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659 results on '"Vergouwe, Yvonne"'

151. External Validation of a Referral Rule for Axial Spondyloarthritis in Primary Care Patients with Chronic Low Back Pain

Author

van Hoeven, Lonneke, Vergouwe, Yvonne, de Buck, P D M, Luime, Jolanda J, Hazes, Johanna M W, Weel, Angelique E A M, van Hoeven, Lonneke, Vergouwe, Yvonne, de Buck, P D M, Luime, Jolanda J, Hazes, Johanna M W, and Weel, Angelique E A M

Abstract

OBJECTIVES: To validate and optimize a referral rule to identify primary care patients with chronic low back pain (CLBP) suspected for axial spondyloarthritis (axSpA).DESIGN: Cross-sectional study with data from 19 Dutch primary care practices for development and 38 for validation.PARTICIPANTS: Primary care patients aged 18-45 years with CLBP existing more than three months and onset of back pain started before the age of 45 years.MAIN OUTCOME: The number of axSpA patients according to the ASAS criteria.METHODS: The referral rule (CaFaSpA referral rule) was developed using 364 CLBP patients from 19 primary care practices and contains four easy to use variables; inflammatory back pain, good response to nonsteriodal anti-inflammatory drugs, family history of spondyloarthritis and a back pain duration longer than five years. This referral rule is positive when at least two variables are present. Validation of the CaFaSpA rule was accomplished in 579 primary care CLBP patients from 38 practices from other areas. Performance of the referral rule was assessed by c-statistic and calibration plot. To fit the final referral rule the development and validation datasets were pooled leading to a total study population of 943 primary care participants.RESULTS: The referral rule was validated in 579 patients (41% male, mean age 36 (sd7.0). The percentage of identified axSpA patients was 16% (n=95). External validation resulted in satisfactory calibration and reasonable discriminative ability (c-statistics 0.70 [95% CI, 0.64-0.75]). In the pooled dataset sensitivity and specificity of the referral rule were 75% and 58%.CONCLUSIONS: The CaFaSpA referral rule for axSpA consists of four easy to use predictors for primary care physicians and has a good predictive value in this validation study. The referral rule has the potential to be a screening tool for primary care by identifying CLBP patients suspected for axSpA.

Published
2015

152. The Prognostic Value of the Work Ability Index for Sickness Absence among Office Workers

Author

Reeuwijk, KG, Robroek, Suzan, Niessen, MAJ, Kraaijenhagen, RA, Vergouwe, Yvonne, Burdorf, Lex, Reeuwijk, KG, Robroek, Suzan, Niessen, MAJ, Kraaijenhagen, RA, Vergouwe, Yvonne, and Burdorf, Lex

Abstract

Background The work ability index (WAI) is a frequently used tool in occupational health to identify workers at risk for a reduced work performance and for work-related disability. However, information about the prognostic value of the WAI to identify workers at risk for sickness absence is scarce. Objectives To investigate the prognostic value of the WAI for sickness absence, and whether the discriminative ability differs across demographic subgroups. Methods At baseline, the WAI (score 7-49) was assessed among 1,331 office workers from a Dutch financial service company. Sickness absence was registered during 12-months follow-up and categorised as 0 days, 0< days< 5, 5 <= days< 15, and >= 15 days in one year. Associations between WAI and sickness absence were estimated by multinomial regression analyses. Discriminative ability of the WAI was assessed by the Area Under the Curve (AUC) and Ordinal c-index (ORC). Test characteristics were determined for dichotomised outcomes. Additional analyses were performed for separate WAI dimensions, and subgroup analyses for demographic groups. Results A lower WAI was associated with sickness absence (>= 15 days vs. 0 days: per point lower WAI score OR=1.27; 95% CI 1.21-1.33). The WAI showed reasonable ability to discriminate between categories of sickness absence (ORC=0.65; 95% CI 0.63-0.68). Highest discrimination was found for comparing workers with >= 15 sick days with 0 sick days (AUC=0.77) or with 1-5 sick days (AUC=0.69). At the cut-off for poor work ability (WAI <= 27) the sensitivity to identify workers at risk for >= 15 sick days was 7.5%, the specificity 99.6%, and the positive predictive value 82%. The performance was similar across demographic subgroups. Conclusions The WAI could be used to identify workers at high risk for prolonged sickness absence. However, due to low sensitivity many workers will be missed. Hence, additional factors are required to better identify workers at highest ri

Published
2015

159. Prediction of cashew nut allergy in sensitized children.

Author

Valk, Johanna P.M., Vergouwe, Yvonne, Gerth van Wijk, Roy, Steyerberg, Ewout W., Reitsma, Marit, Wichers, Harry J., Savelkoul, Huub F.J., Vlieg‐Boerstra, Berber, Groot, Hans, Dubois, Anthony E.J., and Jong, Nicolette W.

