
Bart CuppenUniversity Medical Center Utrecht | UMC Utrecht · Department of Rheumatology & Clinical Immunology
Bart Cuppen
MD, PhD, epidemiologist
About
34
Publications
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359
Citations
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March 2013 - January 2017
Publications
Publications (34)
Background:
Several studies have employed microarray-based profiling to predict response to tumor necrosis factor-alpha inhibitors (TNFi) in rheumatoid arthritis (RA); yet efforts to validate these targets have failed to show predictive abilities acceptable for clinical practice.
Methods:
The eighty most extreme responders and non-responders to...
Introduction: Biological therapies have greatly improved the treatment efficacy in rheumatoid arthritis (RA). However, in clinical practice a significant proportion of patients experience an inadequate response to treatment. The aim of this study is to classify responding and non-responding rheumatoid arthritis patients treated with biological ther...
Objective: In rheumatoid arthritis (RA), it is of major importance to identify non-responders to tumour necrosis factor-α inhibitors (TNFi) before starting treatment, to prevent a delay in effective treatment. We developed a protein score for the response to TNFi treatment in RA and investigated its predictive value.
Method: In RA patients eligible...
A substantial proportion of rheumatoid arthritis (RA)-patients experience an insufficient response to glucocorticoids, an important therapeutic agent in RA. The multidrug-resistance 1 (MDR1) gene product P-glycoprotein (P-gp) is an efflux pump that actively transports substrates, such as glucocorticoids, out of the cell. We investigated if the vari...
Objectives:
Despite the success of TNF-alpha inhibitor (TNFi) treatment in rheumatoid arthritis (RA), a substantial number of patients necessitate discontinuation. Prediction thereof would be clinically relevant and guide the decision whether to start TNFi treatment.
Methods:
Data were used from the observational BiOCURA cohort, in which patient...
Objective:
As there are pharmacological differences between males and females, and glucocorticoid (GC) treatment is associated with increased cardiovascular mortality rate in rheumatoid arthritis (RA) patients, it is important to study serum polar lipid profiles of male and female patients in response to GC therapy. Gender differences may require...
In clinical practice, approximately one-third of patients with rheumatoid arthritis (RA) respond insufficiently to TNF-α inhibitors (TNFis). The aim of the study was to explore the use of a metabolomics to identify predictors for the outcome of TNFi therapy, and study the metabolomic fingerprint in active RA irrespective of patients' response. In t...
Scatter plot of the combined model between good responders and non-responders to TNFi therapy.
Patients were groups according to their observed responses on x-axis; y-axis represents the predicted probability calculated by the regression. The pseudo R-square, as a measure for the explained variance in the observed response by the model was 0.433 (C...
ROC curve for the combined model non-, moderate- and good responders to TNFi therapy.
The AUC-ROC was 0.760 (95% CI: 0.682?0.837).
(TIF)
List of relative standard deviations (RSD) for all 139 measured metabolites.
(PDF)
List of detected metabolites in oxylipins analysis.
(PDF)
Classification table of predicted good- and non-responders and observed good- and non-responders.
(PDF)
Net reclassification index of prediction models for sensitivity analysis.
(PDF)
Metabolites cross-sectionally associated with either baseline DAS28, ESR or CRP (p < 0.05) based on the complete cohort of bDMARD users (n = 231).
(PDF)
ROC curve for the clincial model containing non-, moderate- and good responders to TNFi therapy.
The AUC-ROC was 0.641 (95% CI: 0.548?0.734).
(TIF)
Baseline characteristics of all selected subjects (n = 231), and split for all EULAR good-responders and non-responders (n = 80 each).
(PDF)
List of detected metabolites in lipids analysis.
(PDF)
List of detected metabolites in amines analysis.
(PDF)
Scatter plot of the clinical model between good responders and non-responders to TNFi therapy.
Patients were groups according to their observed responses on x-axis; y-axis represents the predicted probability calculated by the regression. The pseudo R-square, as a measure for the explained variance in the observed response by the model was 0.147 (C...
Previously and currently used treatments of all selected subjects and split for responders and non-responders.
(PDF)
Background
In rheumatoid arthritis, prediction of response to TNF-alpha inhibitor (TNFi) treatment would be of clinical value. This study aims to discover miRNAs that predict response and aims to replicate results of two previous studies addressing this topic. Methods
From the observational BiOCURA cohort, 40 adalimumab- (ADA) and 40 etanercept- (E...
Oxidised lipids, covering enzymatic and auto-oxidation-synthesised mediators, are important signalling metabolites in inflammation while also providing a readout for oxidative stress, both of which are prominent physiological processes in a plethora of diseases. Excretion of these metabolites via urine is enhanced through the phase-II conjugation w...
Objectives. To review studies that address prediction of response to biologic treatment in RA and to explore the clinical utility of the studied (bio)markers. Methods. A search for relevant articles was performed in PubMed, Embase and Cochrane databases. Studies that presented predictive values or in which these could be calculated were selected. T...
Objectives:
To review studies that address prediction of response to biologic treatment in RA and to explore the clinical utility of the studied (bio)markers.
Methods:
A search for relevant articles was performed in PubMed, Embase and Cochrane databases. Studies that presented predictive values or in which these could be calculated were selected...
Background TNF-alpha inhibitor (TNFi) treatment has dramatically improved the outcome of RA patients. A substantial number of patients, however, fails to clinically respond to this therapy or experiences adverse-effects that necessitate discontinuation of therapy. In that sense, treatment success could be envisioned as a matter of balance between d...
Background In rheumatoid arthritis (RA) it is of major importance to distinguish non-responders to TNF-alpha inhibitor (TNFi) treatment before start to prevent a delay in effective treatment, potential side-effects and unnecessary healthcare costs. We investigated the ability of al large set of inflammatory proteins to predict (absence of) response...
Objectives A significant proportion of patients with rheumatoid arthritis do not respond adequately to biological treatment. We hypothesized that lack of response to (biological) disease-modifying anti-rheumatic drug (DMARD) is high in patients in whom the subjective, patient-reported, component of the Disease Activity Score 28 (DAS28) is high at b...
Background
Infections are important denominators of morbidity and mortality in patients with systemic lupus erythematosus (SLE). Pneumococcus pneumoniae has been identified as a relatively frequent cause of serious infections in SLE and vaccination against this pathogen is possible. We analysed the incidence of serious infections in a cohort of SLE...
Background In rheumatoid arthritis (RA) it is of major importance to distinguish non-responders to biological treatment to prevent a delay in effective treatment, potential side-effects and unnecessary healthcare costs. Prediction of response is a hot topic for years, yet predictive values remain modest. An explanation could be, that the measured r...
Background The commonly used Disease Activity Score based on 28 joints (DAS28) is a composite index composed of two somewhat subjective components (tender joint count and visual analogue scale general well-being) and two more objective components (swollen joint count and erythrocyte sedimentation rate). However, not all individual components of DAS...