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CME Disclosure Statement

CME Disclosure Statement.

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CME Disclosure Statement

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  1. CME Disclosure Statement The North Shore LIJ Health System adheres to the ACCME's new Standards for Commercial Support. Any individuals in a position to control the content of a CME activity, including faculty, planners and managers, are required to disclose all financial relationships with commercial interests. All identified potential conflicts of interest are thoroughly vetted by the North Shore-LIJ for fair balance and scientific objectivity and to ensure appropriateness of patient care recommendations. Course Director, Kevin Tracey, has disclosed a commercial interest in Setpoint, Inc. as the cofounder, for stock and consulting support. He has resolved his conflicts by identifying a faculty member to conduct content review of this program who has no conflicts. The speaker, Martin L. Lesser, PhD, has no conflicts. 2

  2. Phase I Designs “3+3” dose escalation design for determining maximum tolerated dose (MTD) Fixed multiple dose design (e.g., randomize 5 subjects to each of 5 doses) Goal: design should protect subjects from harm, especially in a trial for which safe dosing, pharmacokinetics, and potential toxicities are unknown or poorly understood

  3. X1=# of DLTs in first cohort of 3 X2=# of DLTs in first cohort of 3 DLT=dose limiting toxicity Source: Jovanovic, et al. 2004

  4. Phase II Designs Applied to a specific disease entity Fixed dose is used Simple primary outcome: response, measurement of some parameter Single arm, open label (traditional) Single arm, blinded evaluator (uncommon) Simon 2-stage design Randomized Phase II trial (for selection of best therapy)

  5. Simon 2-Stage Optimal Design H0: p ≤ p0 vs. HA: p ≥ p1 Where response rate ≤ p0 is uninteresting and response rate ≥ p1 is the desired target Simon’s “Optimal Design”: Observe n1 subjects in stage 1. If response rate r1≤ a1/n1, then stop the trial and reject the drug. If r1> a1/n1, then study an additional n2 subjects in stage 2, for a total of n=n1+n2. If the “total” response rate r ≤ a/n, then reject the drug. If r > a/n, then consider the drug for further testing and Phase III trials. Simon: Controlled Clin Trials, 10:1-10, 1989.

  6. Simon 2-Stage Optimal Design (cont’d) For given α, β, p0, and p1, this design minimizes EN(p0), the expected number of subjects studied under H0 . Example: Let α=0.05 β=0.20 p0= 0.30 p1= 0.45 Stage 1: Enter 27 subjects; stop trial and reject drug if r1≤ 9/27. If r1 > 9/27, then go on to Stage 2. Stage 2: Enter 54 additional subjects (total=81). If r ≤ 30/81, then reject the drug. If r > 30/81, then trial is favorable toward drug. Note: E(N(p0)) = 41.7. Prob(early termination)=0.73

  7. Simon 2-Stage Minimax Design Similar to the 2-stage optimal design Minimizes the maximum total sample size (n) among all optimal designs Minimax design is attractive when subject accrual is low Previous example worked with minimax: r1≤ 16/46, r ≤ 25/65, EN(p0)=49.6, PET(p0)=0.81 (Optimal design had n=81.)

  8. Phase III Trials

  9. Design Considerations(continued) Treatment Plan Blinding Use of Placebo Control Criteria for evaluation of treatment effect (comparability of patient follow-up)

  10. Design Considerations(continued) Blinding Placebo control Stratification The process of randomization Handling dropouts and non-compliance Statistical methods for data analysis Sample size and power Interim analysis and early stopping

  11. Blinding Any attempt to make study participants unaware of which treatment is offered Is indicated when the occurrence and reporting of outcomes can be easily influenced by knowledge of treatment (subjective responses, behavior change) May be either single blind or double blind Blinding is not always feasible Blinding may be unsuccessful (ability to break the blind)

  12. Placebo Control Appropriate when no effective standard treatment exists for the control group Makes subject’s attitudes to the trial as similar as possible in the treatment and control groups Major uses: − Controls for psychological factors − Maintains double blind design − Controls for spontaneous disease variability • Ethical issues: - May be unethical to withhold treatment in order to administer placebo

  13. Example: RCT in Head and Neck CancerAssuming Full (100%) Compliance in Group A Weight Gain (lbs.) n=50 NG Feeding Tube µ=8.0, σ=3 RANDOMIZE A 7.57 ± 2.84 B n=50 Best Oral Nutrition µ=5.0, σ=3 4.61 ± 3.01 A vs. B P<0.0001

  14. Example: RCT in Head and Neck CancerAssuming 50% Compliance in Group A Weight Gain (lbs.) n=25 Pull out NG tube and default to best oral nutrition µ=4.5, σ=3 5.00 ± 2.42 A1 A1 n=50 NG Feeding Tube RANDOMIZE 6.39 ± 2.74 A A1 A2 A2 n=25 Compliant with NG tube µ=8.0, σ=3 7.78 ± 2.34 n=50 Best Oral Nutrition µ=5.0, σ=3 B 5.44 ± 2.81 B 5.66 ± 2.98 A vs. B (ITT) p=0.2098 A2 vs. B p=0.0028 A2 vs. A1+B p=0.0009 A1 vs. A2 vs. B p=0.0003

  15. Example:The BHAT Trial(Beta-blocker Heart Attack Trial) Randomized, double-blind, placebo-controlled trial to test the effect of propanolol (beta-blocker) on total mortality n = 3837 patients randomized to propanolol or placebo Trial was stopped 1 year early (on the 6th interim analysis) using the O-F group sequential approach when logrank X2 =2.82 > 2.23

  16. O’Brien-Fleming Boundaries Applied to the BHAT Trial

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