ISSUES THAT PLAGUE NON-INFERIORITY TRIALS PAST AND FUTURE - PowerPoint PPT Presentation

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ISSUES THAT PLAGUE NON-INFERIORITY TRIALS PAST AND FUTURE

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REVIEW ISSUES: PAST, PRESENT AND FUTURE IN NON-INFERIORITY (NI) STUDIES ... Hasselblad and Kong (2001) present this as their major example for using meta ... – PowerPoint PPT presentation

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Title: ISSUES THAT PLAGUE NON-INFERIORITY TRIALS PAST AND FUTURE


1
ISSUES THAT PLAGUE NON-INFERIORITY TRIALSPAST
AND FUTURE
  • RALPH B. DAGOSTINO, SR.
  • BOSTON UNIVERSITY
  • HARVARD CLINICAL RESEARCH INSTITUTE

2
OBJECTIVES
  1. REVIEW ISSUES PAST, PRESENT AND FUTURE IN
    NON-INFERIORITY (NI) STUDIES
  2. PRESENT/ DISCUSS EXAMPLES
  3. MAKE SOME COMMENTS FOR IMPROVEMENTS
  4. PRESENT A PERSONAL VIEW

3
OUTLINE
  1. Early Objectives and Issues
  2. Approaches to Non-inferiority Trials
  3. Examples (Here are some Problems)
  4. Non-Inferiority AND/OR Superiority
  5. All is Non-Inferiority
  6. Intent-to-Treat vs. Per Protocol
  7. New Major Issues

4
EARLY OBJECTIVES AND ISSUES EQUIVALENCY
  • American Dental Association (ADA 1980s)
  • CREST equivalent to COLGATE?
  • Ho A-Bgt 10 or A-Blt 10
  • What does the 10 mean?
  • DFMS or DFMT for 2 years, 3 years?
  • Study done on differences and ratio used as
    descriptive measure of effect
  • 5.0 vs 5.4 becomes (5.4-5.0)/5.0 .4/5. 8

5
EARLY OBJECTIVES
  • M 10 CAME FROM NOWHERE, BUT WE KNEW WHAT IT
    WAS, That is, 10
  • TREATMENT DIFFERENCES CONCERNED DIFFERENCES
    (RATIOS) BETWEEN ACTIVE TREATMENTS
  • WE WERE LOST BUT WE BELIEVED WE HAD A SENSE
    ABOUT IT

6
APPROACHES TO NI TESTS
  • MUST DO BETTER THAN PLACEBO
  • But you cannot use a Placebo (P)
  • Putative Placebo Approach
  • Test Treatment (T) vs Positive Control (C)
    directly with given Margin M (Assay Sensitivity
    approach)

7
APPROACH 1 (Putative Placebo) Stellar Example
from the Past
  • CAPRIE Study. Hasselblad and Kong (2001) present
    this as their major example for using
    meta-analyses for dealing with estimating assay
    sensitivity (T vs. P)
  • Want T vs. C, C vs. P, T vs. P

8
21
9
CAPRIE STUDY (cont)
  • Can we obtain effect of Clopidogrel vs. Aspirin
  • Yes, if we can locate Asprin vs. Placebo
  • Do we believe what we get?

10
For Aspirin vs. PlaceboAntiplatelet Trialists
Collaboration Meta-Analysis
  • Meta-analysis of all published and unpublished
    unconfounded randomized trials available March
    1990
  • Trials identified by literature search, trial
    registry and inquiry of investigators and
    pharmaceutical manufacturers
  • Clear definitions of endpoints
  • Well defined statistical methodology

11
APPROACH
  • T vs. C (from Caprie trial)
  • C vs. P (from Meta-analysis)
  • Obtain T vs. P (from multiplication)
  • (T/C) (C/P) (T/P)

12
Clopidogrel Vs. Synthetic Placebo Control
Odds Ratios and 95 Confidence Intervals
Overall Patient Population
CAPRIE Clopidogrel Vs. Aspirin
Meta-Analysis Aspirin Vs. Placebo
Estimated Clopidogrel Vs. Placebo
  • Endpoint
  • All Strokes, MIs,
  • or Vascular Deaths p lt 0.000001
  • All Strokes, MIs
  • or Death from p lt 0.000001
  • Any Cause
  • Vascular p lt 0.0016
  • Deaths
  • All Cause p lt 0.0045
  • Deaths
  • 0.4 0.6
    0.8 1.0 1.2
    1.4 1.6
  • First Drug Better Second
    Drug Better

