All Publications

  • Environmental and State-Level Regulatory Factors Affect the Incidence of Autism and Intellectual Disability PLOS COMPUTATIONAL BIOLOGY Rzhetsky, A., Bagley, S. C., Wang, K., Lyttle, C. S., Cook, E. H., Altman, R. B., Gibbons, R. D. 2014; 10 (3)


    Many factors affect the risks for neurodevelopmental maladies such as autism spectrum disorders (ASD) and intellectual disability (ID). To compare environmental, phenotypic, socioeconomic and state-policy factors in a unified geospatial framework, we analyzed the spatial incidence patterns of ASD and ID using an insurance claims dataset covering nearly one third of the US population. Following epidemiologic evidence, we used the rate of congenital malformations of the reproductive system as a surrogate for environmental exposure of parents to unmeasured developmental risk factors, including toxins. Adjusted for gender, ethnic, socioeconomic, and geopolitical factors, the ASD incidence rates were strongly linked to population-normalized rates of congenital malformations of the reproductive system in males (an increase in ASD incidence by 283% for every percent increase in incidence of malformations, 95% CI: [91%, 576%], p<6×10(-5)). Such congenital malformations were barely significant for ID (94% increase, 95% CI: [1%, 250%], p = 0.0384). Other congenital malformations in males (excluding those affecting the reproductive system) appeared to significantly affect both phenotypes: 31.8% ASD rate increase (CI: [12%, 52%], p<6×10(-5)), and 43% ID rate increase (CI: [23%, 67%], p<6×10(-5)). Furthermore, the state-mandated rigor of diagnosis of ASD by a pediatrician or clinician for consideration in the special education system was predictive of a considerable decrease in ASD and ID incidence rates (98.6%, CI: [28%, 99.99%], p = 0.02475 and 99% CI: [68%, 99.99%], p = 0.00637 respectively). Thus, the observed spatial variability of both ID and ASD rates is associated with environmental and state-level regulatory factors; the magnitude of influence of compound environmental predictors was approximately three times greater than that of state-level incentives. The estimated county-level random effects exhibited marked spatial clustering, strongly indicating existence of as yet unidentified localized factors driving apparent disease incidence. Finally, we found that the rates of ASD and ID at the county level were weakly but significantly correlated (Pearson product-moment correlation 0.0589, p = 0.00101), while for females the correlation was much stronger (0.197, p<2.26×10(-16)).

    View details for DOI 10.1371/journal.pcbi.1003518

    View details for Web of Science ID 000336509000034

    View details for PubMedID 24625521

    View details for PubMedCentralID PMC3952819

  • Identifying Patients at Risk for Suicide: Brief Review Making Health Care Safer II: An Updated Critical Analysis of the Evidence for Patient Safety Practices Bagley, S. C. AHRQ. 2013: 287–296
  • Predicting Suicide Attempt Risk: Logistic Regression Requires Large Sample Sizes JOURNAL OF CLINICAL PSYCHIATRY Bagley, S. C. 2011; 72 (12): 1698-1698

    View details for DOI 10.4088/JCP.11lr07393

    View details for Web of Science ID 000298778500020

    View details for PubMedID 22244029

  • Efficacy and Comparative Effectiveness of Atypical Antipsychotic Medications for Off-Label Uses in Adults A Systematic Review and Meta-analysis JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION Maher, A. R., Maglione, M., Bagley, S., Suttorp, M., Hu, J., Ewing, B., Wang, Z., Timmer, M., Sultzer, D., Shekelle, P. G. 2011; 306 (12): 1359-1369


