Drug Lit Exam 2- Active Compareator

Front 1

active comparator trial definition

Back 1

Comparison of a
standard or conventional therapy
(active entity) to a new therapy

Front 2

2 reasons you might want to do an active comparator trial

Back 2

Placebo is not possible or is unethical
•New treatment has a potential advantage over proven treatment

Front 3

4 ways a comparator might be better than proven treatment

Back 3

–Lower costs
–Less adverse effects
–Simpler dosing regimen
–New treatment is less invasive

Front 4

Active comparator must be proven effective in what conditions? (2) why?

Back 4

–In the same patient population in which the control was originally shown to be effective
–In a placebo control trial (ideally in more than one study)
–Otherwise--- you could be comparing two ineffective therapies.

Front 5

Use of a Placebo vs. Active Comparator

Back 5

“In cases where an available treatment is known to prevent serious harm, such as death or irreversible morbidity in the study population, it is generally inappropriate to use a placebo control.”

Front 6

when is it ok to use placebo

Back 6

•“In other situations, where there is no serious harm, it is generally considered ethical to ask patients to participate in a placebo-controlled trial, even if they may experience discomfort as a result, providing the setting is non-coercive and patients are fully informed about available therapies and the consequences of delaying treatment.”

Front 7

superiority trial

Back 7

To determine if new therapy is superior to standard or conventional therapy

Front 8

non inferiority trial

Back 8

To determine if new therapy is no worse than or as good as the standard therapy by a pre-defined margin

Front 9

equivalence trial

Back 9

New treatment is similar to standard treatment (not better, not worse)

Front 10

non inferiority vs. equivalence studies: confidence interval arrows

Back 10

-non inferiority - one sided arrows- care mostly about one side of confidence interval

-equivalence studies- concerned with both sides of confidence interval

Front 11

Active Comparator Trial Designs graphs

Back 11

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Front 12

superiority trial hypothesis

goal

statistical interpretation (what is used to gauge things)

Back 12

superiority trial hypothesis: to show no difference exists

goal (alternative hypothesis): show meaningful difference exists between treatments

statistical interpretation used: p-value

Front 13

non-inferiority/equivalence trial hypothesis

goal

statistical interpretation (what is used to gauge things)

Back 13

noninferiority or equivalence trial hypothesis: to show difference exists

goal (alt hypothesis): show meaningful difference does NOT exist

stat interpretation: CI

Front 14

confidence interval measures what in an AC trial

Back 14

A measure of the difference between treatment effects

Front 15

interpret the 95% confidence interval range (what does it mean)

Back 15

95% confidence interval is the range across which the results would probably fall 95 times if the trial were repeated 100 times

Front 16

why is CI better than p value for AC studies

Back 16

Provides more information than the p value in a non-inferiority study because it not only evaluates the null hypothesis but indicates the lower and upper bounds of the estimate

Front 17

4 challenges of using an AC trial (study conduct requirements, study conduction, focus)

Back 17

•Large sample size is necessary
•Active comparator must be proven effective
•Focus is on treatment difference
•Poor study conduct is frequently encountered

Front 18

active comparator must be proven effective in what 2 conditions

Back 18

–In the same patient population in which the comparator was originally shown to be effective
–In a placebo control trial (ideally in more than one study)

Front 19

why is poor study conduct frequently encountered in AC trials

Back 19

–No automatic check for internal validity (as in placebo controlled trial

Front 20

Active comparator trials are not useful for

Back 20

determining true effectiveness of the control or the drug

Front 21

3 challenges in interpreting AC trials

Back 21

•Understand the limitations of an ACT
•Terminology
–Lack of “superiority” does not mean “equivalence”
–“Non-inferiority” does not mean “equivalence”
•Poor reporting
–162 non-inferiority or equivalence trials were evaluated for quality of reporting
–33 (20%) satisfied reporting requirements (4/33 trials contained highly misleading conclusions)

Front 22

Most common active comparator trial design

Back 22

non inferiority trial

Front 23

Non inferiority trials Aim to demonstrate what?

Back 23

that the experimental treatment is not clinically worse in terms of effectiveness or safety compared to the standard treatment (active comparator)

Front 24

for non inferiority trials, what do you have to determine prior to the trial (for comparisons)

Back 24

•Necessary to determine a zone of clinical equivalence – non-inferiority margin (Δ)

Front 25

definition of non inferiority margin

how to interpret

Back 25

The maximum allowable difference between two treatments

The difference in treatment cannot be outside of the boundaries of the margin to claim “non-inferiority”

Front 26

the correct way to choose non inferiority margin (when should you choose it, size (2), what its based on)

Back 26

•Determine a priori
•Determine based on statistical reasoning and clinical judgment
•Smallest value that would be a clinically important effect
•Should be conservative (smaller) than the “clinically relevant” effect - (do not want the margin to be larger than the expected success of the control!!)