13
  • Meta-analysis studies contain very old studies
    (only up to 1990), many prior to all of the
    elaborate medical interventions (procedures) now
    routinely provided
  • Many of the studies did not have MI, IS or
    vascular death as their outcomes (the
    meta-analysis went back to original investigators
    who in turn, had to generate data). Ever try to
    get data on something you did not collect?
  • None of the studies used for Clopidogrel with
    aspirin comparison had PAD as an entry criteria
    (PAD represented 1/3 of Clopidogrel Study)

14
EFFECT SIZE Relative Risk Reduction by
Qualifying Condition (ASA vs Clopidogrel)
  • IS n 6431
  • MI n 6302
  • PAD n 6452
  • Total n 19185
  • 30 20 10 0 10 20
  • Clopidogrel Better Aspirin Better

15
Problems With Historical Controls
  • Biases
  • Time Biases
  • Change in recognition or diagnosis of disease
  • Changing disease process
  • Change in usual therapy
  • (Myocardial Infarctions MI, Dx, Tx)
  • Selection Biases
  • Patients/Health care systems
  • Are we really seeing the same patients in
    historical studies as those in active control
    trial?

16
Problems With Meta-AnalysesSo What Is Sponsor to
DO?
  • If we plan to use placebo controlled trials, what
    should we require of the historical placebo
    trials?
  • Same Disease/Conditions?
  • Same Population
  • Same Dose and Administration Levels of Active
    Control C?
  • Same Outcomes?
  • Combine All or Some (good) Placebo Controlled
    Studies

17
Still Other Problems With Meta-Analyses
  • What if previous studies had multiple arms? How
    to put correctly into meta-analysis?
  • What if none of the individual studies achieved
    significance?
  • What are we to believe from meta-analyses?
  • Do we believe the p-levels of the meta-analysis?
    (I do not think we should.)

18
APPROACH 2NON-INFERIORITY STUDIESACTIVE CONTROL
STUDIES
  • NON-INFERIORITY TEST
  • H0 T-C gt M vs. H1 T-C lt M
  • (Say data are event rates)
  • T is new treatment
  • C is positive control
  • M IS NON-INFERIORITY MARGIN

19
NON-INFERIORITY STUDIES
  • APPROACH 2
  • SELECT A VALUE OF M THAT MAKES SENSE
  • WANT ASSURANCE THAT ASSAY SENSITIVITY IS PRESENT
    (Placebo is working)
  • WANT CONSISTENCY WITH PAST

20
NON-INFERIORITY STUDIES Statistical Approach
  • Need Active Control C vs. Placebo P data from
    Historical data (C vs. P)
  • Need to test effectiveness of T vs. C
  • Need estimate of fraction of C-P preserved by T
    (e.g., (T-P)/(C-P) M) M0.5 (C-P)
  • METHODS EXIST THAT ALLOW TEST TO BUILD IN NEW AND
    HISTORICAL DATA
  • (STATISTICS IN MEDICINE, 2002)

21
WHAT IS NEEDED FOR 2
  • CONFIDENCE INTERVAL IS OFTEN USED. WANT M1.11
    (SAY) OUTSIDE UPPER LIMIT OF CONFIDENCE INTERVAL
    (M is relative risk)
  • FDA ODAC 8/04 (non-small cell lung cancer)

1.0
1.11 M
22
SOME REALITIES
  • Sounds nice
  • What happens

23
Anti-infective Product No placebo data
  • Historical data is not Placebo, but C
  • VRE (vancomycin resistant enterococcal)
  • High dose Low dose
  • MITT 60.0 (N65) vs. 46.2 (N52)
  • Bacteremic
  • 55.6 (N18) vs. 25.0
    (N16)
  • What is M? One trial OK? Any superiority?

24
ANOTHER EXAMPLERespiratory Distress
  • Respiratory Distress Syndrome in Premature
    Infants
  • Treatments
  • New Drug
  • Comparator
  • Outcome
  • Survival at 28 Day

25
Respiratory Distress (cont)
  • Survanta versus Sham (two studies one positive,
    other negative) All Cause mortality
  • Study 1 8 vs. 23 Study2 17 vs. 14
  • What is M? .23-.08? .180-.125?

26
CONSISTENCY Example Control rate different from
historical
  • Historical Data says C0.5 and P0.6
  • Want Tlt0.55
  • P-C0.10, M0.5(0.10) 0.05
  • (T-C)/C 0.05/0.50 10
  • Data is C0.30 and T0.33, T-C0.03
  • (T-C)/C 0.03/0.30 10
  • IS STUDY A SUCCESS? USE RATIOS?

