpose: To test the feasibility of a remotely-delivered intervention to increase low-intensity physical activity (walking) in middle-aged and older adults. Design: This study used a Personalized (N-of-1) trial design. Setting: This study took place at a major healthcare system from November 2021 to February 2022. Subjects: Sixty adults (45-75 years, 92% female, 80% white) were recruited. Intervention: A 10-week study comprising a 2-week baseline, followed by four 2-week periods where 4 Behavior Change Techniques (BCTs) - self-monitoring, goal setting, action planning and feedback - were delivered one at a time in random order. Measures: Activity was measured by a Fitbit, and intervention components delivered by email/text. Average daily steps were compared between baseline and intervention. Participants completed satisfaction items derived from the System Usability Scale and reported attitudes and opinions about personalized trials. Results: Participants rated personalized trial components as feasible and acceptable. Changes in steps between baseline and intervention were not significant, but a large heterogeneity of treatment effects existed, suggesting some participants significantly increased walking while others significantly decreased. Conclusions: Our intervention was well-accepted but use of BCTs delivered individually did not result in a significant increase in steps. Feasibility and heterogeneity of treatment effects support adopting a personalized trial approach to optimize intervention results.

STATISTICAL INFERENCE IN QUANTILE REGRESSION FOR ZERO-INFLATED OUTCOMES.

An extension of quantile regression is proposed to model zero-inflated outcomes, which have become increasingly common in biomedical studies. The method is flexible enough to depict complex and nonlinear associations between the covariates and the quantiles of the outcome. We establish the theoretical properties of the estimated quantiles, and develop inference tools to assess the quantile effects. Extensive simulation studies indicate that the novel method generally outperforms existing zero-inflated approaches and the direct quantile regression in terms of the estimation and inference of the heterogeneous effect of the covariates. The approach is applied to data from the Northern Manhattan Study to identify risk factors for carotid atherosclerosis, measured by the ultrasound carotid plaque burden.

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.

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.

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.

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.

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.