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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Increasing the Precision of Hypertension Treatment Through Personalized Trials: a Pilot Study.

BACKGROUND: There are substantial differences in the effects of blood pressure (BP) medications in individual patients. Yet, the current standard approach to prescribing BP medications is not personalized. OBJECTIVE: To determine the feasibility of individualizing the selection of BP medications through pragmatic personalized (i.e., N-of-1) trials. DESIGN: Series of N-of-1 trials. SETTING: Outpatient. PATIENTS: Hypertensive adults prescribed none or one BP medication. INTERVENTION: Participation in a flexible, open-label personalized trial of two to three BP medications (NCT02744456). MEASUREMENTS: BP was measured twice per day with a validated home BP device. Frequency and severity of side effects were assessed at the end of the day via an electronic questionnaire. Patients' BP medication preference was assessed after reviewing BP lowering and side effect results with a study clinician. Feasibility was assessed by determining the proportion of patients who adhered to self-assessments. Benefit was assessed by asking patients to rate the helpfulness of participation and whether they would recommend personalized trials to other hypertensive patients. KEY RESULTS: Of ten patients enrolled, two dropped out prior to initiation, one discovered white coat hypertension through ambulatory BP monitoring, and seven (mean age 58 years, 71% of women) completed personalized trials. All seven were compliant with home BP monitoring and side effect tracking. All seven recommended personalized trials of BP medications to others. Thiazides were preferred by three patients, renin-angiotensin system-blocking agents by two patients, a combination of thiazide and beta-blocker by one patient, and any of three classes by one patient. CONCLUSIONS: Personalized trials of BP medications were feasible and led to improved treatment precision. Heterogeneity of patient preferences and of therapeutic BP response for first-line BP medications can be determined through a personalized trial approach.

Functional Trajectories, Cognition, and Subclinical Cerebrovascular Disease.

BACKGROUND AND PURPOSE: Cognition and education influence functional trajectories, but whether associations differ with subclinical brain infarcts (SBI) or white matter hyperintensity volume (WMHV) is unknown. We hypothesized that SBI and WMHV moderated relationships between cognitive performance and education and functional trajectories. METHODS: A total of 1290 stroke-free individuals underwent brain magnetic resonance imaging and were followed for 7.3 years (mean) with annual functional assessments with the Barthel index (range, 0-100). Magnetic resonance imaging measurements included pathology-informed SBI (PI-SBI) and WMHV (% total cranial volume). Generalized estimating equation models tested associations between magnetic resonance imaging variables and baseline Barthel index and change in Barthel index, adjusting for demographic, vascular, cognitive, and social risk factors, and stroke and myocardial infarction during follow-up. We tested interactions among education level, baseline cognitive performance (Mini-Mental State score), and functional trajectories and ran models stratified by levels of magnetic resonance imaging variables. RESULTS: Mean age was 70.6 (SD, 9.0) years; 19% had PI-SBI, and mean WMHV was 0.68%. Education did not modify associations between cognition and functional trajectories. PI-SBI modified associations between cognition and functional trajectories (P=0.04) with a significant protective effect of better cognition on functional decline seen only in those without PI-SBI. There was no significant interaction for WMHV (P=0.8). PI-SBI, and greater WMHV, were associated with 2- to 3-fold steeper functional decline, holding cognition constant. CONCLUSIONS: PI-SBI moderated the association between cognition and functional trajectories, with 3-fold greater decline among those with PI-SBI (compared with no PI-SBI) and normal baseline cognition. This highlights the strong and independent association between subclinical markers and patient-centered trajectories over time.

Cerebral white matter disease and functional decline in older adults from the Northern Manhattan Study: A longitudinal cohort study.