Subjects
*CASHEW nuts, *FOOD allergy
Published
2017
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160. Assessing discriminative ability of risk models in clustered data

Author

van Klaveren, David, Steyerberg, Ewout, Perel, P, Vergouwe, Yvonne, van Klaveren, David, Steyerberg, Ewout, Perel, P, and Vergouwe, Yvonne

Abstract

Background: The discriminative ability of a risk model is often measured by Harrell's concordance-index (c-index). The c-index estimates for two randomly chosen subjects the probability that the model predicts a higher risk for the subject with poorer outcome (concordance probability). When data are clustered, as in multicenter data, two types of concordance are distinguished: concordance in subjects from the same cluster (within-cluster concordance probability) and concordance in subjects from different clusters (between-cluster concordance probability). We argue that the within-cluster concordance probability is most relevant when a risk model supports decisions within clusters (e.g. who should be treated in a particular center). We aimed to explore different approaches to estimate the within-cluster concordance probability in clustered data. Methods: We used data of the CRASH trial (2,081 patients clustered in 35 centers) to develop a risk model for mortality after traumatic brain injury. To assess the discriminative ability of the risk model within centers we first calculated cluster-specific c-indexes. We then pooled the cluster-specific c-indexes into a summary estimate with different meta-analytical techniques. We considered fixed effect meta-analysis with different weights (equal; inverse variance; number of subjects, events or pairs) and random effects meta-analysis. We reflected on pooling the estimates on the log-odds scale rather than the probability scale. Results: The cluster-specific c-index varied substantially across centers (IQR = 0.70-0.81; I-2 = 0.76 with 95% confidence interval 0.66 to 0.82). Summary estimates resulting from fixed effect meta-analysis ranged from 0.75 (equal weights) to 0.84 (inverse variance weights). With random effects meta- analysis - accounting for the observed heterogeneity in c-indexes across clusters - we estimated a mean of 0.77, a between-cluster variance of 0.0072 and a 95% prediction interval of 0.60 to 0.95. The nor

Published
2014

166. Predicting 3-Year Mortality After Percutaneous Coronary Intervention

Author

Iqbal, Javaid, primary, Vergouwe, Yvonne, additional, Bourantas, Christos V., additional, Klaveren, David V., additional, Zhang, Yao-Jun, additional, Campos, Carlos M., additional, García-García, Hector M., additional, Morel, Marie-Angele, additional, Valgimigli, Marco, additional, Windecker, Stephan, additional, Steyerberg, Ewout W., additional, and Serruys, Patrick W., additional

Published
2014
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167. Epigenome-based cancer risk prediction: rationale, opportunities and challenges

Author

Widschwendter, Martin, Jones, Allison, Evans, Iona, Reisel, Daniel, Dillner, Joakim, Sundström, Karin, Steyerberg, Ewout W., Vergouwe, Yvonne, Wegwarth, Odette, Rebitschek, Felix G., Siebert, Uwe, Sroczynski, Gaby, de Beaufort, Inez D., Bolt, Ineke, Cibula, David, Zikan, Michal, Bjørge, Line, Colombo, Nicoletta, Harbeck, Nadia, Dudbridge, Frank, Tasse, Anne-Marie, Knoppers, Bartha M., Joly, Yann, Teschendorff, Andrew E., and Pashayan, Nora

Abstract

Epigenetic misprogramming is an essential component of cancer development.DNA methylation-based risk-prediction models provide novel opportunities for risk-tailored screening and prevention of cancer.Multidisciplinary collaborative research is needed to overcome the scientific challenges associated with the discovery of DNA methylation markers for risk-prediction, such as identifying surrogate tissues and developing novel analytical methods.Implementation of epigenome-based risk-tailored screening and prevention programmes requires several ethical, legal, social, organizational and economic challenges to be addressed in addition to the engagement of policymakers, health-care professionals and the public.

Published
2018
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170. Reporting and Methods in Clinical Prediction Research: A Systematic Review

Author

Bouwmeester, W (Walter), Zuithoff, NPA, Mallett, S, Geerlings, MI (Miriam), Vergouwe, Yvonne, Steyerberg, Ewout, Altman, DG, Moons, KGM (Karel), Bouwmeester, W (Walter), Zuithoff, NPA, Mallett, S, Geerlings, MI (Miriam), Vergouwe, Yvonne, Steyerberg, Ewout, Altman, DG, and Moons, KGM (Karel)

Abstract

Background: We investigated the reporting and methods of prediction studies, focusing on aims, designs, participant selection, outcomes, predictors, statistical power, statistical methods, and predictive performance measures. Methods and Findings: We used a full hand search to identify all prediction studies published in 2008 in six high impact general medical journals. We developed a comprehensive item list to systematically score conduct and reporting of the studies, based on recent recommendations for prediction research. Two reviewers independently scored the studies. We retrieved 71 papers for full text review: 51 were predictor finding studies, 14 were prediction model development studies, three addressed an ex Conclusions: The majority of prediction studies in high impact journals do not follow current methodological recommendations, limiting their reliability and applicability.

