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Gerard J. J. M. Borsboom

Bio: Gerard J. J. M. Borsboom is an academic researcher from Erasmus University Rotterdam. The author has contributed to research in topics: Population & Birth weight. The author has an hindex of 36, co-authored 76 publications receiving 6015 citations. Previous affiliations of Gerard J. J. M. Borsboom include Erasmus University Medical Center.


Papers
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Journal ArticleDOI
TL;DR: It is concluded that split-sample validation is inefficient, and bootstrapping is recommended for estimation of internal validity of a predictive logistic regression model.

2,155 citations

Journal ArticleDOI
TL;DR: A logistic regression model may be used to provide predictions of outcome for individual patients at another centre than where the model was developed to improve predictions for future patients.
Abstract: A logistic regression model may be used to provide predictions of outcome for individual patients at another centre than where the model was developed. When empirical data are available from this centre, the validity of predictions can be assessed by comparing observed outcomes and predicted probabilities. Subsequently, the model may be updated to improve predictions for future patients. As an example, we analysed 30-day mortality after acute myocardial infarction in a large data set (GUSTO-I, n = 40 830). We validated and updated a previously published model from another study (TIMI-II, n = 3339) in validation samples ranging from small (200 patients, 14 deaths) to large (10,000 patients, 700 deaths). Updated models were tested on independent patients. Updating methods included re-calibration (re-estimation of the intercept or slope of the linear predictor) and more structural model revisions (re-estimation of some or all regression coefficients, model extension with more predictors). We applied heuristic shrinkage approaches in the model revision methods, such that regression coefficients were shrunken towards their re-calibrated values. Parsimonious updating methods were found preferable to more extensive model revisions, which should only be attempted with relatively large validation samples in combination with shrinkage.

476 citations

Journal ArticleDOI
TL;DR: The findings indicate potential public health benefits of modifying socioeconomic characteristics of areas and suggest the prevalence of poor housing conditions, social disintegration, and unhealthy psychologic profiles and behaviors was higher in neighborhoods with a low socioeconomic status.
Abstract: This study sought to determine the contribution of neighborhood socioeconomic status to all-cause mortality and to explore its correlates. As part of the longitudinal "Gezondheid en LevensOmstandigheden Bevolking en omstreken" (GLOBE) study in the Netherlands, 8,506 randomly selected men and women aged 15-74 years from 86 neighborhoods in the city of Eindhoven reported on their socioeconomic status in the 1991 baseline survey. During the 6-year follow-up, 487 persons died. Neighborhood socioeconomic status was derived from individual reports on socioeconomic status. Its effect on mortality was stringently controlled for four individual-level socioeconomic indicators. Persons living in a neighborhood with a high percentage of unemployed/disabled or poor persons had a higher mortality risk than did those living in a neighborhood with a low percentage of unemployed/disabled or poor persons. This was independent of individual socioeconomic characteristics, including individual unemployment/disability or reports of severe financial problems. Educational and occupational neighborhood indicators were similarly, but less strongly, related to mortality. The prevalence of poor housing conditions, social disintegration, and unhealthy psychologic profiles and behaviors was higher in neighborhoods with a low socioeconomic status. Contextual effects of socioeconomic status may thus be due to one or more of these specific circumstances. The findings indicate potential public health benefits of modifying socioeconomic characteristics of areas.

255 citations

Journal ArticleDOI
TL;DR: Investigation of the usefulness of multiple genetic testing using simulated data demonstrated that a high to excellent discriminative accuracy can be obtained by simultaneously testing multiple susceptibility genes.

226 citations

Journal ArticleDOI
TL;DR: The study showed that epidemics in specific years were associated with specific geographical areas and were significantly more often preceded by a month of abnormally high minimum temperature in the preceding 3 months than based on random chance.

194 citations


Cited by
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Journal ArticleDOI
Paul Burton1, David Clayton2, Lon R. Cardon, Nicholas John Craddock3  +192 moreInstitutions (4)
07 Jun 2007-Nature
TL;DR: This study has demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in theBritish population is generally modest.
Abstract: There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.

