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Trial Objectives. Superiority, Non-inferiority, and Equivalence. Questions of Interest. Is the new treatment better than the control treatment that I am using now? (superiority trial)

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Trial objectives

Trial Objectives

Superiority, Non-inferiority, and Equivalence


Questions of interest

Questions of Interest

  • Is the new treatment better than the control treatment that I am using now? (superiority trial)

  • If it is not better, is the new treatment as good (not unacceptably non-inferior) as the control treatment that I am using now? (non-inferiority trial)

  • Can I use the new treatment and the control treatment interchangeably? (equivalence trial)

Non-inferiority and equivalence trials are usually

considered when there is an active control.


Definitions ich guidelines e9

Definitions (ICH Guidelines – E9)

  • Superiority trial – a trial with the primary objective of showing that the response to the investigational product is superior to a comparative agent (active or placebo control).

  • Equivalence trial – a trial with primary objective of showing that the response to two or more treatments differs by an amount which is clinically unimportant (active control).

  • Non-inferiority trial – a trial with the primary objective of showing that the response to the investigational product is not clinically inferior (or not unacceptably inferior) to a comparative agent (active or placebo control but usually active) – very common in the regulatory setting either for a new treatment or for a new label indication.


Fda guidance

FDA Guidance

  • “The objective of a non-inferiority trial is to show that any difference in the effectiveness of the two drugs is small enough to allow a conclusion that the new drug is not substantially less effective than the active control.”

  • “FDA considers the selection of a non-inferiority margin to be the single greatest challenge in designing, conducting, and interpreting non-inferiority trials…If a non-inferiority margin is incorrectly calculated and set to large, a drug that is not effective may appear to be effective; if the margin is too small, an effective drug may appear ineffective.”

GAO-1-798 Evidence from Clinical Trials


Reasons for active controls

Reasons for Active Controls

  • An active treatment (comparator) with established efficacy exists.

  • If superiority can be established, the standard of care is improved.

  • While a short-term study with a placebo control might be ethical, if the outcome is morbidity/mortality, a trial with use of a placebo is not ethical if an accepted standard of care treatment exists (recall papers by Temple and Ellenberg).


The number and type of active comparator studies vary by sponsor commercial versus non commercial

The Number and Type of Active Comparator Studies Vary by Sponsor (Commercial versus Non-Commercial)

  • Among published reports of trials between June 2008 and September 2009 in major medical journals, 97/212 (46%) used an active comparator.

  • 36/108 (33%) with commercial sponsors and 61/104 (59%) with non-commercial sponsors.

  • 18/36 (50%) of active controlled commercial trials were non-inferiority versus 5/61 (8%) of non-commercial trials.

JAMA 2010; 303:951-958


Examples non inferiority 1

Examples – Non-Inferiority - 1

  • Safety: Is a new vaccine for pertussis (whooping cough) that has an improved safety profile as effective in preventing whooping cough as the currently licensed vaccine?

  • Ease of use: Is a new oral anticoagulant non-inferior to warfarin for stroke and systemic embolism among patients with atrial fibrillation? (N Engl J Med 2011)


Examples non inferiority 2

Examples – Non-Inferiority - 2

  • Treatment duration: Is a short course of treatment for latent TB infection (3 months of INH plus rifapentine) as effective as 9 months of INH in preventing active TB? (N Engl J Med 2011)

  • Cost: Is an inexpensive alternative to ranibizumab called bevacizumab non-inferior for visual acuity among patients with age-related macular degeneration? (N Engl J Med 2011)


Trial objectives

Example - HIV Trial:Abacavir-Lamivudine-Zidovdine vsIndinavir-Lamivudine-ZidovudineJAMA 2001;285:1155-1163.

“The study was powered to assess treatment equivalence for the primary endpoint (i.e., a plasma HIV RNA level <= 400 copies/mL at week 48 for the intent- to-treat population). For the primary end point, treatments were considered equivalent if the 95% confidence interval was within the bound -12% to 12%.”


Motivation evaluating new treatments in for non inferiority and equivalence trials

Motivation Evaluating New Treatments in for Non-Inferiority and Equivalence Trials

New Treatment

  • Costs less

  • More convenient to use (e.g., short course of prophylaxis for TB, no blood tests as for warfarin)

  • Lower risk of side effects (e.g., pertussis vaccine)

    But is it as effective?


