Inference and Decision Making for 21st-Century Drug Development and Approval

References

• Bayarri, M. J., and Berger, J.O. (2004), “The Int88erplay of Bayesian and Frequentist Analysis,” Statistical Science, 19(1), 58–80. DOI: 10.1214/088342304000000116.
   Web of Science ®Google Scholar
• Berger, J. O. (1990), “Robust Bayesian Analysis: Sensitivity to the Prior,” Journal of Statistical Planning and Inference, 25(3), 303–328. DOI: 10.1016/0378-3758(90)90079-A.
   Web of Science ®Google Scholar
• Christensen, R. (2005), “Testing Fisher, Neyman, Pearson, and Bayes,” The American Statistician, 59 (2), 121–126. DOI: 10.1198/000313005X20871.
   Web of Science ®Google Scholar
• Chuang-Stein, C., and Kirby, S. (2014), “The Shrinking or Disappearing Observed Treatment Effect,” Pharmaceutical Statistics, 13 (5), 277–280. DOI: 10.1002/pst.1633.
   PubMed Web of Science ®Google Scholar
• Dodd, L. E., Proschan, M. A., Neuhaus, J., Koopmeiners, J. S., Neaton, J., Beigel, J. D., Barrett, K., Lane, H. C., Davey, R. T., Jr. (2016), “Design of a Randomized Controlled Trial for Ebola Virus Disease Medical Countermeasures: PREVAIL II, the Ebola MCM Study,” The Journal of Infectious Diseases, 213, 1906–1913. DOI: 10.1093/infdis/jiw061.
   PubMed Web of Science ®Google Scholar
• Drug Amendments Act of 1962, Public Law 87–781, 76 STAT 780, available at http://prescriptiondrugs.procon.org/sourcefiles/1962Amendments.pdf
   Google Scholar
• Fisher, R. A. (1925), Statistical Methods for Research Workers, Edinburgh, Scotland: Oliver & Boyd, p. 45.
   Google Scholar
• Fisher, R. A. (1926), “The Arrangement of Field Experiments,” Journal of the Ministry of Agriculture of Great Britain, 33, 503–513.
   Google Scholar
• Gamalo, M. A., Tiwari, R. C., and LaVange, L. M. (2014), “Bayesian Approach to the Design and Analysis of Non-inferiority Trials for Anti-infective Products,” Pharmaceutical Statistics, 13(1), 25–40. DOI: 10.1002/pst.1588.
   PubMed Web of Science ®Google Scholar
• Goodman, S. N. (1999), “Toward Evidence-Based Medical Statistics. 1: The P Value Fallacy,” Annals of Internal Medicine, 130, 995–1004. DOI: 10.7326/0003-4819-130-12-199906150-00008.
   PubMed Web of Science ®Google Scholar
• Goodman, S. N., and Sladky, J. T., (2005), “A Bayesian Approach to Randomized Controlled Trials in Children Utilizing Information From Adults: The Case in Guillian-Barré Syndrome,” Clinical Trials, 2, 305–310. DOI: 10.1191/1740774505cn102oa.
   PubMed Web of Science ®Google Scholar
• Greco, T., Landoni, G., Biondi-Zoccai, G., D’Ascenzo, F., and Zangrillo, A. (2016), “A Bayesian Network Meta-analysis for Binary Outcome: How To Do It,” Statistical Methods in Medical Research, 25(5), 1757–1773. DOI: 10.1177/0962280213500185.
   PubMed Web of Science ®Google Scholar
• Greenhouse, J. B., and Seltman, H. (2005), “Using Prior Distributions to Synthesize Historical Evidence: Comments on the Goodman-Sladky Case Study of IVIg in Guillian-Barré Syndrome,” Clinical Trials 2, 311–318. DOI: 10.1191/1740774505cn095oa.