BACKGROUND: Cerebral white matter hyperintensities (WMHs) on MRI are common and associated with vascular and functional outcomes. However, the relationship between WMHs and longitudinal trajectories of functional status is not well characterized. We hypothesized that whole brain WMHs are associated with functional decline independently of intervening clinical vascular events and other vascular risk factors. METHODS AND FINDINGS: In the Northern Manhattan Study (NOMAS), a population-based racially/ethnically diverse prospective cohort study, 1,290 stroke-free individuals underwent brain MRI and were followed afterwards for a mean 7.3 years with annual functional assessments using the Barthel index (BI) (range 0-100) and vascular event surveillance. Whole brain white matter hyperintensity volume (WMHV) (as percentage of total cranial volume [TCV]) was standardized and treated continuously. Generalized estimating equation (GEE) models tested associations between whole brain WMHV and baseline BI and change in BI, adjusting for sociodemographic, vascular, and cognitive risk factors, as well as stroke and myocardial infarction (MI) occurring during follow-up. Mean age was 70.6 (standard deviation [SD] 9.0) years, 40% of participants were male, 66% Hispanic; mean whole brain WMHV was 0.68% (SD 0.84). In fully adjusted models, annual functional change was -1.04 BI points (-1.20, -0.88), with -0.74 additional points annually per SD whole brain WMHV increase from the mean (-0.99, -0.49). Whole brain WMHV was not associated with baseline BI, and results were similar for mobility and non-mobility BI domains and among those with baseline BI 95-100. A limitation of the study is the possibility of a healthy survivor bias, which would likely have underestimated the associations we found. CONCLUSIONS: In this large population-based study, greater whole brain WMHV was associated with steeper annual decline in functional status over the long term, independently of risk factors, vascular events, and baseline functional status. Subclinical brain ischemic changes may be an independent marker of long-term functional decline.

Estimating global treatment toxicity burden from adverse-event data.

BACKGROUND: A summary measure that reflects the global toxicity burden of a treatment is essential for comparing therapies. Current toxicity summaries are ad hoc and do not distinguish among the severities and types of toxicities. Here a clinically feasible method for estimating the toxicity burden, based on a prospective evaluation of the toxicity profile of a randomized clinical trial of 746 prostate cancer patients conducted by SWOG, is proposed. METHODS: For 308 patients who experienced severe toxicities, 2 physicians randomly selected from 14 physicians evaluated each toxicity profile and assigned a visual analogue scale score (0-10) based on their impression of the global burden of toxicities. With mixed-effects models, severity scores and a 10-point toxicity burden score (TBS) were derived from 27 predictors accounting for severe (grade 3) and life-threatening (grade 4) toxicities for each organ class of the Common Terminology Criteria for Adverse Events. RESULTS: For most organ classes, grade 3 toxicities had a TBS of 4.14 (95% confidence interval [CI], 3.65-4.63), but infections, cardiovascular events, and pulmonary events had a higher TBS with differences of 0.87 (95% CI, 0.53-1.21), 0.88 (95% CI, 0.51-1.25), and 0.73 (95% CI, 0.22-1.24), respectively. Moreover, most grade 4 events had a higher TBS than grade 3 events, except for hemorrhaging, pain, metabolic events, and musculoskeletal events. The intrarater and interrater correlations were 0.91 and 0.59, respectively. CONCLUSIONS: The burden of toxicity grades differs with toxicity types. A TBS provides a toxicity burden summary that incorporates physicians' perspectives and differentiates between severe and life-threatening toxicities and organ classes. Cancer 2018;124:858-64. © 2017 American Cancer Society.

The Influence of Daily Stress on Sedentary Behavior: Group and Person (N of 1) Level Results of a 1-Year Observational Study.

OBJECTIVE: The purpose of this study, which used mobile technologies to continuously collect data for 1 year, was to examine the association of psychological stress with objectively measured sedentary behavior in adults at both the group (e.g., nomothetic approach) and individual (e.g., idiographic approach) level. METHODS: Data were collected in an observational study of healthy adults (n = 79) residing in the New York City metro area who were studied for 365 days from 2014 to 2015. Sedentary behavior was objectively measured via accelerometry. A smartphone-based electronic diary was used to assess level of stress ("Overall, how stressful was your day?" 0-10 scale) and sources of stress. RESULTS: The end-of-day stress rating was not associated with total sedentary time (B = -1.34, p = .767) at the group level. When specific sources of stress were evaluated at the group level, argument-related stress was associated with increased sedentariness, whereas running late- and work-related stress were associated with decreased sedentariness. There was a substantial degree of interindividual variability in the relationship of stress with sedentary behavior. Both the level and sources of stress were associated with increased sedentariness for some, decreased sedentariness for others, and had no effect for many (within-person variance p < .001). CONCLUSIONS: These findings suggest that the influence of stress on sedentary behavior varies by source of stress and from person to person. A precision medicine approach may be warranted to target reductions in sedentary time, although further studies are needed to confirm the observed findings in light of study limitations including a small sample size and enrollment of participants from a single, urban metropolitan area.