Trial objectives

Superiority and Non-Inferiority in One Trial(Usually concurrent placebo arm is absent, but this may be practical in some short-term studies)

Randomize

Drug A

Control

Drug B

Experimental

Placebo

Superiority

Non-inferiority


Effect of hypericum perforatum st john s wort in major depressive disorder

Effect of Hypericum perforatum (St. John’s Wort) in Major Depressive Disorder

Randomize

Sertraline

Active Control

St. John’s Wort

Experimental

Placebo

Control

Neither sertraline or St. John’s Wort was significantly different

from placebo in this 8 week study. The authors noted “without a placebo,

hypericum could easily have been considered as effective as sertraline…”

JAMA 2002; 287:1807-1814.


Trial objectives

In the absence of a concurrent placebo, have to provide assurance that the active control would have been superior to placebo, if it had been used, and the test treatment would have beat placebo had it been used (indirect inference).


Non inferiority or equivalence trials key features

Non-inferiority or Equivalence Trials:Key Features

  • Efficacy of reference or control treatment (anchor) must be clearly established (control is better than nothing).

  • Target population and outcome measures must be similar to the trial that established efficacy of control (constancy assumption).

  • Margin of non-inferiority/equivalence must be a priori stated, clinically relevant, and chosen to ensure new treatment is better than “imputed” nothing (non-inferiority margin).


Trial objectives

Assay Sensitivity and Constancy are Critical Assumptions in Interpreting Non-inferiority and Equivalence Trials

Assay Sensitivity (def.) – ability to demonstrate a difference between active and inactive treatments

  • Can you assume that the standard treatment (active control) is effective?

  • How do you tell the difference between a good trial that establishes two active treatments to be similarly effective from a bad trial that incorrectly claims similarity?

    • External evidence: historical data that the control treatment is effective

    • Internal evidence : a high quality trial

      Constancy (def.)

  • Historical data showing that the control treatment is effective (better than placebo), holds in the setting of the current non-inferiority trial

Hung and O’Neill, Encyclopedia of Clinical Trials


Trial objectives

Historical Evidence Concerning Efficacy of Active Control and Defining the Non-Inferiority or Equivalence Margin

  • One trial

  • Meta-analysis or overview of trials (need to be cognizant of “file-drawer” problem)

  • Point-estimate or lower bound of 95% CI

  • Retention of certain fraction of superiority of active control over placebo (e.g., 50%)

    • True probability of event for active control and placebo are 20% and 30%

    • Show probability of event with new treatment is smaller than 25% (a difference, or non-inferiority margin, between new treatment and active control of 5%)

Would like to convince people that if you had used placebo you would have won!


General problems in determining non inferiority margin

General Problems in Determining Non-Inferiority Margin

  • What is “unacceptably inferior” or an acceptable level of non-inferiority – often in the eyes of the beholder!

  • Multiple outcomes are at play – non-inferiority margins are typically defined for the primary endpoint but many outcomes may be considered.

  • Constancy assumption: same endpoint, duration of follow-up as trial(s) that established efficacy of active control.

  • The margin assumes we know “true” effect of active control and often there is substantial variability.

  • In some cases, there are multiple choices for active control.


Another problem

Another Problem

  • Suppose the control arm (e.g., standard of care) is shown to be inferior to another treatment – what is the relevance of showing your drug is not too much worse than a drug which is inferior to another?

  • See Fleming T and Emerson S, N Engl J Med, 2011.

    • Rivaroxaban found inferior to wafarin for atrial fibirallation (Patel M et al, N Engl J Med 2011)

    • Another recently licensed drug, dabigatran, was found to be superior to wafarin (Connolly S et al, N Engl J Med, 2009)


How do you prove two treatments are equal cannot prove h o 0

How do you prove two treatments are equal?

Cannot prove HO: Δ=0


Trial objectives

“It is never correct to claim that treatments have no effect or that there is no difference in the effects of treatments. It is impossible to prove … that two treatments have the same effect. There will always be uncertainty surrounding estimates of treatment effects, and a small difference can never be excluded… An analysis of 45 reports of trials purporting to test equivalence found that only a quarter set boundaries on their equivalence.”

Alderson P, Chalmers I. BMJ 2003:326:1691-8.

The non-inferiority/equivalence margin must

be specified in the protocol!


