Practical Issues to Consider: Design and Analysis of Thorough QT/QTc Study Venkat Sethuraman...

Practical Issues to Consider: Design and Analysis of Thorough QT/QTc Study

Venkat SethuramanFDA/Industry Workshop, 14-16 Sept., 2005

2 V Sethuraman/FDA-Industry Workshop/14-16 Sept., 2005

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


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


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


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.


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



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


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.


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



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.


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?


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


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.


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

http://www.fda.gov/ohrms/dockets/ac/03/briefing/3956B1_01_FDA-alfuzosin.htm

http://www.vesicare.com/pdf/vesicare_prescribing_info.pdf


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


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


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


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


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


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.


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


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.


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


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.


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


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

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Practical Issues to Consider: Design and Analysis of Thorough QT/QTc Study Venkat Sethuraman...

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