Regional Subclinical Cerebrovascular Disease Is Associated with Balance in an Elderly Multi-Ethnic Population.

INTRODUCTION: White matter hyperintensity volume (WMHV) and subclinical brain infarcts (SBI) are associated with impaired mobility, but less is known about the association of WMHV in specific brain regions. We hypothesized that anterior WMHV would be associated with lower scores on the Short Physical Performance Battery (SPPB), a well-validated mobility scale. METHODS: The SPPB was measured a median of 5 years after enrollment into the Northern Manhattan MRI sub study. Volumetric distributions for WMHV in 14 brain regions as a proportion of total cranial volume were determined. Multi-variable linear regression was performed to examine the association of SBI and regional log-WMHV with the SPPB score. RESULTS: Among 668 participants with SPPB measurements (mean 74 ± 9 years, 37% male and 70% Hispanic), the mean SPPB score was 8.2 ± 2.9. Total (beta = -0.3 per SD, p = 0.001), anterior periventricular (beta = -0.4 per SD, p = 0.001), parietal (beta = -0.2 per SD, p = 0.02) and frontal (beta = -0.3 per SD, p = 0.002) WMHVs were associated with SPPB; other WMHV and SBI were not associated with the SPPB. CONCLUSIONS: WMHV, especially in the anterior -cerebral regions, is associated with a lower SPPB. Prevention of subclinical cerebrovascular disease is a potential target to prevent physical decline in the elderly.

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.

Quantile Coarsening Analysis of High-Volume Wearable Activity Data in a Longitudinal Observational Study.

Owing to advances in sensor technologies on wearable devices, it is feasible to measure physical activity of an individual continuously over a long period. These devices afford opportunities to understand individual behaviors, which may then provide a basis for tailored behavior interventions. The large volume of data however poses challenges in data management and analysis. We propose a novel quantile coarsening analysis (QCA) of daily physical activity data, with a goal to reduce the volume of data while preserving key information. We applied QCA to a longitudinal study of 79 healthy participants whose step counts were monitored for up to 1 year by a Fitbit device, performed cluster analysis of daily activity, and identified individual activity signature or pattern in terms of the clusters identified. Using 21,393 time series of daily physical activity, we identified eight clusters. Employment and partner status were each associated with 5 of the 8 clusters. Using less than 2% of the original data, QCA provides accurate approximation of the mean physical activity, forms meaningful activity patterns associated with individual characteristics, and is a versatile tool for dimension reduction of densely sampled data.

Long-Term Exposure to Ambient Air Pollution and Subclinical Cerebrovascular Disease in NOMAS (the Northern Manhattan Study).

BACKGROUND AND PURPOSE: Long-term exposure to ambient air pollution is associated with higher risk of cardiovascular disease and stroke. We hypothesized that long-term exposure to air pollution would be associated with magnetic resonance imaging markers of subclinical cerebrovascular disease. METHODS: Participants were 1075 stroke-free individuals aged ≥50 years drawn from the magnetic resonance imaging subcohort of the Northern Manhattan Study who had lived at the same residence for at least 2 years before magnetic resonance imaging. Cross-sectional associations between ambient air pollution and subclinical cerebrovascular disease were analyzed. RESULTS: We found an association between distance to roadway, a proxy for residential exposure to traffic pollution, and white matter hyperintensity volume; however, after adjusting for risk factors, this relationship was no longer present. All other associations between pollutant measures and white matter hyperintensity volume were null. There was no clear association between exposure to air pollutants and subclinical brain infarcts or total cerebral brain volume. CONCLUSIONS: We found no evidence that long-term exposure to ambient air pollution is independently associated with subclinical cerebrovascular disease in an urban population-based cohort.