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Published byKatelyn Hopkins Modified over 11 years ago
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The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006
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Post-Market Trials Phase IV Label extension or modification Surveillance Investigator INDs Seeding Studies Biostatistician input much needed
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Roles Role should not be described as a list of tasks Role of the biostatistician in post-market industry trials is to be an advocate for GOOD SCIENCE.
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Wisdom Good Science is Good Business but Good Business is not necessarily good science Credible and timely results is good business in the long run
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Good ScienceDesign Stage Objectives Primary and secondary endpoints Eligibility Power and precision Doses, regimens Control Group Non-inferiority trials
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Good Science--Results Results available to patients and physicians Publication regardless of results Clear definition of original objectives of the trial Appropriate measures of precision, exposure Post-hoc power
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Advocate Independent Review throughout the trial
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Post Market Trials Then and Now
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Large Trials GUSTOt-PA vs streptokinase ATLASadjuvant tamoxifen COMMITacute MI asparin vs clopidogrel CPPTlipids, cholestiramine CONCORDEHIV, AZT WHI
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Surprising Results BHATpropranalol CASTencainide, flecainide
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Cooperative Meta Analyses ATTantithrombolytics EBCTCGearly breast cancer
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OncologyPractice Changing Trials Aromatase inhibatorsbreast cancer bevacizumab-VEGF, colorectal trastuzimabbreast cancer taxaneslung, ovarian platinumlung ovarian
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However…. Most of the trials just referenced were not conducted by industry
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Industry Sponsorship Pre-Market---Science / Regulatory driven Post-MarketMarketing driven
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Marketing Influence No trials undertaken whose results could threaten market share Results suppressed if they threaten market share
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Industry Sponsorship Phase IVUnder control of marketing Anti-depressants19/21 trials head-to-head sponsors product superior. – Low dose for competitor – Different schedules – Simple conditions – Not double blind
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The Non-Inferiority Complex Sloppy trials Result is under control of sponsor Delta Active control Sub-potent dose Terminate before effects Imprecise measurement
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Industry Sponsorship Publication bias Results not matched with original objectives Cox-2 inhibitor trials / bureaucracy
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Industry Sponsorship Advertising agency purchased CRO Seeding studies Design problems Organizational problems
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Good News William Olson, Ortho-McNeil Patent 6,339,105 A regimen for the administration of tramadol for the treatment of analgesia Slower titration rate Reduction in side effects
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Opportunities Bayesian design and analysis Testing groundsadaptive designs Meta analysis – Methodology – Fixed vs Random Effects – Mixed models
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A. MugglinMedical Devices Fine illustration of the role of statisticians Interesting SCD-HeFT cost-effectiveness study How do results of this information get disseminated to stakeholderspatients and their caregivers? Should not be used as sole justification for higher prices for the product.
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Mugglin--Future Globalization Aging of populations Cost-effectiveness IOM recommendation Genetics
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Revisit approved but unpopular drugs due to knowledge of what DNA is associated with response, low toxicity. bucindolol vs other beta blockers for heart failure tamoxifen vs aromatase inhibitors in breast cancer
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Gould--Surveillance fialuridine (FIAU), 1993 Good list of limitations (Considerations and Issues) Accumulating information of RR and the lower 5% point---how long to watch a signal? Retrospective pharmacovigilence
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Gould--Bayes Definitely a role for Bayesian methods here. The sooner the better. Empirical Bayes a good start Sponsor safety database OncologyMedDRA vs CTC 3.0
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Gould--Contribution Shows the contribution a statistician can make to a difficult problem by thinking through the problem Hope for a common ground between plaintiffs and industry To deny the implications of this type of analysis is to deny our ability to reason
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Marinac-Dabic FDA/CDRH Sources of data Areas requiring attention Motivate good science Post-market surveillance for the elderly Passive reporting system for high quality post-market surveillance data
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Thank You
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