27
ANSWER TO CONSISTENCY
  • There was consistency
  • Differences related to birth weight

28
Non-Inferiority and Inferiority at the same time
  • Sponsor falls apart

0
M
29
Non-Inferiority and Superiority
  • Sponsor jumps for joy (Sequential test)

0
M
30
Switching trial design (Cardiac Stent Trials)
  • (1) New drug coated stents, we can do
    non-inferiority study with margin set (15)
  • (2) We can do superiority study with non-coated
    stent as control
  • With first option we have to worry about
    evaluating Ms, Effect size and CREEP
  • With superiority trial clean results

31
Respiratory Distress
  • Compare new surfaxin to another not so great
    one, but still used in practice

32
Switching from Superiority to non-Inferiority
  • HOW CAN WE SWITCH FROM A SUPERIORITY TEST TO
    NON-INFERIORITY ?
  • This is a question thrown at me constantly

33
Assessing Efficacy Non-Inferiority and Safety
Superiority
  • Carotid artery Magnetic Resonance Imaging agent
  • Imaging Agents
  • Agent N (New) Agent C (Comparator)
  • Non-inferiority Outcome
  • Endpoint agents ability to classify correctly
    patients with gt 25 stenosis (sensitivity)
  • Sensitivity of Comparator is .80 or 80
  • Non-inferiority margin M set to 0.10

34
Assessing Efficacy Non-Inferiority and Safety
Superiority (Contd)
  • There is a specific adverse event that is
    hypothesized to occur less often with New than
    with Comparator
  • Do we want to make the specific adverse event
    rate an additional primary endpoint? WHY NOT?

35
Non US STUDIES
  • Forced off shore (ethical and other reasons)

36
The BLOB EFFECT
  • Everything is suddenly Non-Inferiority

37
ALLHAT STUDY
  • COMPARISON OF ANTI-HYPERTENSIVE MEDICATIONS
    (MULTIPLE ARMS)
  • NOT A NON-INFERIORITY STUDY

38
Safety Studies
  • Safety studies have become carefully designed and
    executed studies
  • Should they be non-inferiority studies?

39
SAFETY STUDIES (PHASE 4)
  • HISTORICAL APPROACH NEW RATE gt OLD
  • H01 T-C lt 0 vs. H11 T-C gt 0
  • H02 RRT/C lt 1 vs. H12 RRT/C gt 1
  • STUDY POWERED TO REJECT T/C gt1.5 (SAY)
  • SHIFT IS TO MAKING THESE NON-INFERIORITY STUDIES
  • H0 T-C gt M vs. H1 T-C lt M
  • H0 RRT/C gt M vs. H1 RRT/C lt M

40
Safety Studies
  • OLD
  • NEW

1
M
41
SAFETY STUDY TO NON-INFERIORITY STUDY(QT
LONGATION)
  • Safety issue drug may cause QT problem
  • Ho A/B 1.0 vs H1 R A/B gt 1.0
  • Study powered for R gt 1.0
  • When interest in risk fades can we suddenly say
    this should be a non-inferiority study?
  • HoR gt 1.5 vs. H1R lt 1.5 was not original
    objective
  • If we do not reject Ho is that enough?

42
Form of Interest and Sample Size
  • Ho p1-p2 gt M
  • Ho p1-p2gtRp2
  • Ho p1/p2 gt R
  • Best Choice does depend on p2 (control rates)

43
Intent-to-Treat vs. Per-Protocol
  • In superiority trials, the primary analysis is
    often on intent-to-treat (ITT) population
  • Per Protocol (PP) bigger differences of
    treatments
  • In non-inferiority should we use PP?

44
Intent-to-Treat vs. Per-Protocol (Contd)
  • PP as primary not always accepted
  • the ITT analysis is as important as the PP
    analysis
  • need to reconcile differences between ITT and PP
    analysis
  • Perform sensitivity analyses. Results should
    be similar in both populations (ROBUSTNESS).
  • The Committee on Proprietary Medicinal Products
    draft Points to Consider similar conclusions
    from both the ITT and PP are required in a
    noninferiority trial.

45
  • We ask sponsor to do both (ITT and PP) and expect
    to achiev the sam significant result on both.
  • What is the true alpha associated with this?

46
NEW MAJOR ISSUES
  • Missing Data
  • Noncompliance
  • Interim Analysis
  • OUR USUAL LOGIC INCREASES CHANCE OF ACCEPTANCE OF
    non-inferiority

47
MORE NEW ISSUES
  • Multiple endpoints
  • Multiple groups
  • Repeated Measures

48
WHERE ARE WE?
  • NON-INFERIORITY TRIALS HAVE MADE A BIG IMPACT
  • They have brought many new problems and
    challenges with them
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