2019
DOI: 10.1111/apt.15609
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A clinical decision support tool may help to optimise vedolizumab therapy in Crohn’s disease

Abstract: Background:A clinical decision support tool (CDST) has been validated for predicting treatment effectiveness of vedolizumab (VDZ) in Crohn's disease.Aim: To assess the utility of this CDST for predicting exposure-efficacy and disease outcomes.Methods: Using data from three independent datasets (GEMINI, GETAID and VICTORY), we assessed clinical remission rates and measured VDZ exposure, rapidity of onset of action, response to dose optimisation and progression to surgery by CDST-defined response groups (low, in… Show more

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Cited by 33 publications
(33 citation statements)
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“…Both for CD and UC, clinical decision support tools deriving from similar analyses in the phase III studies and validated in other real-world populations have previously been published [ 39 , 44 , 45 ]. Although it is clear that they rely on data of higher quality, a potential disadvantage of those models is that they require information on endoscopic disease activity.…”
Section: Discussionmentioning
confidence: 99%
“…Both for CD and UC, clinical decision support tools deriving from similar analyses in the phase III studies and validated in other real-world populations have previously been published [ 39 , 44 , 45 ]. Although it is clear that they rely on data of higher quality, a potential disadvantage of those models is that they require information on endoscopic disease activity.…”
Section: Discussionmentioning
confidence: 99%
“…I would like to thank Drs. Verstockt and Ferrante for their editorial on our recently published paper describing further validation of a vedolizumab‐specific clinical decision support tool (VDZ‐CDST) for Crohn's disease (CD) . The authors highlight several key points with the majority of discussion focused around whether the VDZ‐CDST is truly drug specific.…”
Section: Drug‐specific Predictions With Only Slight Modifications In mentioning
confidence: 99%
“…The development of models to assist clinicians in the assessment of disease and the likelihood of complications were highlighted. [6][7][8][9] These models can accommodate multiple variables and produce projections of the probability of responding to treatments, achieving clinical remission, or developing complications. These decision-support tools can identify patients who are more likely to respond to an individual treatment.…”
mentioning
confidence: 99%