Relationship between significance tests and confidence intervals

Relationship Between SignificanceTests and Confidence Intervals

Superiority strongly

shown

p=0.002

p=0.05

Superiority shown

p=0.20

Superiority not shown

ControlBetter

0

New Agent Better

Treatment Difference


Trial objectives

Superiority Trial – ALLHAT:Lisinopril vs Chlorthalidone for CHD Incidence, CVD Composite Outcome, and ESRD*

CHD (95% CI:0.91-1.08)

CVD Composite (95% CI:

1.05-1.16)

ESRD (95% CI: 0.88-1.38)

Lisinopril better

Chlorthalidone better

1.00

HR (Lisinopril/Chlorthalidone)

In ALLHAT, 15,255 participants were randomized to chlorthalidone and 9,000+

participants were randomized to each of 3 other treatments.

JAMA 2002;288:2981-2997.


Interpretation of head to head equivalence trials convince and cappp

Interpretation of Head to Head (Equivalence) Trials:CONVINCE and CAPPP

CONVINCE equivalence bounds (0.86-1.16)

CONVINCE Trial result

CAPPP Trial result

Overview (9 trials)

1.00

Calcium Channel Blocker better

SOC better

HR (Verapamil/SOC) for CONVINCE

(Captopril/SOC) for CAPPP

CAPPP = Captopril Primary Prevention Project. Authors

concluded: “captopril and conventional treatment did not differ in efficacy.”

See JAMA 2003;289: 2073-2082 for Convince Trial


Example 2nn study

Example: 2NN Study

  • A study of first-line antiretroviral therapy in HIV

  • Main comparison between nevirapine twice daily and efavirenz (plus stavudine and lamivudine) in terms of ‘treatment failure’ (based on virology, disease progression, therapy change)

  • Primary objective was to establish the non-inferiority of nevirapine twice daily (δ=10%)

Lancet 2004, 363:1253-63


Results 2nn study

Results: 2NN Study

  • Confidence intervals for failure rates (EFV-NVP)

    • All data (-12.8%, 0.9%)

    • Those starting med. (-14.6%, -0.8%)

  • Neither interval is completely above δ value of -10%; one interval also excludes zero.


Conclusions 2nn study

Conclusions: 2NN Study

  • BUT, the authors concluded:

    ‘Antiviral therapy with nevirapine or efavirenz showed similar efficacy, so triple-drug regimens with either … are valid for first-line treatment’

Lancet 2004, 363:1253-63


Interpretation of non inferiority trials 6 examples a f hazard ratio test drug standard and 95 ci

Interpretation of Non-Inferiority Trials:6 Examples (A – F): Hazard ratio (Test Drug/Standard) and 95% CI

Estimated benefit of

standard drug over placebo

Zone of

noninferiority

Test drugbetter

Standarddrug better

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

A

Superiority

B

C

Noninferiority(i.e., Equivalence)

Inferiority

D

E

Underpowered trial

F

Anteman EM, Circulation 2001;103:e101-e104.


Interpretation of non inferiority trials 6 examples a f hazard ratio and 95 ci

Interpretation of Non-Inferiority Trials:6 Examples (A – F) (Hazard ratio and 95% CI)

Estimated benefit of

standard drug over placebo

Zone of

noninferiority

Test drugbetter

Standarddrug better

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

A

Superiority

B

C

Noninferiority(i.e., Equivalence)

Inferiority

D

E

Underpowered trial

F

A = Test drug is superior to standard


Interpretation of non inferiority trials 6 examples a f hazard ratio and 95 ci1

Interpretation of Non-Inferiority Trials:6 Examples (A – F) (Hazard ratio and 95% CI)

Estimated benefit of

standard drug over placebo

Zone of

noninferiority

Test drugbetter

Standarddrug better

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

A

Superiority

B

C

Noninferiority(i.e., Equivalence)

Inferiority

D

E

Underpowered trial

F

B = Test drug is better than standard and can be considered“non-inferior” to standard


Interpretation of non inferiority trials 6 examples a f hazard ratio and 95 ci2

Interpretation of Non-Inferiority Trials:6 Examples (A – F) (Hazard ratio and 95% CI)

Estimated benefit of

standard drug over placebo

Zone of

noninferiority

Test drugbetter

Standarddrug better

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

A

Superiority

B

C

Noninferiority(i.e., Equivalence)

Inferiority

D

E

Underpowered trial

F

C = Test drug is worse than standard but not that much worse,and can be considered “non-inferior” to standard


Interpretation of non inferiority trials 6 examples a f hazard ratio and 95 ci3

Interpretation of Non-Inferiority Trials:6 Examples (A – F) (Hazard ratio and 95% CI)

Estimated benefit of

standard drug over placebo

Zone of

noninferiority

Test drugbetter

Standarddrug better

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

A

Superiority

B

C

Noninferiority(i.e., Equivalence)

Inferiority

D

E

Underpowered trial

F

D = Test drug is inferior to standard and non-inferiority

criteria not satisfied.


