issues that plague non inferiority trials past and future l.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
ISSUES THAT PLAGUE NON-INFERIORITY TRIALS PAST AND FUTURE PowerPoint Presentation
Download Presentation
ISSUES THAT PLAGUE NON-INFERIORITY TRIALS PAST AND FUTURE

Loading in 2 Seconds...

play fullscreen
1 / 48

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


  • 1599 Views
  • Uploaded on

ISSUES THAT PLAGUE NON-INFERIORITY TRIALS PAST AND FUTURE RALPH B. D’AGOSTINO, SR. BOSTON UNIVERSITY HARVARD CLINICAL RESEARCH INSTITUTE OBJECTIVES REVIEW ISSUES: PAST, PRESENT AND FUTURE IN NON-INFERIORITY (NI) STUDIES PRESENT/ DISCUSS EXAMPLES MAKE SOME COMMENTS FOR IMPROVEMENTS

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'ISSUES THAT PLAGUE NON-INFERIORITY TRIALS PAST AND FUTURE' - liam


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
issues that plague non inferiority trials past and future
ISSUES THAT PLAGUE NON-INFERIORITY TRIALSPAST AND FUTURE

RALPH B. D’AGOSTINO, SR.

BOSTON UNIVERSITY

HARVARD CLINICAL RESEARCH INSTITUTE

objectives
OBJECTIVES
  • REVIEW ISSUES: PAST, PRESENT AND FUTURE IN NON-INFERIORITY (NI) STUDIES
  • PRESENT/ DISCUSS EXAMPLES
  • MAKE SOME COMMENTS FOR IMPROVEMENTS
  • PRESENT A PERSONAL VIEW
outline
OUTLINE
  • Early Objectives and Issues
  • Approaches to Non-inferiority Trials
  • Examples (Here are some Problems)
  • Non-Inferiority AND/OR Superiority
  • All is Non-Inferiority
  • Intent-to-Treat vs. Per Protocol
  • New Major Issues
early objectives and issues equivalency
EARLY OBJECTIVES AND ISSUES: EQUIVALENCY
  • American Dental Association (ADA 1980s)
  • CREST equivalent to COLGATE?
  • Ho: A-B>= 10% or A-B<= 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%
early objectives
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
approaches to ni tests
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)
approach 1 putative placebo stellar example from the past
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
caprie study cont
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?
for aspirin vs placebo antiplatelet trialists collaboration meta analysis
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
approach
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)
slide12
Clopidogrel Vs. Synthetic Placebo Control Odds Ratios and 95% Confidence IntervalsOverall Patient Population

CAPRIE: Clopidogrel Vs. Aspirin

Meta-Analysis: Aspirin Vs. Placebo

Estimated: Clopidogrel Vs. Placebo

Endpoint

All Strokes, MIs,

or Vascular Deaths p < 0.000001

All Strokes, MIs

or Death from p < 0.000001

Any Cause

Vascular p < 0.0016

Deaths

All Cause p < 0.0045

Deaths

0.4 0.6 0.8 1.0 1.2 1.4 1.6

First Drug Better Second Drug Better

slide13
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)
effect size relative risk reduction by qualifying condition asa vs clopidogrel
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

problems with historical controls
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?
problems with meta analyses so what is sponsor to do
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
still other problems with meta analyses
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.)
approach 2 non inferiority studies active control studies
APPROACH 2NON-INFERIORITY STUDIESACTIVE CONTROL STUDIES

NON-INFERIORITY TEST

H0: T-C >= M vs. H1: T-C < M

(Say data are event rates)

T is new treatment

C is positive control

M IS NON-INFERIORITY MARGIN

non inferiority studies
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
non inferiority studies statistical approach
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) M=0.5 (C-P)

METHODS EXIST THAT ALLOW TEST TO BUILD IN NEW AND HISTORICAL DATA

(STATISTICS IN MEDICINE, 2002)

what is needed for 2
WHAT IS NEEDED FOR 2
  • CONFIDENCE INTERVAL IS OFTEN USED. WANT M=1.11 (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

some realities
SOME REALITIES
  • Sounds nice
  • What happens
anti infective product no placebo data
Anti-infective Product No placebo data
  • Historical data is not Placebo, but C
  • VRE (vancomycin resistant enterococcal)

