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Gastric Cancer. 2016 Jan;19(1):24-30. doi: 10.1007/s10120-015-0533-9. Epub 2015 Aug 23.

Statistical monitoring of data quality and consistency in the Stomach Cancer Adjuvant Multi-institutional Trial Group Trial.

Author information

1
CluePoints S.A., Rue Emile Francqui 1, 1435, Mont-Saint-Guibert, Belgium.
2
Institut de Statistique, Biostatistique et Sciences Actuarielles, Université Catholique de Louvain, Louvain-la-Neuve, Belgium.
3
Institut de Recherches Interdisciplinaires et de Développements en Intelligence Artificielle, Brussels University, Brussels, Belgium.
4
International Drug Development Institute, Louvain-la-Neuve, Belgium.
5
Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.
6
CluePoints S.A., Rue Emile Francqui 1, 1435, Mont-Saint-Guibert, Belgium. marc.buyse@iddi.com.
7
Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium. marc.buyse@iddi.com.
8
International Drug Development Institute, Cambridge, MA, USA. marc.buyse@iddi.com.

Abstract

INTRODUCTION:

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.

METHODS:

CSM with SMART™ 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.

RESULTS:

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.

DISCUSSION:

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.

KEYWORDS:

Clinical trials; Multicenter study; Quality control; Risk management; Stomach neoplasm

PMID:
26298185
DOI:
10.1007/s10120-015-0533-9
[Indexed for MEDLINE]

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