Blinded Safety Signal Monitoring for the FDA IND Reporting Final Rule
We introduce a safety monitoring procedure for two-arm blinded clinical trials. This procedure incorporates a Bayesian hierarchical model for using prior information and pooled event rates to make inferences on the rate of adverse events of special intere
- PDF / 164,508 Bytes
- 11 Pages / 439.36 x 666.15 pts Page_size
- 13 Downloads / 202 Views
Abstract We introduce a safety monitoring procedure for two-arm blinded clinical trials. This procedure incorporates a Bayesian hierarchical model for using prior information and pooled event rates to make inferences on the rate of adverse events of special interest in the test treatment arm. We describe a collaborative process for specifying the prior and calibrating the operating characteristics. Keywords Adverse events • Bayesian inference • Blinded data • Clinical trials • Safety monitoring
1 Introduction Regulatory requirements and guidance documents regarding clinical trials place primary responsibility on the sponsor for ongoing safety evaluation of investigational products (Guideline for Good Clinical Practice E6(R1) 1996; European Commission 2006; US Department of Health and Human Services Food and Drug Administration 2012), as the sponsor is best positioned to assess the overall safety of these drugs and devices. Sponsors should review aggregated safety data throughout the development program and facilitate early planning for assessment of emerging safety signals by establishing a multidisciplinary Safety Management Team (SMT) (US Department of Health and Human Services Food and Drug Administration 2012; Crowe et al. 2009; Xia et al. 2011; Chuang-Stein and Xia 2013). This collaborative team of subject matter experts from clinical, safety, and statistics groups could synthesize all available information to provide a complete assessment of the safety profile. Adverse events of special interest (AESI) could be established and analyses
G. Ball () Biostatistics and Research Decision Sciences, Merck Research Laboratories, 126 E Lincoln Ave, Rahway, NJ 07065-4607, USA e-mail: [email protected] P.M. Schnell Division of Biostatistics, School of Public Health, University of Minnesota, 420 Delaware St SE, Minneapolis, MN 55455-0381, USA © Springer International Publishing Switzerland 2016 J. Lin et al. (eds.), Statistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics, ICSA Book Series in Statistics, DOI 10.1007/978-3-319-42568-9_17
201
202
G. Ball and P.M. Schnell
pre-specified in order to identify and understand potential safety signals as early as possible in the drug development process. The SMT would evaluate accumulating blinded data on a regular and ongoing basis and alert the Safety Review Committee if evidence of a higher than expected AESI rate were to emerge. Regulations also assert that trials should only be carried out if the risks have been adequately assessed and can be appropriately managed (Guideline for Good Clinical Practice E6(R1) 1996; World Medical Association 2006; Council for International Organizations of Medical Sciences 2002). Potential issues that may be suspected because of preclinical data or other available sources should be targeted for evaluation (US Department of Health and Human Services Food and Drug Administration 2005). In the United States, sponsors must report a suspected adverse reaction if an aggregate analysis indicat
Data Loading...
