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Break out session: Estimands in practice
Mouna Akacha (Novartis) and Julia Saperia (MHRA)
PSI Conference 2017 – London
May 16th 2017
Aim
 Gain familiarity in deciding on estimands
and apply structured framework in
different clinical trial settings
• Chronic pain
• Asthma
• Cancer-related wasting syndrome
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Estimands
A.
Population
Subjects targeted by
the scientific question
C.
Intervention
effect of interest
How potential
intercurrent events are
reflected in the scientific
question
B.
Variable
Quantities required to
address the scientific
D.
question
Summary
measure
On which the treatment
comparison will be based
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A lot of this boils down to...
 How do we account for intercurrent events that
themselves are informative about the effects of treatment?
• E.g. study treatment discontinuation due to AE or LoE,
intake of rescue or concomitant medication,
inevaluable tumor assessment, switch to new antineoplastic therapy (ANP), death etc.
Treatment discontinuation due to lack of efficacy
Patient 1
Patient 2
Patient 3
Patient 4
?
Patient 7
Randomisation
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Rescue medication
Death
Patient 5
Patient 6
Treatment
complete
Study discontinuation
Rescue medication
TIMELINE
Treatment discontinuation due to adverse
events
Study discontinuation
?
Primary endpoint
Some estimand approaches
 Treatment-Policy: Consider the variable regardless of
whether the intercurrent event has occurred
 Composite: Define the intercurrent event as a
component of a composite variable
 Hypothetical: Consider a given hypothetical outcome
associated with the intercurrent event
 Principal Stratum: Focus on the stratum of patients in
which an intercurrent event would not occur
 While-on-treatment: Consider the variable up to the
time of the intercurrent event
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Structured framework to bridge trial objectives with
statistical inference
Trial Objective
Estimand
(informing the trial design)
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Main Estimator
Sensitivity Estimator 1
...
Sensitivity Estimator 𝒌
Main Estimate
Sensitivity Estimate 1
...
Sensitivity Estimate 𝒌
Case studies
For these case studies
• each table will focus on one case study and
discuss the choice of estimands for
licensing purposes (~ 50 minutes)
• Justify your choice and if time allows discuss main and
sensitivity estimators
• choices of estimands and estimators will be
shared and discussed in the last 30 minutes
• Group’s responsibility to identify a person to feed back
Note: For the case studies we assume a certain design
is given – with the new framework the estimand choice
should drive/inform design choice.
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Case study 1 – Chronic pain
 Randomised, double-blind, placebo-controlled phase III study
 Compare a Drug X versus Placebo (on top of stable standard of
care) in the treatment of chronic pain
 Measurement of clinical interest: Change from baseline in pain
score at week 12
Week 12
Placebo
Drug X
•
•
•
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May take prohibited medication or rescue medication in periods where pain is not
well controlled – patients are followed up regardless
May change stable SoC doses
May discontinue study or treatment for various reasons, e.g. AEs and lack of efficacy
Case study 2 – Asthma
 Randomised, double-blind, active-controlled phase III study
 Inhaled corticosteroid (ICS) + long-acting beta agonist (LABA)
+ long-acting muscarinic antagonist (LAMA) vs ICS + LABA
• ICS + LABA + LAMA vs ICS + LABA
• both are fixed dose combination products
 Measurement of clinical interest: Change from baseline in lung
function at week 24
Week 24
ICS + LABA
ICS + LABA + LAMA
•
•
•
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Unbalanced treatment discontinuations expected – more in ICS + LABA arm
Alternative medication is given after stopping of randomised treatment
Randomised treatment must stop and rescue given if severe exacerbation
occurs
Case study 3 – Cancer-related wasting syndrome
 Randomised, double-blind, placebo-controlled phase III study
 Compare Drug X against placebo for weight gain in late-stage
cancer
 Measurement of clinical interest: Change from baseline in body
weight at week 12
Week 12
Placebo
Drug X
•
•
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Some patients die before the end of 12 weeks
Death may or may not be related to wasting syndrome
What would be appropriate estimands?
 Note: Should you require more information on
the specific settings to decide on the estimand
then
• Write down the information needed
• Consider different scenarios related to this
additional information
• Decide on estimands in the different scenarios
 Moderators will help you
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Moderators
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Mouna Akacha
Julie Anderson
Anna Berglind
Robert Cuffe
Christine Fletcher
Lisa LaVange
Michael O’Kelly
Alan Phillips
James Roger
Kaspar Rufibach
Julia Saperia
David Wright
- Novartis
- GSK
- AstraZeneca
- GSK
- Amgen
- FDA
- Quintiles
- ICON
- LSHTM
- Roche
- MHRA
- AstraZeneca
Additional considerations
 What if the comparator was standard of care
instead of placebo?
 Would you change your mind if your main
focus was the patient’s or physician’s
perspective?
 If you could, would you change anything in the
design?
 What if we were interested in non-inferiority
instead of superiority?
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