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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/20631

Title: Statistical monitoring of data quality and consistency in the Stomach Cancer Adjuvant Multi-institutional Trial Group Trial
Authors: Timmermans, Catherine
Doffagne, Erik
Venet, David
Desmet, Lieven
Legrand, Catherine
Burzykowski, Tomasz
Buyse, Marc
Issue Date: 2016
Publisher: SPRINGER
Citation: GASTRIC CANCER, 19 (1), p. 24-30
Abstract: Data quality may impact the outcome of clinical trials; hence, there is a need to implement quality control strategies for the data collected. Traditional approaches to quality control have primarily used source data verification during on-site monitoring visits, but these approaches are hugely expensive as well as ineffective. There is growing interest in central statistical monitoring (CSM) as an effective way to ensure data quality and consistency in multicenter clinical trials. CSM with SMART (TM) uses advanced statistical tools that help identify centers with atypical data patterns which might be the sign of an underlying quality issue. This approach was used to assess the quality and consistency of the data collected in the Stomach Cancer Adjuvant Multi-institutional Trial Group Trial, involving 1495 patients across 232 centers in Japan. In the Stomach Cancer Adjuvant Multi-institutional Trial Group Trial, very few atypical data patterns were found among the participating centers, and none of these patterns were deemed to be related to a quality issue that could significantly affect the outcome of the trial. CSM can be used to provide a check of the quality of the data from completed multicenter clinical trials before analysis, publication, and submission of the results to regulatory agencies. It can also form the basis of a risk-based monitoring strategy in ongoing multicenter trials. CSM aims at improving data quality in clinical trials while also reducing monitoring costs.
Notes: [Timmermans, Catherine; Doffagne, Erik; Buyse, Marc] CluePoints SA, B-1435 Mont St Guibert, Belgium. [Timmermans, Catherine; Desmet, Lieven; Legrand, Catherine] Catholic Univ Louvain, Inst Stat Biostat & Sci Actuarielles, Louvain La Neuve, Belgium. [Venet, David] Univ Brussels, Inst Rech Interdisciplinaires & Dev Intelligence, Brussels, Belgium. [Burzykowski, Tomasz] Int Inst Drug Dev, Louvain La Neuve, Belgium. [Burzykowski, Tomasz; Buyse, Marc] Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, Diepenbeek, Belgium. [Buyse, Marc] Int Inst Drug Dev, Cambridge, MA USA.
URI: http://hdl.handle.net/1942/20631
DOI: 10.1007/s10120-015-0533-9
ISI #: 000367260300006
ISSN: 1436-3291
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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