Technical report: an online international weight control registry to inform precision approaches to healthy weight management.

BACKGROUND: Personalizing approaches to prevention and treatment of obesity will be a crucial aspect of precision health initiatives. However, in considering individual susceptibility to obesity, much remains to be learned about how to support healthy weight management in different population subgroups, environments and geographical locations. SUBJECTS/METHODS: The International Weight Control Registry (IWCR) has been launched to facilitate a deeper and broader understanding of the spectrum of factors contributing to success and challenges in weight loss and weight loss maintenance in individuals and across population groups. The IWCR registry aims to recruit, enroll and follow a diverse cohort of adults with varying rates of success in weight management. Data collection methods include questionnaires of demographic variables, weight history, and behavioral, cultural, economic, psychological, and environmental domains. A subset of participants will provide objective measures of physical activity, weight, and body composition along with detailed reports of dietary intake. Lastly, participants will be able to provide qualitative information in an unstructured format on additional topics they feel are relevant, and environmental data will be obtained from public sources based on participant zip code. CONCLUSIONS: The IWCR will be a resource for researchers to inform improvements in interventions for weight loss and weight loss maintenance in different countries, and to examine environmental and policy-level factors that affect weight management in different population groups. This large scale, multi-level approach aims to inform efforts to reduce the prevalence of obesity worldwide and its associated comorbidities and economic impacts. TRIAL REGISTRATION: NCT04907396 (clinicaltrials.gov) sponsor SB Roberts; Tufts University IRB #13075.

The Effects of M2M and Adapted Yoga on Physical and Psychosocial Outcomes in People With Multiple Sclerosis.

OBJECTIVE: To investigate the effects of two 12-week exercise training interventions, movement-to-music (M2M) and adapted yoga (AY), on physical and psychosocial outcomes in people with multiple sclerosis (MS). DESIGN: Three-arm randomized controlled proof-of-concept trial. SETTING: A community-based fitness facility. PARTICIPANTS: Participants (N=81) with MS (Patient Determined Disease Steps [PDDS] self-reported disease status scores: 0-6) between ages of 18 and 65 years were randomized to M2M (n=27), AY (n=26), or waitlist control (n=28). INTERVENTIONS: Both M2M and AY completed three 60-minute exercise sessions per week for 12 weeks. Waitlist controls received biweekly newsletters via mail that contained educational information on living with MS. MAIN OUTCOME MEASURES: Primary measures were timed Up and Go (TUG, s) test, 6-minute walk test (6MWT, m), and 5 times sit-to-stand test (FTSST, s). Secondary measures were self-reported outcomes assessed using Patient-Reported Outcomes Measurement Information System Fatigue and Pain Interference Short Form 8a. Participants were evaluated at baseline and postintervention. Primary analyses were performed using an intent-to-treat mixed model analysis of covariance. RESULTS: Comparisons across all 3 groups revealed significant group differences in TUG and 6MWT. Post hoc analyses indicated significant improvements in TUG (least square mean difference [95% confidence interval] = -1.9s [-3.3 to -0.5], P=.01, d=0.7) and 6MWT (41.0m [2.2-80.0], P=.04, d=0.6; controlled for PDDS) in M2M compared to controls, while no significant differences were observed when compared AY to controls. No significant group differences were found in FTSST, fatigue, and pain interference. CONCLUSIONS: M2M may be a useful and enjoyable exercise form for people with MS in improving mobility and walking endurance and merits long-term study in larger study populations.

All-Cause and Cause-Specific Mortality Associated with Bariatric Surgery: A Review.

The question of whether or not nonsurgical intentional or voluntary weight loss results in reduced mortality has been equivocal, with long-term mortality following weight loss being reported as increased, decreased, and not changed. In part, inconsistent results have been attributed to the uncertainty of whether the intentionality of weight loss is accurately reported in large population studies and also that achieving significant and sustained voluntary weight loss in large intervention trials is extremely difficult. Bariatric surgery has generally been free of these conflicts. Patients voluntarily undergo surgery and the resulting weight is typically significant and sustained. These elements, combined with possible non-weight loss-related mechanisms, have resulted in improved comorbidities, which likely contribute to a reduction in long-term mortality. This paper reviews the association between bariatric surgery and long-term mortality. From these studies, the general consensus is that bariatric surgical patients have: 1) significantly reduced long-term all-cause mortality when compared to severely obese non-bariatric surgical control groups; 2) greater mortality when compared to the general population, with the exception of one study; 3) reduced cardiovascular-, stroke-, and cancer-caused mortality when compared to severely obese non-operated controls; and 4) increased risk for externally caused death such as suicide.

Multiple Electronic Health Record-Based Measures of Social Determinants of Health to Predict Return to the Emergency Department Following Discharge.