High dose Low dose

  • MITT 60.0 % (N=65) vs. 46.2 % (N=52)
  • Bacteremic

55.6 (N=18) vs. 25.0 (N=16)

  • What is M? One trial OK? Any superiority?
another example respiratory distress
ANOTHER EXAMPLERespiratory Distress
  • Respiratory Distress Syndrome in Premature Infants
    • Treatments
      • New Drug
      • Comparator
    • Outcome
      • Survival at 28 Day
respiratory distress cont
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?
consistency example control rate different from historical
CONSISTENCY Example Control rate different from historical
  • Historical Data says C=0.5 and P=0.6
  • Want T<=0.55
  • P-C=0.10, M=0.5(0.10) = 0.05
  • (T-C)/C = 0.05/0.50 = 10%
  • Data is C=0.30 and T=0.33, T-C=0.03
  • (T-C)/C = 0.03/0.30 = 10%
  • IS STUDY A SUCCESS? USE RATIOS?
answer to consistency
ANSWER TO CONSISTENCY
  • There was consistency
  • Differences related to birth weight
non inferiority and superiority
Non-Inferiority and Superiority
  • Sponsor jumps for joy (Sequential test)

0

M

switching trial design cardiac stent trials
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
respiratory distress
Respiratory Distress
  • Compare new surfaxin to another “not so great” one, but still used in practice
switching from superiority to non inferiority
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
assessing efficacy non inferiority and safety superiority
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: agent’s ability to classify correctly patients with > 25% stenosis (sensitivity)
    • Sensitivity of Comparator is .80 or 80%
    • Non-inferiority margin M set to 0.10
assessing efficacy non inferiority and safety superiority cont d
Assessing Efficacy Non-Inferiority and Safety Superiority (Cont’d)
  • 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?
non us studies
Non US STUDIES
  • Forced off shore (ethical and other reasons)
the blob effect
The BLOB EFFECT
  • Everything is suddenly Non-Inferiority
allhat study
ALLHAT STUDY
  • COMPARISON OF ANTI-HYPERTENSIVE MEDICATIONS (MULTIPLE ARMS)
  • NOT A NON-INFERIORITY STUDY
safety studies
Safety Studies
  • Safety studies have become carefully designed and executed studies
  • Should they be non-inferiority studies?
safety studies phase 4
SAFETY STUDIES (PHASE 4)

HISTORICAL APPROACH: NEW RATE > OLD

H01: T-C <= 0 vs. H11: T-C > 0

H02: RR=T/C <= 1 vs. H12: RR=T/C > 1

STUDY POWERED TO REJECT T/C >1.5 (SAY)

SHIFT IS TO MAKING THESE NON-INFERIORITY STUDIES

  • H0: T-C >= M vs. H1: T-C < M

H0: RR=T/C >= M vs. H1: RR=T/C < M

safety study to non inferiority study qt longation
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 > 1.0
  • Study powered for R > 1.0
  • When interest in risk fades can we suddenly say this should be a non-inferiority study?
  • Ho:R >= 1.5 vs. H1:R < 1.5 was not original objective
  • If we do not reject Ho is that enough?
form of interest and sample size
Form of Interest and Sample Size
  • Ho: p1-p2 >= M
  • Ho: p1-p2>=Rp2
  • Ho: p1/p2 >= R
  • Best Choice does depend on p2 (control rates)
intent to treat vs per protocol
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?
intent to treat vs per protocol cont d
Intent-to-Treat vs. Per-Protocol (Cont’d)
  • 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”.
slide45
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?
new major issues
NEW MAJOR ISSUES
  • Missing Data
  • Noncompliance
  • Interim Analysis
  • OUR USUAL LOGIC INCREASES CHANCE OF ACCEPTANCE OF non-inferiority
more new issues
MORE NEW ISSUES
  • Multiple endpoints
  • Multiple groups
  • Repeated Measures
where are we
WHERE ARE WE?
  • NON-INFERIORITY TRIALS HAVE MADE A BIG IMPACT
  • They have brought many new problems and challenges with them