Application of Time-to-Event Methods in the Assessment of Safety in Clinical Trials

Since randomized controlled trials (RCT) are typically designed and powered for efficacy rather than safety, power is an important concern in the analysis of the effect of treatment on the occurrence of adverse events (AE). These outcomes are often time-to-event outcomes which will naturally be subject to right-censoring due to early patient withdrawals. In the analysis of the treatment effect on such an outcome, gains in efficiency, and thus power, can be achieved by exploiting covariate information. We apply the targeted maximum likelihood methodology to the estimation of treatment specific survival at a fixed end point for right-censored survival outcomes. This approach provides a method for covariate adjustment, that under no or uninformative censoring, does not require any additional parametric modeling assumptions, and, under informative censoring, is consistent under consistent estimation of the censoring mechanism or the conditional hazard for survival. Thus, the targeted maximum likelihood estimator has two important advantages over the Kaplan-Meier estimator: 1) It exploits covariates to improve efficiency, and 2) It is consistent in the presence of informative censoring. These properties are demonstrated through simulation studies. Extensions to the methodology are provided for non randomized post-market safety studies and also for the inclusion of time-dependent covariates

Covariate Adjustment in Randomized Trials with Binary Outcomes: Targeted Maximum Likelihood Estimation

Covariate adjustment using linear models for continuous outcomes in randomized trials has been shown to increase efficiency and power over the unadjusted method in estimating the marginal effect of treatment. However, for binary outcomes, investigators generally rely on the unadjusted estimate as the literature indicates that covariate-adjusted estimates based on logistic regression models are less efficient. The crucial step that has been missing when adjusting for covariates is that one must integrate/average the adjusted estimate over those covariates in order to obtain the marginal effect. We apply the method of targeted maximum likelihood estimation (MLE), as presented in van der Laan and Rubin (2006), to obtain estimators for the marginal effect using covariate adjustment for binary outcomes. We show that the covariate adjustment in randomized trials using logistic regression models can be mapped, by averaging over the covariate(s), to obtain a fully robust and efficient estimator of the marginal effect, which equals the targeted maximum likelihood estimator (MLE). We present simulation studies that show the targeted MLE increases efficiency and power over the unadjusted method, particularly for smaller sample sizes, even when the regression model is mis-specified

The Experiences of American Indian Participants and Site Coordinators in a Gestational Diabetes Risk Reduction Trial

Gestational diabetes mellitus is the most common complication of pregnancy and contributes to increased risk for type 2 diabetes in both the mother and offspring. We developed and evaluated a gestational diabetes risk reduction and preconception counseling program, Stopping GDM (SGDM), for American Indian females. The purpose of this study is to examine the experiences of American Indian mother-daughter dyad participants and the site coordinators who facilitated the SGDM randomized controlled trial to inform program revisions. We engaged mother-daughter dyads (n = 22 dyads) and site coordinators (n = 6) in focus group interviews. Four themes emerged: (1) SGDM sparked valuable quality conversation for dyads; (2) gestational diabetes risk factors and risk reduction was new information for most dyads; (3) all trial sites experienced challenges to recruitment and engagement; and (4) study-improvement recommendations. These findings will be used to enhance SGDM to decrease adverse intergenerational health impacts of gestational diabetes in American Indian communities

The role of social and/or ecological contexts influences assessment strategy use in Tilapia

Animals engage in costly agonistic contests during which winners procure resources. During these interactions, the combatants obtain and use information to make decisions on whether to persist or to withdraw from the fight, which is termed assessment. Recent theory and work have suggested that the types of assessment employed may be more variable than previously thought, with the use of different strategies possibly being influenced by social and ecological conditions during priming. This study addresses the contextual components (social and ecological) that affect the utilization of one assessment strategy over another. Male tilapia were primed with different combinations of social (large and small animals) and ecological (resource rich or poor) contexts 24 hr prior to fighting in staged, dyadic contests. When opponents were primed with the same context, a clear assessment strategy emerged and differed as a function of priming treatment. Conversely, when fish were primed with different treatment contexts, there was no discernible assessment. In addition, priming conditions had differing effects for large and small fish. Thus, assessment strategies in cichlids are dependent upon a combination of social, ecological contexts and size of the animal. Since assessment strategies change as a function of both of these contexts, as well as others, future framework investigating assessment strategies should include both intrinsic and extrinsic factors that may shape fighting dynamics.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151902/1/eth12936_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151902/2/eth12936.pd

Factors Influencing the Impact of Depressive Symptoms on Physical Functional Capacity After Cardiac Rehabilitation