Published
2012

176. 1037 The Choice of NSAID Treatment With Respect To Upper Gastrointestinal Complications and Cardiovascular Complications: A Treatment Decision Model Using Multiple Healthcare Databases

Author

Valkhoff, Vera E., primary, Romio, Silvana, additional, Vergouwe, Yvonne, additional, Arfe, Andrea, additional, Castellsague, Jordi, additional, Garbe, Edeltraut, additional, Herings, Ron M., additional, Lucchi, Silvia, additional, Nicotra, Federica, additional, Schade, Rene, additional, Schink, Tania, additional, Straatman, Huub, additional, Varas, Christina, additional, Villa, Marco, additional, Kuipers, Ernst J., additional, Steyerberg, Ewout W., additional, and Sturkenboom, Miriam C., additional

Published
2013
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178. PREDICTION OF ONE-YEAR MORTALITY IN PATIENTS WITH ACUTE CORONARY SYNDROMES UNDERGOING PCI FROM THE ACUITY (ACUTE CATHETERIZATION AND URGENT INTERVENTION TRIAGE STRATEGY) TRIAL VALIDATION OF THE LOGISTIC CLINICAL SYNTAX SCORE

Author

Farooq, Vasim, primary, Vergouwe, Yvonne, additional, Genereux, Philippe, additional, Palmerini, Tullio, additional, Bouranats, Christos V., additional, Caixeta, Adriano, additional, Garcia, Hector, additional, Kappetein, A., additional, Morel, Marie-angèle, additional, Valgimigli, Marco, additional, Windecker, Stephan, additional, Dawkins, Keith, additional, Steyerberg, Ewout, additional, Serruys, Patrick, additional, and Stone, Gregg, additional

Published
2013
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179. A new concordance measure for risk prediction models in external validation settings.

Author

Klaveren, David, Gönen, Mithat, Steyerberg, Ewout W., and Vergouwe, Yvonne

Subjects
DIAGNOSIS related groups, RESEARCH funding, LOGISTIC regression analysis, STATISTICAL models
Abstract

Concordance measures are frequently used for assessing the discriminative ability of risk prediction models. The interpretation of estimated concordance at external validation is difficult if the case-mix differs from the model development setting. We aimed to develop a concordance measure that provides insight into the influence of case-mix heterogeneity and is robust to censoring of time-to-event data. We first derived a model-based concordance (mbc) measure that allows for quantification of the influence of case-mix heterogeneity on discriminative ability of proportional hazards and logistic regression models. This mbc can also be calculated including a regression slope that calibrates the predictions at external validation (c-mbc), hence assessing the influence of overall regression coefficient validity on discriminative ability. We derived variance formulas for both mbc and c-mbc. We compared the mbc and the c-mbc with commonly used concordance measures in a simulation study and in two external validation settings. The mbc was asymptotically equivalent to a previously proposed resampling-based case-mix corrected c-index. The c-mbc remained stable at the true value with increasing proportions of censoring, while Harrell's c-index and to a lesser extent Uno's concordance measure increased unfavorably. Variance estimates of mbc and c-mbc were well in agreement with the simulated empirical variances. We conclude that the mbc is an attractive closed-form measure that allows for a straightforward quantification of the expected change in a model's discriminative ability due to case-mix heterogeneity. The c-mbc also reflects regression coefficient validity and is a censoring-robust alternative for the c-index when the proportional hazards assumption holds. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Published
2016
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180. Prediction of Chlamydia trachomatis infection to facilitate selective screening on population and individual level: a cross-sectional study of a population-based screening programme.

Author

van Klaveren, David, Götz, Hannelore M., de Coul, Eline LM Op, Steyerberg, Ewout W., Vergouwe, Yvonne, and Op de Coul, Eline Lm

Subjects
CHLAMYDIA infection diagnosis, CHLAMYDIA infections, CHLAMYDIA trachomatis, ETHNIC groups, MEDICAL screening, METROPOLITAN areas, HUMAN sexuality, SOCIAL classes, ACQUISITION of data, CROSS-sectional method, SEXUAL partners, PSYCHOLOGY
Abstract

