1. Paul Gallo 2019 Joint Statistical Meetings July 31, 2019
Implementing Effective DMC Decision-Making in Complex Clinical Trial Designs
Paul Gallo
2019 Joint Statistical Meetings
July 31, 2019

2. Expanding utilization of DMCs
The usage of Data Monitoring Committees has increased in recent years
So has the scope of potential recommendations, e.g.:
stopping or modifying a trial for ethical reasons based on safety concerns
stopping for demonstrated efficacy (usually based on a group sequential scheme)
stopping for lack of effect, or futility
implementing an adaptive design scheme
To be implemented efficiently while maintaining integrity and interpretability of trial results

3. Some issues Understanding relevant benefit-risk considerations
DMC role in complex / adaptive trials
Level / details of unblinding in DMC reports
Data quality
Stated role of the DMC statistician

4. 1) Benefit-risk Recently, often heard / seen: Do they really?
“DMCs evaluate benefit-risk”, or “DMCs assess benefit-risk”, etc.
Do they really?
In the same manner as:
FDA, when deciding whether a treatment should be available to patients, or what a label should describe?
Me and my doctor, when deciding on a course of treatment for me?

5. Data access
It’s increasingly accepted – correctly – that DMCs should have access to relevant safety and efficacy data
regardless of the specific focus of the monitoring plan
in order to ensure they can carry out their responsibilities to trial participants

6. Challenges
Interim data often can not convey a clear picture of either risk or benefit, much less both
misleading signals (especially early) are inevitable
different schedules / time courses of different outcomes
some important safety concerns are quite long-term
Expert DMCs sensibly integrate the strength of numerical signals, relevant scientific knowledge, consistency of patterns, etc.
e.g., what types of safety risks might be expected?
but sometimes there are surprises . . .

7. So, what does the DMC do for B-R?
Is this more correctly stated as “consider” rather than “assess” or “evaluate”?
What is the question the DMC addresses as it considers whether a trial should continue?
How about
Is this study a rational, ethical medical experiment that can provide important information on therapies that may have favorable benefit-risk profiles, without exposing participants to undue risks, relative to the answers it may provide?
Usually, not something that lends itself to simple algorithms

8. 2) Adaptive designs
Adaptive designs have received increasing focus during years
Examples of aspects that might be changed: sample size, treatment arms, patient population, randomization allocation, etc.
Validity of conclusions depends on adequate pre-specification of an adaptive plan

9. DMCs in adaptive designs
A DMC seems a natural party to consider for a role in the adaptation decision process
they’re already allowed access to interim results
independence, objectivity
Possible misunderstanding: what changes can a DMC implement pro-actively?
apart from their safety responsibilities, which always take precedence

10. DMC role adaptive trials
What the DMC can’t do
Proactively initiate aspects of change based on their review – essentially re-design the trial in a more favorable direction
pre-specification is a fundamental tenet of a valid design
What the DMC could do
Play a role in implementing a pre-planned adaptation scheme
note: doesn’t mean that actions are fully algorithmic

11. DMC as implementer FDA 2010 draft AD guidance: FDA 2018:
“a DMC can help implement the adaptation decision according to the prospective adaptation algorithm, but it should not be in a position to otherwise change the study design except for serious safety-related concerns that are the usual responsibility of a DMC”
FDA 2018:
“. . . revisions based on non-prospectively planned analyses can create difficulty in controlling the Type I error probability and in interpreting the trial results”

12. One board, or two?
Should adaptation decisions be made by a group separate from a more “familiar” DMC?
Both single and separate board models seem to have been used
FDA 2018 acknowledges both possibilities
Adaptations are an aspect of trial design – decisions may not be completely independent of other DMC recommendations
Personally, I’d usually recommend a single DMC (as per Antonijevic et al, TIRS 2013)

13. 3) Coding / unblinding Fully unblinded outputs? Coded, e.g., A / B?
Arguments in support of coding sometimes focus on the “accidental access” possibility
I actually saw this once: A / B, then C / D, E / F . . .
Different coding for efficacy vs safety (or other parameters with potential to de-code)?
Or else, how can the DMC take into account critical benefit-risk considerations?

14. Fundamental principle
We need to be NOT in the mindset that added clarity of information to a DMC in any way compromises a trial

15. Options
Putting a de-coding envelope in the hands of the DMC usually satisfies most perspectives
opened whenever they want (even on Day 1), no need to request, or to tell anyone
In situations structurally more complex or where full labelling sensibly facilitates review (e.g., multiple doses), we’d do so up front
If a DMC initially insists on explicit labelling, we wouldn’t object

16. 4) Data quality / completeness
Data of less than perfect quality is a source of uncertainty
so is having less data!
Timely decisions, based on current available information, have important ethical implications
Inherent conflict between quality / completeness of data, and “recent-ness”
can’t recent, not-fully-cleaned data be relevant?
Overheard from an experienced DMC expert:
If it’s clean, it’s too old!

17. Data quality
A principle?: DMC should never make what turns out to be an incorrect decision because they didn’t understand limitations in the data they reviewed!
I like the idea of making essentially everything available, clearly explaining any limitations
Providing multiple versions? – e.g.,
clean / all?
adjudicated / all? (+ adjudication confirmation rates)
Allocate resources sensibly

18. 5) DMC statistician – a 2nd class citizen?
Proposals I’ve seen / heard:
The DMC statistician is “a non-voting member”
“No statistician is needed because the DMC is only reviewing safety”
DMC composition reflects a variety of expertises and perspectives relevant to a decision
Statistics is unquestionably one of these
Is “voting” over-emphasized anyway?
For major decisions, DMCs aim to arrive at a consensus that all members are comfortable with

19. Stated role of the DMC statistician
Safety review
These may be the setting where statistical perspective is most indispensable!
Strength of signal vs scientific plausibility vs degree of exploration vs consistency of related outcomes – what is the data really saying?
I would recommend to resist any specification of the DMC statistician as less than a full- fledged member

20. Thank you !!