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Unsafety: Making no mockery of honest ad-hockery Janet Wittes Statistics Collaborative ASA/FDA 2005.

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Presentation on theme: "Unsafety: Making no mockery of honest ad-hockery Janet Wittes Statistics Collaborative ASA/FDA 2005."— Presentation transcript:

1 Unsafety: Making no mockery of honest ad-hockery Janet Wittes Statistics Collaborative ASA/FDA 2005

2 Topic du jour

3 Sleight of tongue Game: Remove safety and add virtue in two easy steps D S M C __ _ _ _

4 Sleight of tongue Game: Remove safety and add virtue in two easy steps D S M C D M C _ _

5 Sleight of tongue Game: Remove safety and add virtue in two easy steps D S M C D M C I D M C

6 Efficacy Stop for overwhelming efficacy =0.05; power = 90%; four looks Probability of stopping early>70% Early stop: estimate pulls toward null

7 Our current approaches Prespecify Classify precisely Give lots of data Rely on mechanism

8 Divide and (un)conquer (e.g. Neuropathy) EventTC Neuropathic pain10 Neuropathy10 Neuropathy NOS52 Neuropathy peripheral20 … … …

9 e.g. Neuropathy EventTC Anosmia ….. Autonomic neuropathy10 … Cranial neuropathy21 … …

10 e.g. Neuropathy EventTC … Parathesia32 Parathesia NOS40 Parathesia other01 … Peripheral motor neuropathy60 Peripheral sensory neuropathy32

11 Other examples Heart failure Separate near synonyms Allocate to heart and lung

12 Other examples Heart failure Separate near synonyms Allocate to heart and lung Bleeding: distribute over body systems

13 Consider mechanism If you dont get the drug, you cant react to it Eschew ITT: safety population Modified Daleys Rule: censor early and often Dont collect extraneous information Appeal to statistical conservatism

14 Populations ITT mITT Safety: one dose of study med ATP Etc.

15 e.g., Vioxx- short follow-up

16 Through 36 months

17 With denominators Bresalier et al., NEJM, Feb 2005

18 The denominators Mo Rx Po

19 No data dredging We test hypotheses Too many type 1 errors if we dredge

20 What we typically present Current behavior Same tables for interim & final analyses Long complete listings What we should do Interim data are different from final Presenting too much dulls the mind

21 Sentinel events Single event (e.g., death in a vaccine trial) Several events (e.g., 3 retinal thromboses) Sentinel event rate (e.g., WHI) Lachenbruch and Wittes, SIM, to appear

22 How to handle 1.Identify sentinel event 2.Establish statl method for future events Need reasonable power Type I error rate > 1-sided 0.025

23 Methods Individual Number of non-events until the kth event Negative binomial SPRT Time to the next (or kth) event ( - distn) Rate: event rate in future patients Normal Poisson

24 Pitfalls Time is subtle Power is low Censoring is tricky

25 Pull-up Safety hypothesis: E.g., Cox-2 leads to 2 fold increase in MI etc. Design: stop early if you reject Estimated relative risk must be pulled toward 2 Insight from Joe Heyse

26 The option Respect PI: Adjudicate adverse events Precision: Reclassify, reorganize Mechanism: Be an empiricist Dredging:Use sentinel events


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