Objectives: To develop prediction models for Chlamydia trachomatis (Ct) infection with different levels of detail in information, that is, from readily available data in registries and from additional questionnaires.Methods: All inhabitants of Rotterdam and Amsterdam aged 16-29 were invited yearly from 2008 until 2011 for home-based testing. Their registry data included gender, age, ethnicity and neighbourhood-level socioeconomic status (SES). Participants were asked to fill in a questionnaire on education, sexually transmitted infection history, symptoms, partner information and sexual behaviour. We developed prediction models for Ct infection using first-time participant data-including registry variables only and with additional questionnaire variables-by multilevel logistic regression analysis to account for clustering within neighbourhoods. We assessed the discriminative ability by the area under the receiver operating characteristic curve (AUC).Results: Four per cent (3540/80 385) of the participants was infected. The strongest registry predictors for Ct infection were young age (especially for women) and Surinamese, Antillean or sub-Saharan African ethnicity. Neighbourhood-level SES was of minor importance. Strong questionnaire predictors were low to intermediate education level, ethnicity of the partner (non-Dutch) and having sex with casual partners. When using a prediction model including questionnaire risk factors (AUC 0.74, 95% CI 0.736 to 0.752) for selective screening, 48% of the participating population needed to be screened to find 80% (95% CI 78.4% to 81.0%) of Ct infections. The model with registry risk factors only (AUC 0.67, 95% CI 0.656 to 0.675) required 60% to be screened to find 78% (95% CI 76.6% to 79.4%) of Ct infections.Conclusions: A registry-based prediction model can facilitate selective Ct screening at population level, with further refinement at the individual level by including questionnaire risk factors. [ABSTRACT FROM AUTHOR]

Published
2016
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184. Combined anatomical and clinical factors for the long-term risk stratification of patients undergoing percutaneous coronary intervention: the Logistic Clinical SYNTAX score

Author

Farooq, Vasim, primary, Vergouwe, Yvonne, additional, Räber, Lorenz, additional, Vranckx, Pascal, additional, Garcia-Garcia, Hector, additional, Diletti, Roberto, additional, Kappetein, Arie Pieter, additional, Morel, Marie Angèle, additional, de Vries, Ton, additional, Swart, Michael, additional, Valgimigli, Marco, additional, Dawkins, Keith D., additional, Windecker, Stephan, additional, Steyerberg, Ewout W., additional, and Serruys, Patrick W., additional

Published
2012
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196. COMBINED ANATOMICAL AND CLINICAL FACTORS FOR THE RISK STRATIFICATION OF PATIENTS UNDERGOING PERCUTANEOUS CORONARY INTERVENTION: THE LOGISTIC CLINICAL SYNTAX SCORE

Author

Farooq, Vasim, primary, Vergouwe, Yvonne, additional, Raber, Lorenz, additional, Vrancx, Pascal, additional, Garcia, Hector, additional, Brugaletta, Salvatore, additional, Kappetein, A., additional, Morel, Marie-angèle, additional, de Vries, Ton, additional, Swart, Michael, additional, Dawkins, Keith, additional, Valgimigli, Marco, additional, Windecker, Stephan, additional, Steyerberg, Ewout W., additional, and Serruys, Patrick, additional

Published
2012
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198. Validation of the Feverkidstool and procalcitonin for detecting serious bacterial infections in febrile children

Author

Nijman, Ruud G, Vergouwe, Yvonne, Moll, Henriëtte A, Smit, Frank J, Weerkamp, Floor, Steyerberg, Ewout W, van der Lei, Johan, de Rijke, Yolanda B, and Oostenbrink, Rianne

Abstract

BackgroundTo validate the Feverkidstool, a prediction model consisting of clinical signs and symptoms and C-reactive protein (CRP) to identify serious bacterial infections (SBIs) in febrile children, and to determine the incremental diagnostic value of procalcitonin.MethodsThis prospective observational study that was carried out at two Dutch emergency departments included children with fever, aged 1 month to 16 years. The prediction models were developed with polytomous logistic regression differentiating “pneumonia” and “other SBIs” from “non-SBIs” using standardized, routinely collected data on clinical signs and symptoms, CRP, and procalcitonin.ResultsA total of 1,085 children were included with a median age of 1.6 years (interquartile range 0.8–3.4); 73 children (7%) had pneumonia and 98 children (9%) had other SBIs. The Feverkidstool showed good discriminative ability in this new population. After adding procalcitonin to the Feverkidstool, c-statistic for “pneumonia” increased from 0.85 (95% confidence interval (CI) 0.76–0.94) to 0.86 (0.77–0.94) and for “other SBI” from 0.81 (0.73–0.90) to 0.83 (0.75– 0.91). A model with clinical features and procalcitonin performed similar to the Feverkidstool.ConclusionThis study confirms the external validity of the Feverkidstool, with CRP and procalcitonin being equally valuable for predicting SBI in our population of febrile children. Our findings do not support routine dual use of CRP and procalcitonin.

Published
2018
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