4 research outputs found
Markers Of Alcohol Use Disorder Outpatient Treatment Outcome: Prediction Modeling Of Day One Treatment
ABSTRACT
Background: Alcohol use disorders (AUD) affect health and wellbeing, and have broad societal costs (Bouchery, Harwood, Sacks, Simon, & Brewer, 2011; Rehm et al., 2009; Sudhinaraset, Wigglesworth, Takeuchi, & Tsuker, 2016). While treatments have existed for decades, they are limited in success and expensive to administer. As such, understanding which factors best predict who will benefit most from treatment remains a laudable goal. Prior attempts to predict factors associated with positive treatment outcome are limited by methodology including statistical methods that lead to poor predictive power in new samples. This study aims to use a data-driven approach to clarify the predictors of AUD treatment success (Objective 1) accompanied by a theory-driven analysis assessing the mediation of treatment outcomes through psychological distress (Objective 2). Methods: One hundred forty-five patients seeking treatment for alcohol use problems at the Day One Intensive Outpatient Treatment Program (part of UVM Medical Center) between June 2011 and June 2012 were examined. Variables were extracted through chart review and were categorized using the Bronfenbrenner Ecological Model. First, 20% of the sample was set-aside for model testing, and the remaining 80% was used in an Elastic Net Regularized linear regression, with 10-fold cross validation. Models were tested on the set-aside sample to yield estimates of out-of-sample prediction and repeated models were compared to ensure generalizability. Next, a theoretical model was tested examining a model of psychological distress mediating the relationship between individual predictors and treatment outcome. Results: The models developed from the Elastic Net Regularization approach demonstrated consistency in model strength (mean=0.32, standard deviation=0.03) with models ranging from 14 to 31 included variables. Across the models, 15 variables occurred in \u3e75% of the models, and an additional 7 variables were included in 25% - 75% of the models. Some of the strongest predictors included treatment non-compliance (β=-0.92), ASI Alcohol Composite (β=0.63), treatment dosage (β =-0.36), and readiness to change (β=-0.95). The results of the theory-driven mediation analysis demonstrated several strong direct predictors of outcome frequency of alcohol use, including readiness to change (β=-0.59), initial frequency of alcohol use (β=0.27), and access to a primary care physician (β=-2.20). The theoretical model found that none of the mediation pathways (testing psychological variables) were significantly different from the direct models. Conclusions: This study used both data-driven and theory-driven methods to examine factors affecting treatment of AUDs. The application of data-driven methods provided several predictors of outcome that can guide treatment efforts within Day One IOP treatment, as well as generalized to other abstinence-based treatment settings. For example, focusing on treatment attendance and using motivational interviewing to enhance readiness to change are methods supported by this study. Demographic variables that have been shown to predict treatment outcome in small studies, without cross-validation were not identified by the elastic net regression (e.g., age and gender). It is suspected that this is due to model overfitting in prior studies supporting the importance of using generalizable statistical methods to understand predictors of treatment outcome. This notion is supported by the results of the theory-driven model, which did not yield a strong model of treatment success. Taken together, the results support the use of strong analytic techniques which will guide theory in the future
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Vascular endothelial growth factor (VEGF) isoform regulation of early forebrain development
This work was designed to determine the role of the vascular endothelial growth factor A (VEGF) isoforms during early neuroepithelial development in the mammalian central nervous system (CNS), specifically in the forebrain. An emerging model of interdependence between neural and vascular systems includes VEGF, with its dual roles as a potent angiogenesis factor and neural regulator. Although a number of studies have implicated VEGF in CNS development, little is known about the role that the different VEGF isoforms play in early neurogenesis. We used a mouse model of disrupted VEGF isoform expression that eliminates the predominant brain isoform, VEGF164, and expresses only the diffusible form, VEGF120. We tested the hypothesis that VEGF164 plays a key role in controlling neural precursor populations in developing cortex. We used microarray analysis to compare gene expression differences between wild type and VEGF120 mice at E9.5, the primitive stem cell stage of the neuroepithelium. We quantified changes in PHH3-positive nuclei, neural stem cell markers (Pax6 and nestin) and the Tbr2-positive intermediate progenitors at E11.5 when the neural precursor population is expanding rapidly. Absence of VEGF164 (and VEGF188) leads to reduced proliferation without an apparent effect on the number of Tbr2-positive cells. There is a corresponding reduction in the number of mitotic spindles that are oriented parallel to the ventricular surface relative to those with a vertical or oblique angle. These results support a role for the VEGF isoforms in supporting the neural precursor population of the early neuroepithelium