Interpretation of non inferiority trials 6 examples a f hazard ratio and 95 ci4

Interpretation of Non-Inferiority Trials:6 Examples (A – F) (Hazard ratio and 95% CI)

Estimated benefit of

standard drug over placebo

Zone of

noninferiority

Test drugbetter

Standarddrug better

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

A

Superiority

B

C

Noninferiority(i.e., Equivalence)

Inferiority

D

E

Underpowered trial

F

E = Test drug is very inferior to standard (non-inferiority

criteria not satisfied)


Interpretation of non inferiority trials 6 examples a f hazard ratio and 95 ci5

Interpretation of Non-Inferiority Trials:6 Examples (A – F) (Hazard ratio and 95% CI)

Estimated benefit of

standard drug over placebo

Zone of

noninferiority

Test drugbetter

Standarddrug better

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

A

Superiority

B

C

Noninferiority(i.e., Equivalence)

Inferiority

D

E

Underpowered trial

F

F = Trial is inconclusive due to small size and resultant wide CI


Possible reasons for non significant difference

Possible Reasons forNon-Significant Difference

  • Small sample size

  • Poor compliance to study treatments

  • Losses-to-follow-up

  • Equivalent regimens

Absence of proof of a treatment difference does

not constitute proof of an absence of a treatment difference.


Non inferiority and equivalence trials considerations

Non-Inferiority and Equivalence TrialsConsiderations

  • Cannot prove Pe = Pc or µ1 = µ2 therefore Ho: δ< 0 versus HA : δ> 0 is not correct because a small, underpowered study could incorrectly lead to a claim of equivalence – absence of evidence is not evidence of absence, and if power is too high, Ho may be rejected when the difference is not important.

  • Since Ho cannot be accepted, either reverse the roles of type 1 and 2 errors (i.e., rejection of Ho implies equivalence) or focus on confidence intervals

  • Treatment difference must be chosen not only to rule out smallest clinically meaningful difference, but also to be sure new treatment is better than no treatment

  • Consensus on what equivalence means, especially in a broad sense, is hard to achieve


1 sided hypothesis testing non inferiority

1-Sided Hypothesis Testing (Non-inferiority)

A = new treatment; B = standard;PA and PB = event rates (failure rate)

If Ho is rejected, treatments are “equivalent”

Roles of null and alternative hypotheses are reversed. In practice, this is confusing to people.

Blackwelder W, Cont Clin Trials 1982


Parallel group studies with continuous outcomes sample size formula is the same except for 0

Parallel Group Studieswith Continuous Outcomes: Sample Size Formula is the Same Except for δ0

2

Note: If Δ=0, then this

is equivalent to

superiority trial to detect

δo with 90% power.


Example non inferiority trial for new bp lowering drug

ExampleNon-Inferiority Trial for New BP Lowering Drug

40132

4+2525

4-2 58

δO = 4 mmHg

Δ = 0, -2 (A better) and +2 (B better)

σ2 = 100; α = 0.025 (1-sided); 1-β = 0.90

1:1 allocation

No. per

group

δO

Δ


Confidence interval approach example of type i error

Confidence Interval ApproachExample of Type I Error

A (newtreatmentbetter)

B (standardtreatmentbetter)


Confidence interval approach example of type ii error

Confidence Interval ApproachExample of Type II Error

A (newtreatmentbetter)

B (standardtreatmentbetter)


Sample size for equivalence design based on ci limits a new treatment b standard

Prob (upper limit of CI exceeds

d

when

d

<

d

)

=

0

0

é

ù

^

^

Prob

(

P

-

P

)

+

Z

s

>

d

=

b

ê

ú

a

A

B

ë

û

0

1

-

2

é

ù

^

^

(

P

-

P

)

-

(

P

-

P

)

d

-

(

P

-

P

)

ê

ú

A

B

A

B

A

B

Prob

>

-

Z

=

b

0

ê

ú

a

s

s

1

-

ê

ú

2

ë

û

P

(1

-

P

)

P

(1

-

P

)

s 2

=

+

A

A

B

B

N

N

A

B

Sample Size for EquivalenceDesign Based on CI LimitsA = New Treatment; B = Standard


Sample size for equivalence design based on ci limits cont a new treatment b standard

Sample Size for EquivalenceDesign Based on CI Limits (cont.)A = New Treatment; B = Standard

(

)

Makuch and Simon (Cancer Treatment Reports, 1978) suggest a = 0.10 (1-sided) and b = 0.20; I like a = .05 (and usually 2-sided)


For proportions and relative risks farrington and manning s approach is better

For Proportions and Relative Risks, Farrington and Manning’s Approach is Better

  • Problem arises because of estimation of variance under the null hypothesis.