Purpose This study aims to determine (1) if depressive symptoms in the year following completion of cardiac rehabilitation impact physical functional capacity and (2) if exercise, perceived benefits and barriers, self-efficacy, and social support moderate this relationship. Design This longitudinal correlational secondary data analysis included 379 cardiovascular rehabilitation patients. Methods Participants completed measures of depression and potential moderating variables at baseline, 2 months, 6 months, and 12 months and 6-minute work test at baseline and 12 months and wore heart rate monitors to measure exercise for 12 months. Findings Poorer physical functional capacity was predicted by depressed mood score. This relationship was moderated by the percentage of time exercising in target heart rate zone and family support of exercise, but not by perceived benefits and barriers or self-efficacy for exercise. Conclusions Depressive symptoms negatively impact physical functional capacity, and this relationship is moderated by family support and the percentage of time exercising in target heart rate zone

SYSTEMS-2: a randomised phase II study of radiotherapy dose escalation for pain control in malignant pleural mesothelioma

SYSTEMS-2 is a randomised study of radiotherapy dose escalation for pain control in 112 patients with malignant pleural mesothelioma (MPM). Standard palliative (20Gy/5#) or dose escalated treatment (36Gy/6#) will be delivered using advanced radiotherapy techniques and pain responses will be compared at week 5. Data will guide optimal palliative radiotherapy in MPM

Adapting to Uncertainty: Nursing Responsiveness to COVID-19

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic

Causal Inference in Epidemiological Studies with Strong Confounding

One of the identifiabilty assumptions of causal effects defined by marginal structural model (MSM) parameters is the experimental treatment assignment (ETA) assumption. Practical violations of this assumption frequently occur in data analysis, when certain exposures are rarely observed within some strata of the population. The inverse probability of treatment weighted (IPTW) estimator is particularly sensitive to violations of this assumption, however, we demonstrate that this is a problem for all estimators of causal effects. This is due to the fact that the ETA assumption is about information (or lack thereof) in the data. A new class of causal models, causal models for realistic individualized exposure rules (CMRIER), introduced in van der Laan and Petersen (2007), is based on dynamic interventions. CMRIER generalize MSM, and their parameters remain fully identifiable from the observed data, even when the ETA assumption is violated, if the dynamic interventions are set to be realistic. Examples of such realistic interventions are provided. We argue that causal effects defined by CMRIER may be more appropriate in many situations, particularly those with policy considerations. Through simulation studies, we examine the performance of the IPTW estimator of the CMRIER parameters in contrast to that of the MSM parameters. We also apply the methodology to a real data analysis in air pollution epidemiology to illustrate the interpretation of the causal effects defined by CMRIER

Recognising Desire: A psychosocial approach to understanding education policy implementation and effect

It is argued that in order to understand the ways in which teachers experience their work - including the idiosyncratic ways in which they respond to and implement mandated education policy - it is necessary to take account both of sociological and of psychological issues. The paper draws on original research with practising and beginning teachers, and on theories of social and psychic induction, to illustrate the potential benefits of this bipartisan approach for both teachers and researchers. Recognising the significance of (but somewhat arbitrary distinction between) structure and agency in teachers’ practical and ideological positionings, it is suggested that teachers’ responses to local and central policy changes are governed by a mix of pragmatism, social determinism and often hidden desires. It is the often underacknowledged strength of desire that may tip teachers into accepting and implementing policies with which they are not ideologically comfortable

Always on my mind: Cross-brain associations of mental health symptoms during simultaneous parent-child scanning.

How parents manifest symptoms of anxiety or depression may affect how children learn to modulate their own distress, thereby influencing the children's risk for developing an anxiety or mood disorder. Conversely, children's mental health symptoms may impact parents' experiences of negative emotions. Therefore, mental health symptoms can have bidirectional effects in parent-child relationships, particularly during moments of distress or frustration (e.g., when a parent or child makes a costly mistake). The present study used simultaneous functional magnetic resonance imaging (fMRI) of parent-adolescent dyads to examine how brain activity when responding to each other's costly errors (i.e., dyadic error processing) may be associated with symptoms of anxiety and depression. While undergoing simultaneous fMRI scans, healthy dyads completed a task involving feigned errors that indicated their family member made a costly mistake. Inter-brain, random-effects multivariate modeling revealed that parents who exhibited decreased medial prefrontal cortex and posterior cingulate cortex activation when viewing their child's costly error response had children with more symptoms of depression and anxiety. Adolescents with increased anterior insula activation when viewing a costly error made by their parent had more anxious parents. These results reveal cross-brain associations between mental health symptomatology and brain activity during parent-child dyadic error processing