RCTs

Question 1

Example of criterias for randomization that are not really, but only quasi-randomized?

Answer 1

• Date of birth (odd/even), record number, day of enrollment, alternating

No concealment!!

Question 2

What is the goal of intention-to-treat analysis?

Answer 2

Preserve the balance of confounders, both measured and unmeasured to evaluate effectiveness (as opposed to efficacy).

In general, loss to follow-up is not random, but related to prognostic factors, which is why we need ITT as an unbiased estimate.

But careful - it’s also more conservative. Which can be both good and bad.

Question 3

What is industry bias?

Answer 3

RCTs sponsored by the industry have more favourable results

Question 4

What is the issue with surrogates outcomes?

Answer 4

Surrogate outcomes: biological or imaging markers that are thought to be indirect measures of the effect of treatment on clinical outcomes

They are misleading:
There are many examples of treatments that have had a major beneficial effect on a surrogate outcome, which had previously been shown to be correlated with a relevant clinical outcome in observational studies, but where the treatments have proved ineffective or harmful in subsequent large RCTs that used these same clinical outcomes

Question 5

What are the barriers to RCT?

Answer 5

1. Expensive/difficult
2. Broad findings (can’t be applied to a single individual)
3. Generalizability is bad
4. Ethical issues of randomizing
5. Time before results are out

Question 6

Selection bias in RCT is due to?

Answer 6

• Possibly poor random sequence generation (are the groups comparable?)
• Allocation that is not perfectly concealed

Question 7

Performance bias in RCT is due to?

Answer 7

Not double blinding, such that the hypothesis of the study is known

Question 8

Detection bias in RCT is due to?

Answer 8

Not blinding the outcome assessment (i.e., the outcome assessor needs to not know the allocation)

Question 9

Attrition bias in RCT is due to?

Answer 9

Incomplete outcome data, and not knowing the reason for attrition/exclusion

Question 10

Reporting bias in RCT is due to?

Answer 10

Selective outcome reporting (authors are more likely to publish studies and selectively report outcomes that show statistical significance)

Question 11

What is N=1 RCT? When and why do we use it?

Answer 11

When we have only one patient to observe, with the goal to determine the optimal intervention for this very patient.

Especially useful for:

• rare diseases
• comorbidities
• concurrent therapies

Requirements:

• Stable conditions
• Quick onset of action/termination of therapy

Question 12

Why do we use cluster randomization RCTs?

Answer 12

When we fear contamination (or when it’s cheaper, or for administrative convenience)

Question 13

What is the issue with cluster randomization and power?

Answer 13

Since the observations within a cluster are correlated, we need a larger N, depending on the ICC (correlation), which will be high if we had consistent practices.

Question 14

What formula do we use to determine the N needed for are cluster randomization RCT?

Answer 14

1 + (n-1)*correlation –> is the design effect factor, by which we must multiply the N

where n is the average cluster size

Question 15

What happens if we ignore cluster effect in cluster RCTs?

Answer 15

• We have extreme p-values and very narrow CI

- Leading to spurious significant findings

Question 16

What are the assumptions of a factorial RCT?

Answer 16

• Independent effects of A and B (no interaction/synergy)

Question 17

Why would we use a Active Control Trial?

Answer 17

• Ethic problems of using a placebo, especially when we have mortality or serious morbidity
• To make comparisons

Question 18

What is the main difference in terms of goal between superiority trials and noninferiority trials?

Answer 18

Superiority trial: want to know if new tx is better than std tx (e.g., we want to develop a better tx)

Non inferiority trial: want to know if the new tx is as good as the std tx (e.g., we want to develop a less expensive tx or a tx with less side effects)

Question 19

What is assay sensitivity?

Answer 19

The ability of a trial to distinguish an effective drug from an ineffective drug

Question 20

How does the interpretation of SUP and N-INF trials differ?

Answer 20

SUP: entirely interpretable without additional assumptions or information
N-INF: dependent on knowing that the control had the expected effect, which may not be measured in the study since we have no placebo arm

Question 21

What’s up with assay sensitivity in SUP and N-INF trials?

Answer 21

SUP: has, by definition, assay sensitivity
N-INF: whether or not it has assay sensitivity relies on external info, usually a historical control trial

• but even then, it could be undermined by poor compliance, non-protocol crossovers, spontaneous improvement, poorly responsive participants, and insensitive measures to drug effect

Question 22

What is the margin (M1)?

Answer 22

the maximum acceptable extent of clinical noninferiority of an experimental treatment

Question 23

Null hypothesis and alternative hypothesis FORMULA for non-inferiority trials

Answer 23

H0: C-T >= M1 (so the difference is larger than the threshold)
Ha: C-T

Question 24

Non-inferiority trials use ….-sided tests

Answer 24

one

Question 25

Null hypothesis of

a) Superiority trials
b) Non inferiority trials

Answer 25

a) HoSUP: There is no difference (not superior; doesn’t mean that they are equivalent though)
b) HoNInf: The new treatment is inferior to the standard*

*a noninferiority design statistically tests the null hypothesis that the experimental treatment is inferior by the equivalence margin.

Question 26

Alternative hypothesis of

a) Superiority trials
b) Non inferiority trials

Answer 26

a) HaSUP: There is a difference

b) HoNInf: There is no difference

Question 27

What’s up with non inferiority and equivalence trials?

Answer 27

Non inferiority trials are often called equivalence trials, but it’s a misnomer.

If the intent of a study is to demonstrate that differences between control and experimental treatments are not large in either direction, then it is known as an equivalence trial.

Non inferiority trials are one sided.

Question 28

What would be a
a) Type I error
b) Type II error
in a superiority trial

Answer 28

a) Falsely concluding Ha: Conclude that there is a difference, when there really is none
b) Falsely concluding Ho: Conclude that there is no difference when there is one

Question 29

What would be a
a) Type I error
b) Type II error
in a non-inferiority trial

Answer 29

a) Falsely concluding Ha: Conclude that the new treatment is noninferior (no difference) when the new treatment is actually inferior
b) Falsely concluding Ho: Conclude that the new treatment is inferior when there is no difference

Question 30

How do we determine the margin?

• assumptions?
• any limits?

Answer 30

• From a random effects meta-analysis of previous placebo-controlled studies of the standard treatment
• A mix of stats and clinical judgment

Assumptions: constancy assumption, which is unverifiable. Which is why non-inferiority margin are often a fraction of the standard treatment effect to be preserved

Limits: Must be smaller than the expected difference between the new treatment and a placebo

Question 31

In a graph, what if the 95% CI is situated:

a) Over the delta line?
b) Over the 0 line, but doesn’t cross the delta line?
c) After the 0 line?
d) Before the delta line?

Answer 31

a) Inconclusive
b) Non inferior
c) Superior
d) Inferior

Question 32

What are randomized registries?

Answer 32

You randomize treatment, and you follow-up using existing electronic data source (big data)
- diminishes the costs greatly!

Question 33

What are adaptive trials?

Answer 33

When you adjust the enrolment (by changing randomization rates, for example) as you go
- decreases the number of participants needed, gives greater flexibility

Question 34

What are platform trials?

Answer 34

They don’t focus on one intervention but on 1 disease with multiple interventions

Question 35

What are pragmatic trials?

Answer 35

Set in real-world setting (explanatory trials, on the other hand, are carefully controlled for)