Practical Issues to Consider: Design and Analysis of Thorough QT/QTc Study
Venkat SethuramanFDA/Industry Workshop, 14-16 Sept., 2005
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Outline
Introduction
ICH E14; QT correction methods
Study Design Considerations
Choice of Baseline; positive control; # of ECG replicates
Crossover versus Parallel group
Disease specific Considerations
Hypotheses & Sample Size
Analysis
Central Tendency & Categorical Analysis
Summary of issues/resolutions
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Background – QT interval
QT Correction: QT and RR are correlated so a need for correction.
Fridericia’s correction:
QTcF = QT/RR0.33
Bazett’s correction:
QTcB =QT/RR0.5
Pooled correction:
QTcP =QT/RRb
Individual Correction:
QTci =QTi/RRibi
E:Moxifloxaxin 400mg
HR (bpm)
QT
(mse
c)
40 50 60 70 80 90 100
340
380
420
460 Model: QT= 540.95 -2.44 * HR
F:Placebo
HR (bpm)
QT
(mse
c)
40 50 60 70 80 90 100
340
380
420
460 Model: QT= 535.57 -2.44 * HR
QTcF & QTci are generally preferred correction for ‘thorough’ QT study.
HR = (60/RR), with RR in sec
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Background - Impact on Type I Error (Simulation)
HR change
Typ
e I
err
or
0 5 10
0.0
0.2
0.4
0.6
0.8
1.0
Bazett
HR change
Typ
e I
err
or
0 5 10
0.0
0.2
0.4
0.6
0.8
1.0
Fridericia
HR change
Typ
e I
err
or
0 5 10
0.0
0.2
0.4
0.6
0.8
1.0
Pooled Data-driven
HR change
Typ
e I
err
or
0 5 10
0.0
0.2
0.4
0.6
0.8
1.0
Individual Data-driven
HR change
Typ
e I
err
or
0 5 10
0.0
0.2
0.4
0.6
0.8
1.0
Mixed Model
Assume QTcB is the true QT-RR relationship
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Background
ICH E14 – Step 4 (25May2005): “a negative ‘thorough QT/QTc study’ is one in which the upper bound of the 95% one-sided confidence interval for the largest time-matched mean effect of the drug on the QTc interval excludes 10 ms.”
Timing of ‘thorough’ QT study is usually flexible but required for all new products.
This study plays a critical role in determining the intensity of ECG data collection during later stages of drug development.
Usually conducted in healthy volunteers but in some instances cannot be conducted due to safety or tolerability concerns (e.g., cytotoxic cancer drugs).
ECGs should be manually read. Readers should be blinded to time, treatment and subject (one reader should read all the ECG recordings from a given subject).
Cost can be anywhere between $60-100/ECG.
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Study Design Consideration
Placebo-controlled study in normal healthy volunteers with a positive control.
Parallel versus Crossover Designs Crossover: smaller numbers of subjects; Facilitate QT correction
Parallel Group: long half-life drugs; multiple dose
Randomization & Blinding Thorough study should it be handled in a same manner as any
other pivotal trial.
Moxifloxacin visits should not be un-blinded (or single-blind) while keeping all other treatments blinded. This may induce HR differences or cause “habituation effects”.
A crossover study should be period-balanced in all treatments. Do not randomize subjects to receive Moxifloxacin in the first period and in subsequent periods randomized to active treatments.
In a parallel group, it is not required to have all subjects receive Moxifloxacin prior to being randomized to active treatments
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Study Design Consideration
Crossover Design Example 4-period Williams’ design with Active (therapeutic & supra-
therapeutic dose), placebo and positive control.
If active drug is administered under repeat dose conditions (say 5 days of dosing) then, the positive control can be 4 days of placebo + 1 day of moxifloxacin 400 mg.
Adequate washout between treatment groups (say at least 1 week)
Sample size usually ~50 subjects
Parallel Group Subjects randomized to one of 4 treatments
Baseline: recommended to have a 0-24 hr profile with time-match for post-dose
Sample size usually >~60 / arm
Adequate ECG sampling around tmax of active drugs.
Appropriate to consider at least 3 replicate ECG’s at each time point
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Endpoint: Change from Baseline QTc
Baseline definition:
Time-matched: Baseline for each session (or treatment) is the avg. of values at a time point (on baseline day) corresponding to the post-dose time point.
Pre-dose averaged: Baseline for each session (or treatment) is the average of pre-dose values (~1hr prior to dosing).
Time-averaged: Baseline for each session (or treatment) is the average of all values on baseline day.
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Endpoint: Change from Baseline QTc
Figure obtained from > Cornel Pater., Methodological considerations in the design of trials for safety assessment of new drugs and chemical entities Current Controlled Trials in Cardiovascular Medicine 2005, 6:1
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Study Design Consideration
Choice of Positive Control Moxifloxacin 400 mg (single dose) is usually used as a positive
control
Any other positive control? quinolones like, gatifloxacin, etc.
