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Journal article
Composite Indices Using 3 or 4 Components of the Core Data Set Have Similar Predictive Ability to Measure Disease Activity in RA: Evidence from the DANCER and REFLEX Studies
Autoimmune diseases, v 2013, 367190
04 Dec 2013
PMID: 24368941
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Background. Understanding how disease-assessment indices perform in rheumatoid arthritis (RA) clinical trials can inform their use in routine practice. The study objective was to assess the capacity of combinations of RA Core Data Set measures to distinguish rituximab from control treatment. Methods. Post hoc analysis of two randomised clinical trials was used. Composite Efficacy Indices were derived by combining three or four RA Core Data Set measures from three possible sources: physician, patient, and laboratory. Results. All 105 Composite Efficacy Indices evaluated significantly distinguished rituximab from control treatment (P<10−7). Generally, indices containing measures from three different sources had a greater capacity to distinguish rituximab from control treatment than indices containing three measures from one source. Composite Efficacy Indices performed as well as validated indices such as DAS28, RAPID3, and CDAI. Conclusions. All indices composed of three or four RA Core Data Set measures have a similar capacity to detect treatment differences. These results suggest that the precise measurement used is less important than whether any measurement is performed, although selection should be consistent for each patient. Therefore, the choice of assessment tool should not be limited to a prescribed list and should instead be left to the clinician’s discretion.
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Details
- Title
- Composite Indices Using 3 or 4 Components of the Core Data Set Have Similar Predictive Ability to Measure Disease Activity in RA: Evidence from the DANCER and REFLEX Studies
- Creators
- Martin J. Bergman - Drexel UniversityWilliam Reiss - GenentechCarol Chung - GenentechPamela Wong - GenentechAdam Turpcu - Genentech
- Contributors
- Kamal D. Moudgil (Editor)
- Publication Details
- Autoimmune diseases, v 2013, 367190
- Publisher
- Hindawi Publishing Corporation
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Medicine (Graduate)
- Web of Science ID
- WOS:000219157900007
- Scopus ID
- 2-s2.0-84893698442
- Other Identifier
- 991019168693604721
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- Collaboration types
- Industry collaboration
- Domestic collaboration
- Web of Science research areas
- Immunology