scholarly journals Longitudinal medical records as a complement to routine drug safety signal analysis

2015 ◽  
Vol 24 (5) ◽  
pp. 486-494 ◽  
Author(s):  
Kristina Star ◽  
Sarah Watson ◽  
Lovisa Sandberg ◽  
Jeanette Johansson ◽  
I. Ralph Edwards
2018 ◽  
Vol 27 (11) ◽  
pp. 1249-1256 ◽  
Author(s):  
Caitlin Dodd ◽  
Alexandra Pacurariu ◽  
Osemeke U. Osokogu ◽  
Daniel Weibel ◽  
Carmen Ferrajolo ◽  
...  

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Junhao Liu ◽  
Jo Wick ◽  
Renee’ H. Martin ◽  
Caitlyn Meinzer ◽  
Dooti Roy ◽  
...  

Abstract Background Monitoring and reporting of drug safety during a clinical trial is essential to its success. More recent attention to drug safety has encouraged statistical methods development for monitoring and detecting potential safety signals. This paper investigates the potential impact of the process of the blinded investigator identifying a potential safety signal, which should be further investigated by the Data and Safety Monitoring Board with an unblinded safety data analysis. Methods In this paper, two-stage Bayesian hierarchical models are proposed for safety signal detection following a pre-specified set of interim analyses that are applied to efficacy. At stage 1, a hierarchical blinded model uses blinded safety data to detect a potential safety signal and at stage 2, a hierarchical logistic model is applied to confirm the signal with unblinded safety data. Results Any interim safety monitoring analysis is usually scheduled via negotiation between the trial sponsor and the Data and Safety Monitoring Board. The proposed safety monitoring process starts once 53 subjects have been enrolled into an eight-arm phase II clinical trial for the first interim analysis. Operating characteristics describing the performance of this proposed workflow are investigated using simulations based on the different scenarios. Conclusions The two-stage Bayesian safety procedure in this paper provides a statistical view to monitor safety during the clinical trials. The proposed two-stage monitoring model has an excellent accuracy of detecting and flagging a potential safety signal at stage 1, and with the most important feature that further action at stage 2 could confirm the safety issue.


2014 ◽  
Vol 37 (1) ◽  
pp. 94-104 ◽  
Author(s):  
Vaishali K. Patadia ◽  
Martijn J. Schuemie ◽  
Preciosa Coloma ◽  
Ron Herings ◽  
Johan van der Lei ◽  
...  

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Gang Yu ◽  
Xian Zeng ◽  
Shaoqing Ni ◽  
Zheng Jia ◽  
Weihong Chen ◽  
...  

Drug Safety ◽  
2012 ◽  
Vol 36 (1) ◽  
pp. 13-23 ◽  
Author(s):  
Preciosa M. Coloma ◽  
Paul Avillach ◽  
Francesco Salvo ◽  
Martijn J. Schuemie ◽  
Carmen Ferrajolo ◽  
...  

Drug Safety ◽  
2015 ◽  
Vol 38 (2) ◽  
pp. 207-217 ◽  
Author(s):  
Osemeke U. Osokogu ◽  
Federica Fregonese ◽  
Carmen Ferrajolo ◽  
Katia Verhamme ◽  
Sandra de Bie ◽  
...  

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