Effect of Moxifloxacin: The positive control should have an effect on the mean QT/QTc interval of about 5 ms (i.e., an effect that is close to the QT/QTc effect that represents the threshold of regulatory concern, around 5 ms). Detecting the positive control’s effect will establish the ability of the study to detect such an effect of the study drug. Absence of a positive control should be justified and alternative methods to establish assay sensitivity provided.
Factors that affect the estimation of Moxifloxacin Effect effects similar for Time-matched, time averaged or pre-dose averaged
baseline ?
the upper bound of the 95% one-sided confidence interval for the largest time-matched mean effect of the moxi relative to placebo OR Max. mean QTc effect of Moxi (unadjusted for placebo)?
Effects using QTci tends to be smaller than QTcF or QTcB.
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Impact of Positive Control
– Positive control shows >5ms effect (say QTcF) and active treatment shows or does not show effect
– Outcome: the study results are valid.
– If effect of Moxi>12-15ms, are the study results still valid?
– depends on subject population, correction method, baseline, days of separation from baseline to post-dose, etc.
– Positive control shows <5 ms effect
– If active treatment shows no effect, then it is a “failed” study or need to show alternate means of establishing assay sensitivity.
If active treatment shows a positive effect (say >15ms), does the effect of study drug still valid?
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Treatment Estimates from Crossover
Baseline Method
Trt (QTci) Point Estimate*
90% CI
Time-avg. Placebo -5 (-7, -2.7)
Moxi 3.5 (1.3, 5.7)
Moxi-Placebo 8.5 (7.6, 9.3)
Time-match Placebo -5.8 (-8.9, -2.8)
Moxi 6.8 (3.8, 9.8)
Moxi-Placebo (occurred at 1hr)
12.6 (9.7, 15.6)
Pre-dose avg.
Placebo -3.8 (-5.6, -2.1)
Moxi 5.0 (3.3, 6.8)
Moxi-Placebo 8.8 (8.0, 9.7)
* Arth. Mean or LS mean difference
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Categorical Results
Time-matched Time-averaged
/pre-dose avg.
Category Placebo Moxi Placebo Moxi
CFB QTc >30 ms <1% 3.5% 0% 0%
*Subjects were included if they had both baseline and post-dose measurements; ECG values at a time point was an average of 3 replicate measurement.
Increase in QTc> 30, 60 msec
Categorical results might be affected if a diurnal variation in QTc is ignored.
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Moxifloxacin Treatment Estimates Published
Parameter Comparison Point Estimate 90% or 95% CI
QTcF1 * Moxifloxacin 400 mg 13.9 (SD=15)
QTcF2 * Moxi 400mg – Placebo 12.7 (8.6, 16.8)
QTci2 * Moxi 400mg – Placebo 11.1 (7.2, 15)
QTcF3 ^ Moxi 400mg – Placebo 8 (6, 9)
QTci3 ^ Moxi 400mg – Placebo 7 (5, 8)
QTcF4 + Moxi 400mg – Placebo 11, 12, 16
(7, 14)(8, 17)
(12, 21)
1: Moxifloxacin SBA: Mean (SD) change from baseline QTc at Cmax using corresponding time on Placebo Day as baseline
2 . Alfuzosin QT study, and 3. Vardenafil QT study http://www.fda.gov/ohrms/dockets/ac/03/briefing/3956B1_01_FDA-alfuzosin.htm
4. Vesicare QT study: http://www.vesicare.com/pdf/vesicare_prescribing_info.pdf
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Baseline Differences in a Crossover (An Example)
Time(hrs)
Ba
selin
e Q
Tci b
y P
eri
od
0 5 10 15 20
40
04
05
41
04
15
42
04
25
Period 1Period 2Period 3
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Impact of Baseline on QT correction
Pre-dose data used for QT correction
3 pre-dose per period x 3-period
Estimates of QT correction may be unreliable
Difference can be as high as 40-50 ms for some subjects
Pre-dose + placebo treatment (crossover only)
All pre-dose + 12 post-dose time points (placebo)
Assume that placebo occurs equal number of times/period
Estimates could be different for placebo on period 3 (?)
Baseline day profile (0-24 hr)
All 12 baseline time points (each 3 ECG/time point)
Time-match Pre-dose Pre-dose + placebo
RR(ms)
QT
(ms)
600 800 1000 1200 1400
30
04
00
50
0
RR(ms)
QT
(ms)
600 800 1000 1200 1400
30
04
00
50
0
RR(ms)
QT
(ms)
600 800 1000 1200 1400
30
04
00
50
0
RR(ms)
QT
(ms)
600 800 1000 1200 1400
30
04
00
50
0
RR(ms)
QT
(ms)
600 800 1000 1200 1400
30
04
00
50
0
RR(ms)
QT
(ms)
600 800 1000 1200 1400
30
04
00
50
0RR(ms)
QT
(ms)
600 800 1000 1200 1400
30
04
00
50
0
RR(ms)
QT
(ms)
600 800 1000 1200 1400
30
04
00
50
0
RR(ms)
QT
(ms)
600 800 1000 1200 14003
00
40
05
00
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Impact on QT Correction Method
0
10
20
30
40
50
-50 0 50
QTci difference (profile vs pre-dose)
Pe
rce
nt
of T
ota
l
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Impact on QT Correction Method
0
10
20
30
40
-40 -20 0 20
QTci difference (profile vs pre-dose with placebo)
Pe
rce
nt
of T
ota
l
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Endpoint and Hypotheses
From E14: “... The upper bound of the 95% one-sided confidence interval for the largest time-matched mean effect of the drug on the QTc interval excludes 10 ms.”