  • Farrington and Manning (Stat Med 1990) have shown that their maximum likelihood approach is better particularly for small values of pc and pe.

  • Algorithm can be easily programmed.

Stat Med 1990; 9:1447-1454


Trial objectives

Sample Size for Proportions for Non-Inferiority Trial: Makuch and Simon versus Farrington and Manning (PA=PB)*

0.050.050.019,97210,032

0.100.100.05756775

0.150.150.051,0711,080

0.200.200.051,3441,348

0.200.200.10336340

Sample Size per Group

Makuchand Simon

Farrington

and Manning

PA(PE)

PB(PC)

δO

*α = 0.025 (1-sided)

1-β = 0.90

1:1 allocation


Trial objectives

Sample Size for Proportions for Non-Inferiority Trial: Makuch and Simon versus Farrington and Manning (PA = or ≠ PB)*

0.100.100.05756 775

0.1250.100.053,3433,379

0.100.1250.05371 384

Sample Size per Group

Makuchand Simon

Farrington

and Manning

PA(PE)

PB(PC)

δO

*α = 0.025 (1-sided)

1-β = 0.90

1:1 allocation


Trial objectives

Sample Size for Proportions: Superiority Trial with Specified Delta or Inferiority with Farrington and Manning(1:1 allocation and 1-β = 0.90)

0.050.050.019,02110,0328,174

0.100.100.05581775 630

0.150.150.059171,080 880

0.200.200.051,2111,3491,099

0.200.200.10266340 277

Sample Size per Group

Superiority*

Farrington

and Manning**

PA(PE)

PB(PC)

δO

*α = 0.05 (2-sided)

PE=PC - δO

** α = 0.025 (1-sided)

in 1st column;

α = 0.05 (1-sided)

in 2nd column


Trial objectives

General Approach

RRo

RR

NewTreatmentBetter

StandardTreatmentBetter

RRo chosen so that if upper limit

< RRo, we conclude

“equivalence”

RRo usually ≠ 1.0


Example cpcra study of nelfinavir nfv and ritonavir rtv for patients with cd4 100

50%

67%

No PI

Treatment

Example:CPCRA Study of Nelfinavir (NFV) and Ritonavir (RTV) for Patients with CD4+ <100

  • In a placebo-controlled trial, RTV reduced the rate of progression to AIDS by 50%

  • The hypothesized relative risk (NFV/RTV) was chosen to correspond to a 33% loss of efficacy of RTV versus putative placebo

RR (RTV/Placebo) = 0.5Directly est.

RR (NFV/RTV) = 1.33Direct est.

RR (NFV/Placebo) = 0.67Indirectly est.


Confidence interval approach to monitoring rr nfv rtv

Confidence Interval Approachto Monitoring RR (NFV/RTV)

0.75

Lower

limit of

equiv.

1.0

No diff.

1.33

Upper

limit of

equiv.

RTV

Better

NFV

Better

Equivalence

Inconclusive


Non inferiority and superiority

Non-inferiority and superiority

The 95% CI for the difference between the control and the intervention are all >-δ,i.e. non-inferiority demonstrated.

In this case both non-inferiority and superiority have been demonstrated

0

No difference


Non inferiority and inferiority

Non-inferiority and Inferiority

The 95% CI for the difference between the control and the intervention are all >-δ,i.e. non-inferiority demonstrated.

In this case both non-inferiority and superiority have been demonstrated

In this case both non-inferiority and inferiority have been demonstrated

0

No difference


Convince design

CONVINCE Design

  • Based on the findings from 17 trials with over 50,000 participants, the CVD risk reduction associated with BP lowering by diuretics and beta-blockers was estimated as 24%.

  • Equivalence margin was set to ensure that there would be no more than a 50% loss of efficacy based on this point estimate.

  • Upper bound = 1.16 = 0.88 (12% reduction)/ 0.76 (24% reduction).

  • Lower bound = 1/1.16 = 0.86.


Prevention of tuberculosis

Prevention of Tuberculosis

  • Isoniazid (INH) given for 9 months is estimated to be 70% effective.