    Atypical antipsychotic medications are commonly used for off-label conditions such as agitation in dementia, anxiety, and obsessive-compulsive disorder.To perform a systematic review on the efficacy and safety of atypical antipsychotic medications for use in conditions lacking approval for labeling and marketing by the US Food and Drug Administration.Relevant studies published in the English language were identified by searches of 6 databases (PubMed, EMBASE, CINAHL, PsycInfo, Cochrane DARE, and CENTRAL) from inception through May 2011. Controlled trials comparing an atypical antipsychotic medication (risperidone, olanzapine, quetiapine, aripiprazole, ziprasidone, asenapine, iloperidone, or paliperidone) with placebo, another atypical antipsychotic medication, or other pharmacotherapy for adult off-label conditions were included. Observational studies with sample sizes of greater than 1000 patients were included to assess adverse events.Independent article review and study quality assessment by 2 investigators.Of 12 228 citations identified, 162 contributed data to the efficacy review. Among 14 placebo-controlled trials of elderly patients with dementia reporting a total global outcome score that includes symptoms such as psychosis, mood alterations, and aggression, small but statistically significant effects sizes ranging from 0.12 and 0.20 were observed for aripiprazole, olanzapine, and risperidone. For generalized anxiety disorder, a pooled analysis of 3 trials showed that quetiapine was associated with a 26% greater likelihood of a favorable response (defined as at least 50% improvement on the Hamilton Anxiety Scale) compared with placebo. For obsessive-compulsive disorder, risperidone was associated with a 3.9-fold greater likelihood of a favorable response (defined as a 25% improvement on the Yale-Brown Obsessive Compulsive Scale) compared with placebo. In elderly patients, adverse events included an increased risk of death (number needed to harm [NNH] = 87), stroke (NNH = 53 for risperidone), extrapyramidal symptoms (NNH = 10 for olanzapine; NNH = 20 for risperidone), and urinary tract symptoms (NNH range = 16-36). In nonelderly adults, adverse events included weight gain (particularly with olanzapine), fatigue, sedation, akathisia (for aripiprazole), and extrapyramidal symptoms.Benefits and harms vary among atypical antipsychotic medications for off-label use. For global behavioral symptom scores associated with dementia in elderly patients, small but statistically significant benefits were observed for aripiprazole, olanzapine, and risperidone. Quetiapine was associated with benefits in the treatment of generalized anxiety disorder, and risperidone was associated with benefits in the treatment of obsessive-compulsive disorder; however, adverse events were common.

    View details for Web of Science ID 000295257000025

    View details for PubMedID 21954480

  • A Systematic Review of Suicide Prevention Programs for Military or Veterans SUICIDE AND LIFE-THREATENING BEHAVIOR Bagley, S. C., Munjas, B., Shekelle, P. 2010; 40 (3): 257-265


    Military personnel and veterans have important suicide risk factors. After a systematic review of the literature on suicide prevention, seven (five in the U.S.) studies of military personnel were identified containing interventions that may reduce the risk of suicide. The effectiveness of the individual components was not assessed, and problems in methodology or reporting of data were common. Overall, multifaceted interventions for active duty military personnel are supported by consistent evidence, although of very mixed quality, and in some cases during intervals of declines in suicide rates in the general population. There were insufficient studies of U.S. Veterans to reach conclusions.

    View details for Web of Science ID 000278740200005

    View details for PubMedID 20560747

  • Logistic regression in the medical literature: Standards for use and reporting, with particular attention to one medical domain JOURNAL OF CLINICAL EPIDEMIOLOGY Bagley, S. C., White, H., Golomb, B. A. 2001; 54 (10): 979-985


    Logistic regression (LR) is a widely used multivariable method for modeling dichotomous outcomes. This article examines use and reporting of LR in the medical literature by comprehensively assessing its use in a selected area of medical study. Medline, followed by bibliography searches, identified 15 peer-reviewed English-language articles with original data, employing LR, published between 1985 and 1999, pertaining to patient interest in genetic testing for cancer susceptibility. Articles were examined for each of 10 criteria for proper use and reporting of LR models. Substantial shortcomings were found in both use of LR and reporting of results. For many studies, the ratio of the number of outcome events to predictor variables (events per variable) was sufficiently small to call into question the accuracy of the regression model. Additionally, no studies reported validation analysis, regression diagnostics, or goodness-of-fit measures. It is recommended that authors, reviewers, and editors pay greater attention to guidelines concerning the use and reporting of LR models.

    View details for Web of Science ID 000171047800003

    View details for PubMedID 11576808



    Sites are microenvironments within a biomolecular structure, distinguished by their structural or functional role. A site can be defined by a three-dimensional location and a local neighborhood around this location in which the structure or function exists. We have developed a computer system to facilitate structural analysis (both qualitative and quantitative) of biomolecular sites. Our system automatically examines the spatial distributions of biophysical and biochemical properties, and reports those regions within a site where the distribution of these properties differs significantly from control nonsites. The properties range from simple atom-based characteristics such as charge to polypeptide-based characteristics such as type of secondary structure. Our analysis of sites uses non-sites as controls, providing a baseline for the quantitative assessment of the significance of the features that are uncovered. In this paper, we use radial distributions of properties to study three well-known sites (the binding sites for calcium, the milieu of disulfide bridges, and the serine protease active site). We demonstrate that the system automatically finds many of the previously described features of these sites and augments these features with some new details. In some cases, we cannot confirm the statistical significance of previously reported features. Our results demonstrate that analysis of protein structure is sensitive to assumptions about background distributions, and that these distributions should be considered explicitly during structural analyses.

    View details for Web of Science ID A1995QU44000004

    View details for PubMedID 7613462