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

Abstract

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.

Use of the Beta-Binomial Model for Central Statistical Monitoring of Multicenter Clinical Trials

“…We have implemented this approach in the SMART TM software (Statistical Monitoring Applied to Research Trials), which can be used to identify data quality and consistency issues in multicentre clinical trials [18]. Reference [19] provides details on data quality checks performed in a large trial for patients with gastric cancer.…”

Central statistical monitoring of investigator-led clinical trials in oncology

“…It is visually useful to display the DIS as a function of center size, as shown in Fig. 5 [36]. When the trial includes many centers, it may be useful to limit the number of centers found to have statistical inconsistencies by setting the false discovery rate to a low probability, such as 5% [37].…”

“…When the trial includes many centers, it may be useful to limit the number of centers found to have statistical inconsistencies by setting the false discovery rate to a low probability, such as 5% [37]. Timmermans et al provide a detailed example of CSM applied to a completed trial, the Stomach Cancer Adjuvant Multi-Institutional Trial (SAMIT) Group Trial, involving 1495 patients across 232 centers in Japan, which was subsequently published [36,38]. This trial, like many trials in oncology, included many centers with only a couple of patients [36].…”

A Hercule Poirot of clinical research

“…An investigation revealed that this center was fully open on Saturdays, and therefore this inconsistency in the data could be explained. Data inconsistencies found at other centers included small variability for the drug volume, similar trends for bloodtest-related measurements and symptom grades, failure of entering the last date the patient was reported to be relapsefree, and other missing values [4]. None of these data patterns were suspected to have had any impact on the outcome of the trial, nor was there any evidence of misconduct that could have affected the safety or the management of the patients at these centers.…”

“…All individual patient data were sent to CluePoints, a company that is pioneering the use of central statistical monitoring (CSM) to provide an objective and exhaustive assessment of data quality and consistency in multicenter clinical trials. In this issue of Gastric Cancer, a group of investigators from CluePoints and several universities in Belgium reported on the practical use of the SMART TM CSM software on this large randomized phase III trial for gastric cancer [4]. The methods of CSM are technically complex, but the concept behind the approach is stunningly simple: it consists of identifying centers whose data differ significantly from the data provided by all other centers.…”