9,244 citations

Journal ArticleDOI
TL;DR: Spirometric prediction equations for the 3–95-age range are now available that include appropriate age-dependent lower limits of normal for spirometric indices, which can be applied globally to different ethnic groups.
Abstract: The aim of the Task Force was to derive continuous prediction equations and their lower limits of normal for spirometric indices, which are applicable globally. Over 160,000 data points from 72 centres in 33 countries were shared with the European Respiratory Society Global Lung Function Initiative. Eliminating data that could not be used (mostly missing ethnic group, some outliers) left 97,759 records of healthy nonsmokers (55.3% females) aged 2.5-95 yrs. Lung function data were collated and prediction equations derived using the LMS method, which allows simultaneous modelling of the mean (mu), the coefficient of variation (sigma) and skewness (lambda) of a distribution family. After discarding 23,572 records, mostly because they could not be combined with other ethnic or geographic groups, reference equations were derived for healthy individuals aged 3-95 yrs for Caucasians (n=57,395), African-Americans (n=3,545), and North (n=4,992) and South East Asians (n=8,255). Forced expiratory value in 1 s (FEV(1)) and forced vital capacity (FVC) between ethnic groups differed proportionally from that in Caucasians, such that FEV(1)/FVC remained virtually independent of ethnic group. For individuals not represented by these four groups, or of mixed ethnic origins, a composite equation taken as the average of the above equations is provided to facilitate interpretation until a more appropriate solution is developed. Spirometric prediction equations for the 3-95-age range are now available that include appropriate age-dependent lower limits of normal. They can be applied globally to different ethnic groups. Additional data from the Indian subcontinent and Arabic, Polynesian and Latin American countries, as well as Africa will further improve these equations in the future.

3,975 citations

Journal ArticleDOI
TL;DR: It is suggested that reporting discrimination and calibration will always be important for a prediction model and decision-analytic measures should be reported if the predictive model is to be used for clinical decisions.
Abstract: The performance of prediction models can be assessed using a variety of methods and metrics. Traditional measures for binary and survival outcomes include the Brier score to indicate overall model performance, the concordance (or c) statistic for discriminative ability (or area under the receiver operating characteristic [ROC] curve), and goodness-of-fit statistics for calibration.Several new measures have recently been proposed that can be seen as refinements of discrimination measures, including variants of the c statistic for survival, reclassification tables, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Moreover, decision-analytic measures have been proposed, including decision curves to plot the net benefit achieved by making decisions based on model predictions.We aimed to define the role of these relatively novel approaches in the evaluation of the performance of prediction models. For illustration, we present a case study of predicting the presence of residual tumor versus benign tissue in patients with testicular cancer (n = 544 for model development, n = 273 for external validation).We suggest that reporting discrimination and calibration will always be important for a prediction model. Decision-analytic measures should be reported if the predictive model is to be used for clinical decisions. Other measures of performance may be warranted in specific applications, such as reclassification metrics to gain insight into the value of adding a novel predictor to an established model.

3,473 citations

Journal ArticleDOI
TL;DR: The Multi-Ethnic Study of Atherosclerosis was initiated in July 2000 to investigate the prevalence, correlates, and progression of subclinical cardiovascular disease (CVD) in a population-based sample of 6,500 men and women aged 45-84 years for identification and characterization of CVD events.
Abstract: The Multi-Ethnic Study of Atherosclerosis was initiated in July 2000 to investigate the prevalence, correlates, and progression of subclinical cardiovascular disease (CVD) in a population-based sample of 6,500 men and women aged 45-84 years. The cohort will be selected from six US field centers. Approximately 38% of the cohort will be White, 28% African-American, 23% Hispanic, and 11% Asian (of Chinese descent). Baseline measurements will include measurement of coronary calcium using computed tomography; measurement of ventricular mass and function using cardiac magnetic resonance imaging; measurement of flow-mediated brachial artery endothelial vasodilation, carotid intimal-medial wall thickness, and distensibility of the carotid arteries using ultrasonography; measurement of peripheral vascular disease using ankle and brachial blood pressures; electrocardiography; and assessments of microalbuminuria, standard CVD risk factors, sociodemographic factors, life habits, and psychosocial factors. Blood samples will be assayed for putative biochemical risk factors and stored for use in nested case-control studies. DNA will be extracted and lymphocytes will be immortalized for genetic studies. Measurement of selected subclinical disease indicators and risk factors will be repeated for the study of progression over 7 years. Participants will be followed through 2008 for identification and characterization of CVD events, including acute myocardial infarction and other coronary heart disease, stroke, peripheral vascular disease, and congestive heart failure; therapeutic interventions for CVD; and mortality.

3,367 citations

Book
01 Jun 2008
TL;DR: The Intergovernmental Panel on Climate Change (IPCC) Technical Paper Climate Change and Water draws together and evaluates the information in IPCC Assessment and Special Reports concerning the impacts of climate change on hydrological processes and regimes, and on freshwater resources.
Abstract: The Intergovernmental Panel on Climate Change (IPCC) Technical Paper Climate Change and Water draws together and evaluates the information in IPCC Assessment and Special Reports concerning the impacts of climate change on hydrological processes and regimes, and on freshwater resources – their availability, quality, use and management. It takes into account current and projected regional key vulnerabilities, prospects for adaptation, and the relationships between climate change mitigation and water. Its objectives are:

3,108 citations