Health care systems continue to struggle with preventing 30-day readmissions to their institutions. Social determinants of health (SDOH) are important predictors of repeat visits to the hospital. In many health systems, SDOH data are limited to those variables that are most relevant to care delivery or payment (eg, race, gender, insurance status). Despite calls for integrating a more robust set of measures (eg, measures of health behaviors and living conditions) into the electronic health record (EHR), these data often have missing values necessitating the use of imputation to build a comprehensive picture of patients who are likely to return to the health system. Using logistic regression analyses and imputation of missing data from 2017 to 2018, this study uses measures found in the EHR (eg, tobacco use, living situation, problems at home, education) to assess those SDOH that might predict a return to the emergency department within 30 days of discharge from a health system. In both imputed and raw data, the total number of recorded health conditions was the most important predictor and collectively SDOH variables made a relatively small contributions in determining the likelihood of a return to the hospital. Although SDOH variables might be important in the design of programs aimed at preventing readmissions, they may not be useful in readmission predictive models.

An Exploratory Analysis of the Association Between Catechol-O-Methyltransferase and Response to a Randomized Open-Label Placebo Treatment for Cancer-Related Fatigue.

Previous studies have identified catechol-O-methyltransferase (COMT), as a key enzyme influencing sympathetic function. Although the COMT SNP rs4680 and rs4818, are well-studied, little is known about their influence on cancer-related fatigue (CrF) and placebo response. In this study, we examined whether genetic variation in COMT, at the functional SNP rs4680 and linked rs4818, influenced open-label placebo (OLP) responses found in cancer survivors reporting moderate to severe CrF. We randomized cancer survivors (N = 74) reporting moderate-to-severe CrF to receive OLP or to treatment-as-usual (TAU) and assessed if rs4680 and rs4818 were associated with changes in fatigue severity and fatigue-distressed quality of life. At the end of the initial 21 days, the treatments were crossed over and both groups were re-assessed. Participants with the rs4680 high-activity G-allele (G/G or G/A) or rs4818 C/G genotypes reported significant decreases in fatigue severity and improvements in fatigue-distressed quality of life. The COMT rs4818 findings replicated findings in a similar study of OLP in cancer fatigue. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT02522988.

Open-Label Placebo Treatment for Cancer-Related Fatigue: A Randomized-Controlled Clinical Trial.

The purpose of this 21-day assessor blinded, randomized-controlled trial was to compare an open-label placebo (OLP) to treatment as usual (TAU) for cancer survivors with fatigue. This was followed by an exploratory 21-day study in which TAU participants received OLPs while OLP participants in the main study were followed after discontinuing placebos. Cancer survivors (N = 74) who completed cancer treatment 6 months to 10 years prior to enrollment reporting at least moderate fatigue (i.e., ≥4 on a 0-10 scale) were randomized to OLP or TAU. Those randomized to OLP took 2 placebo pills twice a day for 21 days. Compared to those randomized to TAU, OLP participants reported a 29% improvement in fatigue severity (average difference in the mean change scores (MD) 12.47, 95% CI 3.32, 21.61; P = 0.008), medium effect (d = 0.63), and a 39% improvement in fatigue-disrupted quality of life (MD = 11.76, 95% CI 4.65, 18.86; P = 0.002), a large effect (d = 0.76). TAU participants who elected to try OLP for 21-days after the main study reported reductions in fatigue of a similar magnitude for fatigue severity and fatigue-disrupted quality of life (23% and 35%, respectively). OLP may reduce fatigue symptom severity and fatigue-related quality of life disruption in cancer survivors.

Epistemological issues in omics and high-dimensional biology: give the people what they want.

Gene expression microarrays have been the vanguard of new analytic approaches in high-dimensional biology. Draft sequences of several genomes coupled with new technologies allow study of the influences and responses of entire genomes rather than isolated genes. This has opened a new realm of highly dimensional biology where questions involve multiplicity at unprecedented scales: thousands of genetic polymorphisms, gene expression levels, protein measurements, genetic sequences, or any combination of these and their interactions. Such situations demand creative approaches to the processes of inference, estimation, prediction, classification, and study design. Although bench scientists intuitively grasp the need for flexibility in the inferential process, the elaboration of formal supporting statistical frameworks is just at the very start. Here, we will discuss some of the unique statistical challenges facing investigators studying high-dimensional biology, describe some approaches being developed by statistical scientists, and offer an epistemological framework for the validation of proffered statistical procedures. A key theme will be the challenge in providing methods that a statistician judges to be sound and a biologist finds informative. The shift from family-wise error rate control to false discovery rate estimation and to assessment of ranking and other forms of stability will be portrayed as illustrative of approaches to this challenge.