To construct a CI for ‘largest time-matched difference” is a difficult statistical problem
Impact on type II error (sponsor’s risk) while planning these trials
Intersection-Union Hypothesis
kiH ipiSo ,.....2,1,10}{: )()(
kiH ipiS ,.....2,1,10}{: )()(1
)()( , ipiS -Mean CFB QTc for study drug and placebo &
-k refers to # of time points
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Hypotheses
Hochberg and Thamane (1987) - Multiple time points does not have any impact on the type I error rate (public risk).
I-U Test does not assure overall power of the test (sponsor’s risk), i.e., the more time points you test, the higher the chance of type II error.
Since observations within same subject (time points) are possibly correlated, it is expected that K hypotheses are also correlated.
Not aware of statistical methodology to obtain sample size accounting for the correlation.
Result from Simulation accounting for correlation.
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Hypotheses and Sample Size
Need to an understand the correlation structure and a prior estimate of .
Assume AR(1) =0.1
True treatment difference (active-placebo) = 2 ms.
Number of time points = 5
Sample size increases from n=62 per arm to 80 per arm to maintain power at 90%.
Sample size decreases to n=70 if correlation is assumed to be =0.5
Impact on sample size minimal if k>5.
Sample Size
Po
we
r
20 40 60 80 100
20
40
60
80
From Simulation
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Disease Specific Consideration (e.g., cytotoxic cancer drugs).
It may not be feasible to include positive control or even placebo
Limited baseline values
May not be possible to study in healthy volunteers
Uncertain in terms of positive control effects
May not be possible to achieve supra-therapeutic dose
Use PK-QT modeling to predict at higher dose
Use Monte Carlo simulation to simulate models with fixed and random effects to determine the expected value of the model.
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Disease Specific Consideration
An example using PK-QT simulation Consider a ‘thorough’ QT study
conducted at therapeutic dose in healthy volunteers
Due to toxicity of drug, a supra-therapeutic dose is not possible in healthy but PK exposure available from DDI study in patients.
Develop PK-QT models & use simulation to predict QT effects at higher exposure.
ijiijPK
ijiij SQTc
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Conclusion
‘Though’ QT study should be treated as any pivotal trial and should use robust design features.
In general, Crossover designs are preferred.
Proper attention should be given to the choice of positive control and expected effect size.
Baseline should be adequate to address both the central tendency analysis and categorical analysis.
Sample size should be adequately powered to protect type II error in the I-U hypothesis testing.
PK-QT modeling is highly recommended for all ‘thorough’ QT study.
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Reference
1. Bazett JC. An anlysis of time relations of electocardigrams. Heart 1920; 7:353-367.
2. Fridericia LS. Die Systolendauer im Elektrokardiogramm bei normalen Menschen und bei Herzkranken. Acta Medica Scandinavia 1920; 53:469-486
3. Malik M. Problems of heart rate correction in the assessment of drug-induced QT interval prolongation. Journal of Cardiovascular Electrophysiology 2003; 12:411-420
4. Evaluation of Vardenafil and Sildenafil on Cardiac Repolarization, Morganroth J, Ilson BE, Shaddinger BC, Dabiri GA, Patel BR, Boyle DA, Sethuraman VS, Montague TH, - The American Journal of Cardiology, 2004
5. Leslie Kenna, et. al., Clinical Pharmacology Subcommittee of the Advisory Committee for Pharmaceutical Science (2003)
6. ICH E14: The Clinical Evaluation Of Qt/Qtc Interval Prolongation And Proarrhythmic Potential For Non-antiarrhythmic Drugs (http://www.emea.eu.int/pdfs/human/ich/000204en.pdf)
7. Patterson S., et al. (2003). Investigating drug-induced QT and QTc prolongation in the clinic: statistical design and analysis considerations. Report from the Pharmaceutical Research and Manufacturers of America QT Statistics Expert Working Team
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Acknowledgements
Timothy Montague, GSK
Tianyu Li, Fox Chase Cancer Center, PA.
GSK QT Steering committee
Novartis QT sub-group
Joel Morganroth, eRT, PA
Lixia Wang, Novartis, NJ
Organizers: Sue Walker, George Rochester and Tim Montague