  • Event rate in INH group is estimated to be 1.5% after 2 years; in the absence of prophylaxis, this rate would be 5%.

  • Non-inferiority margin set at 0.75% (absolute difference); a rate in the 3-month rifapentine+INH of 2.25% (1.5%+0.75%) is close enough to claim non-inferiority. This would also ensure that rifapentine+INH was better than no treatment by 2.75% (5%-2.25%).

  • Results: 0.19% (rifapentine+INH for 3 months) vs 0.43% for INH for 9 months.

N Engl J Med 2011; 365:2155-2166.


Another example treatment of acute mi see editorial nejm 337 oct 16 1997

Another ExampleTreatment of Acute MISee Editorial NEJM 337:Oct. 16, 1997

Gusto IStudy(N = 41,021)

Background

Lower 95% CI limit for 30 day mortality difference for accelerated infusion of alteplase vs. streptokinase = 0.4% (30 day mortality: 6.3 vs 7.3%) (need N = 50,000 to rule out difference this big)


Two new studies

Two New Studies

Double bolus alteplase vs. accelerated infusion of alteplase (N = 7,169)

7.98% vs. 7.53%

1-sided 95% CI (-∞ to 1.49)

Not equivalent

Cobalt Study

30 day

mortality

Conclusion

Gusto III Trial

30 day

mortality

Conclusion

Double bolus reteplase vs. accelerated infusion of alteplase (N = 15,059)

7.47% vs. 7.24%

95% CI (-0.66 to 1.10)

Similar efficacy


Summary determining equivalence

Summary - Determining Equivalence

  • First step in establishing equivalence - define ‘limits of equivalence’ (± δ)

  • Having conducted the trial, calculate the 95% confidence intervals for the difference between the control and the new treatment

  • If the confidence interval is entirely within ± δ then equivalence is established


Summary determining non inferiority

Summary - Determining Non-inferiority

  • Equivalence requires that the difference

    control - new intervention is both > -δ and < δ, the new treatment must be neither worse nor better than the control by a fixed amount.

  • In contrast to equivalence with non-inferiority we are only interested in determining whether new treatment is no worse by an amount δ.


Analysis of non inferiority equivalence trials

Analysis of Non-inferiority/Equivalence Trials

  • Superiority trials are analysed by intention-to-treat (ITT) because it is the most conservative and least likely to be biased.

  • ITT analysis of non-inferiority trials is not conservative - there is a bias towards no difference.

  • Per protocol analysis is biased since not all randomised patients included.

  • Recommendation: Analyze by both ITT and per protocol (need to ensure power for both).


Testing for superiority after non inferiority

Testing for Superiority after Non-Inferiority

  • In some situations it may be appropriate to test for superiority after testing for non-inferiority.

  • Regulatory authorities do not require any multiplicity adjustment for this.

  • In this situation, while the primary analysis for non-inferiority might be based on a “per protocol” population, the primary analysis for the superiority analysis should be intention to treat.


Equivalence non inferiority trials summary

Equivalence/Non-Inferiority TrialsSummary

  • Equivalence is “in the eyes of the beholder”

  • The absence of a significant difference in a superiority trial does not imply equivalence

  • Need to be sure about the efficacy of the active control treatment based on earlier trials.

  • Sloppy trials yield “equivalent” results

  • Because of difficulty of interpretation, equivalence and non-inferiority trials should be used cautiously.

  • More head to head superiority comparisons of approved treatments are needed.


Quality of reporting of non inferiority and equivalence trials jama 2006 295 1147 1151

Quality of Reporting of Non-inferiority and Equivalence Trials(JAMA 2006;295:1147-1151)

  • Margin of non-inferiority/equivalence defined in most trials, but rationale for margin missing in majority of studies.

  • About 25% of reports did not give sample size justification in sufficient detail to reproduce it.

  • Less than 50% described both intention to treat and per protocol analysis.

  • About 15% of reports did not state confidence intervals.


Guidelines for reporting non inferiority and equivalence trials jama 2006 295 1152 1160

Guidelines for Reporting Non-inferiority and Equivalence Trials+(JAMA 2006;295:1152-1160)

  • Specification of whether the trial is a non-inferiority study

  • Sample size details (specification and rationale for non-inferiority margin)

  • Use of 1- or 2-sided confidence interval

  • Nature of analysis: intention to treat, per protocol or both

  • Presentation of results: confidence intervals

+ Builds on CONSORT guidelines for superiority trials.


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