Front 27

CI size and sample size relationship

Back 27

Larger the CI, the smaller the sample size needs to be- so a lot of people use large CI

Front 28

relationship between non inferiority margin, success rate and sample size

Back 28

higher the success rate you want, the smaller the sample size can be (because odds of it being non inferior are higher due to wider margin)

the wider the inferiority margin, the smaller the sample size can be

Front 29

What if the authors wanted to claim superiority for
the new treatment (assuming it actually performed
better than the control)?

Back 29

can't do this

Front 30

effect of a large margin on:
sample size
chance that inferior treatment appears non inferior

chance that non inferior treatment appears inferior

Back 30

effect on sample size (can be smaller)
chance that inferior treatment appears non-inferior(goes up)
chance that non inferior treatment appears inferior (goes down)???

Front 31

effect of a small margin on:
sample size
chance that inferior treatment appears non inferior

chance that non inferior treatment appears inferior

Back 31

sample size: must be larger
chance that inferior treatment appears non-inferior: goes down
chance that non inferior treatment appears inferior: goes up

Front 32

non inferiority trial bias (2)

Back 32

• “Bias toward the null”
• Population Analysis Bias (using ITT)

Front 33

what does bias towards the null mean?

Back 33

No difference between active control and test treatment
results in a positive study

Front 34

how to avoid bias towards the null (general)

Back 34

Make sure factors that can dilute true differences between
treatments were avoided

Front 35

specific things you can do in the trial to avoid bias towards the null (factors to avoid that dilute true difference) (7)

Back 35

• Imprecise or poorly implemented entry criteria
• Poor blinding
• Poor compliance
• Drop-outs
• Recruitment of patients unlikely to respond
• Treatment crossovers
• Use of concomitant medications (treatments)

Front 36

what type of data analysis is preferred for superiority trials? why (what does it lead to)

Back 36

– ITT analysis is preferred for superiority trials
• Leads to smaller observed treatment effects than if all
patients adhered to the treatment

Front 37

issue with using ITT analysis in non inferiority studies

Back 37

– ITT analysis in non-inferiority can falsely lead to
the claim of non-inferiority

Front 38

best way to do population analysis for non inferiority

Back 38

PP (AKA “on treatment”, “microbiologically evaluable”,
etc.) and ITT analysis are important for non-inferiority
trials

Front 39

goal of superiority active comparator trial

Back 39

Goal is to detect a difference between the new treatment (T) and the standard treatment (C)

Front 40

superiority active comparator trials are most often designed when?

Back 40

Most often designed when there are obvious new advances in therapy or the effect of the active comparator is small

Front 41

superiority active comparator trial- sample size requirements

Back 41

Requires very large sample size and if superiority is not shown, cannot easily switch to non-inferiority

Front 42

Ho of superiority AC trial

research data aims to do what?

Back 42

{non-superiority} ; research data will aim to reject the hypothesis so that T > C

Front 43

point estimate

Back 43

best estimate of the size of the difference between treatments

Front 44

confidence interval and crossing zero (for superiority)

Back 44

The two-sided confidence interval for the difference between the means excludes zero- it's ok to include zero for non inferiority??

Front 45

things to keep in mind about superiority trials (sample size, validity, control)

Back 45

Control must be effective
Remember there is no internal check for validity - bias
–The sample size may be too small (active control superiority trials require VERY large sample sizes)

Front 46

lack of superiority and equivalence

Back 46

–Lack of superiority ≠ equivalence

Front 47

switching type of trials in superiority AC studies

Back 47

–Can switch from non-inferiority to superiority if meet statistical requirements

Front 48

equivalence- what is required for equivalence

Back 48

•Two formulations whose rate and extent of absorption differ by less than -20% or +20% are generally considered bioequivalent (equivalent)

Front 49

what is used to establish bioequivalence between 2 drug products/formulations?

give 3 examples

Back 49

•Pharmacokinetic parameters of time-concentration curves (plasma or serum concentration)

–Peak plasma concentration achieved (Cmax)
–Time to achieve this peak concentration (Tmax)
–Area under the blood time concentration curve (AUC)

Front 50

sample size- what to take into account when calculating

what to report (2)

Back 50

take into account noninferiority/equivalence margin

report all elements necessary to reproduce calculation

report proportion of dropouts forseen

Front 51

requirements for reporting conclusions

Back 51

conclude noninferiority or equivalence ONLY if ITT and PP permit that and only use that vocab