Dataset Information

Colorado Twin Registry: an update.

ABSTRACT: The Colorado Twin Registry (CTR) is a population-based registry housed at the Institute for Behavioral Genetics at the University of Colorado. Recruitment began in 1982 and includes twins born from 1968 to the present. Four samples are currently drawn from the CTR: The Community Twin Sample, the Longitudinal Twin Sample, the Early Reading Development Sample, and the Colorado Learning Sample. Criteria for enrollment, recruitment strategies, demographic information, and zygosity assignment are explained for each sample. In addition, five studies in which CTR twins are now participating are highlighted. These include studies of cognition, learning ability, and vulnerability to substance abuse and antisocial behavior. The development of the CTR is an ongoing and evolving process, and it has proven to be a valuable registry, relatively representative of the population from which it was drawn.

SUBMITTER: Rhea SA

PROVIDER: S-EPMC3854934 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature

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Publications

Colorado Twin Registry: an update.

Rhea Sally-Ann SA Gross Andy A AA Haberstick Brett C BC Corley Robin P RP

Twin research and human genetics : the official journal of the International Society for Twin Studies 20121023 1

The Colorado Twin Registry (CTR) is a population-based registry housed at the Institute for Behavioral Genetics at the University of Colorado. Recruitment began in 1982 and includes twins born from 1968 to the present. Four samples are currently drawn from the CTR: The Community Twin Sample, the Longitudinal Twin Sample, the Early Reading Development Sample, and the Colorado Learning Sample. Criteria for enrollment, recruitment strategies, demographic information, and zygosity assignment are exp ...[more]

PMID: 23092589

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Project description:BackgroundClinical predictive models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision-making and individualize care. The Tufts Predictive Analytics and Comparative Effectiveness (PACE) CPM Registry is a comprehensive database of cardiovascular disease (CVD) CPMs. The Registry was last updated in 2012, and there continues to be substantial growth in the number of available CPMs.MethodsWe updated a systematic review of CPMs for CVD to include articles published from January 1990 to March 2015. CVD includes coronary artery disease (CAD), congestive heart failure (CHF), arrhythmias, stroke, venous thromboembolism (VTE), and peripheral vascular disease (PVD). The updated Registry characterizes CPMs based on population under study, model performance, covariates, and predicted outcomes.ResultsThe Registry includes 747 articles presenting 1083 models, including both prognostic (n = 1060) and diagnostic (n = 23) CPMs representing 183 distinct index condition/outcome pairs. There was a threefold increase in the number of CPMs published between 2005 and 2014, compared to the prior 10-year interval from 1995 to 2004. The majority of CPMs were derived from either North American (n = 455, 42%) or European (n = 344, 32%) populations. The database contains 265 CPMs predicting outcomes for patients with coronary artery disease, 196 CPMs for population samples at risk for incident CVD, and 158 models for patients with stroke. Approximately two thirds (n = 701, 65%) of CPMs report a c-statistic, with a median reported c-statistic of 0.77 (IQR, 0.05). Of the CPMs reporting validations, only 333 (57%) report some measure of model calibration. Reporting of discrimination but not calibration is improving over time (p for trend < 0.0001 and 0.39 respectively).ConclusionsThere is substantial redundancy of CPMs for a wide spectrum of CVD conditions. While the number of CPMs continues to increase, model performance is often inadequately reported and calibration is infrequently assessed. More work is needed to understand the potential impact of this literature.

Dataset Information

Colorado Twin Registry: an update.

Publications

Colorado Twin Registry: an update.

Similar Datasets

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