As part of central statistical monitoring of multicenter clinical trial data, we propose a procedure based on the beta-binomial distribution for the detection of centers with atypical values for the probability of some event. The procedure makes no assumptions about the typical event proportion and uses the event counts from all centers to derive a reference model. The procedure is shown through simulations to have high sensitivity and high specificity if the contamination rate is small and the atypical event proportions are the result of some systematic shift in the underlying data generating mechanism.
Bloomfield Peter, Fourier Analysis of Time Series : An Introduction, ISBN:9780471722236, 10.1002/0471722235
Chuang-Stein C., Drug Information Journal, 27, 515 (1993)
Desmet L., Venet D., Doffagne E., Timmermans C., Burzykowski T., Legrand C., Buyse M., Linear mixed-effects models for central statistical monitoring of multicenter clinical trials, 10.1002/sim.6294
Griffiths D. A., Maximum Likelihood Estimation for the Beta-Binomial Distribution and an Application to the Household Distribution of the Total Number of Cases of a Disease, 10.2307/2529131
Kirkwood Amy A, Cox Trevor, Hackshaw Allan, Application of methods for central statistical monitoring in clinical trials, 10.1177/1740774513494504
Lindblad Anne S, Manukyan Zorayr, Purohit-Sheth Tejashri, Gensler Gary, Okwesili Paul, Meeker-O’Connell Ann, Ball Leslie, Marler John R, Central site monitoring: Results from a test of accuracy in identifying trials and sites failing Food and Drug Administration inspection, 10.1177/1740774513508028
Pogue Janice M, Devereaux PJ, Thorlund Kristian, Yusuf Salim, Central statistical monitoring: Detecting fraud in clinical trials, 10.1177/1740774512469312
R Development Core Team, R: A Language and Environment for Statistical Computing (2011)
TARONE R. E., Testing the goodness of fit of the binomial distribution, 10.1093/biomet/66.3.585
Timmermans Catherine, Doffagne Erik, Venet David, Desmet Lieven, Legrand Catherine, Burzykowski Tomasz, Buyse Marc, Statistical monitoring of data quality and consistency in the Stomach Cancer Adjuvant Multi-institutional Trial Group Trial, 10.1007/s10120-015-0533-9
Timmermans Catherine, Venet David, Burzykowski Tomasz, Data-driven risk identification in phase III clinical trials using central statistical monitoring, 10.1007/s10147-015-0877-5
Tripathi Ram C., Gupta Ramesh C., Gurland John, Estimation of parameters in the beta binomial model, 10.1007/bf01720588
Venet David, Doffagne Erik, Burzykowski Tomasz, Beckers François, Tellier Yves, Genevois-Marlin Eric, Becker Ursula, Bee Valerie, Wilson Veronique, Legrand Catherine, Buyse Marc, A statistical approach to central monitoring of data quality in clinical trials, 10.1177/1740774512447898
Williams D. A., 394: The Analysis of Binary Responses from Toxicological Experiments Involving Reproduction and Teratogenicity, 10.2307/2529820
Young-Xu Yinong, Chan K Arnold, Pooling overdispersed binomial data to estimate event rate, 10.1186/1471-2288-8-58
Bibliographic reference
Desmet, Lieven ; Venet, David ; Doffagne, Erik ; Timmermans, Catherine ; Legrand, Catherine ; et. al. Use of the beta-binomial model for central statistical monitoring of multicenter clinical trials. In: Statistics in Biopharmaceutical Research, Vol. 9, no. 1, p. 1-11 (2017)