   PubMed Web of Science ®Google Scholar
• Hay, M., Thomas, D. W., Craighead, J. L., Economides. C., and Rosenthal. J. (2014). “Clinical Development Success Rates for Investigational Drugs,” Nature Biotechnology, 32(1), 40–51. DOI: 10.1038/nbt.2786.
   PubMed Web of Science ®Google Scholar
• Ibrahim, J. G., and Chen, M. H. (2000), “Power Prior Distributions for Regression Models,” Statistical Science, 15(1), 46–60. DOI: 10.1214/ss/1009212673.
   Web of Science ®Google Scholar
• Inoue, L.Y.T., Berry, D.A., and Parmigiani, G. (2005), “Relationship Between Bayesian and Frequentist Sample Size Determination. The American Statistician, 59 (1), 79–87. DOI: 10.1198/000313005X21069.
   Web of Science ®Google Scholar
• Lee, J. J., and Chu, C. T. (2012), “Bayesian Clinical Trials in Action,” Statistics in Medicine, 31(25), 2955–2972. DOI: 10.1002/sim.5404.
   PubMed Web of Science ®Google Scholar
• Morita, S., Thall, P.F., Mueller, P. (2008), “Determining the Effective Sample Size of a Parametric Prior.” Biometrics, 64, 595–602. DOI: 10.1111/j.1541-0420.2007.00888.x.
   PubMed Web of Science ®Google Scholar
• Morris, D. E., Oakley, J. E. and Crowe, J. A. (2014), “A Web-based Tool for Eliciting Probability Distributions From Experts,” Environmental Modelling & Software, 52, 1–4. DOI: 10.1016/j.envsoft.2013.10.010.
   Web of Science ®Google Scholar
• Müller, P., Xu, Y., and Thall, P. F. (2017), “Clinical Trial Design as a Decision Problem,” Applied Stochastic Models in Business and Industry, 33 (3), 296–301. DOI: 10.1002/asmb.2222.
   PubMed Web of Science ®Google Scholar
• O’Hagan, A., Buck, C., Daneshkhah, A., Eiser, J., Garthwaite, P., Jenkinson, D., Oakley, J., and Rakow, T. (2006), Uncertain Judgements: Eliciting Experts’ Probabilities. West Sussex, England: Wiley.
   Google Scholar
• Proschan, M. A., Dodd, L. E., and Price, D. (2016), “Statistical Considerations for a Trial of Ebola Virus Disease Therapeutics,” Clinical Trials, 13(1), 39–48. DOI: 10.1177/1740774515620145.
   PubMed Web of Science ®Google Scholar
• Sheiner, L. B. (1997), “Learning Versus Confirming in Clinical Drug Development,” Clinical Pharmacology and Therapeutics, 61, 275–291. DOI: 10.1016/S0009-9236(97)90160-0.
   PubMed Web of Science ®Google Scholar
• Spiegelhalter, D. J., Abrams, K. R., Myles, J. P. (2004), Bayesian Approaches to Clinical Trials and Health-Care Evaluations, West Sussex, England:Wiley.
   Google Scholar
• US Food and Drug Administration (2010), Guidance for the Use of Bayesian Statistics in Medical Device Clinical Trials, available at http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/ucm071072.htm
   Google Scholar
• US Food and Drug Administration (2016), Non-Inferiority Clinical Trials to Establish Effectiveness, available at http://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/default.htm
   Google Scholar
• US Food and Drug Administration (2018a), Adaptive Designs for Clinical Trials of Drugs and Biologics, available at https://www.fda.gov/downloads/drugs/guidances/ucm201790.pdf
   Google Scholar
• US Food and Drug Administration (2018b), Labeling for Inter Fix Threaded Fusion Device, available at https://www.accessdata.fda.gov/cdrh_docs/pdf/P970015C.pdf
   Google Scholar
• Ventz, S., and Trippa, L. (2015), “Bayesian Designs and the Control of Frequentist Characteristics: A Practical Solution,” Biometrics, 71 (1), 218–226. DOI: 10.1111/biom.12226.
   PubMed Web of Science ®Google Scholar