1. Regulatory Perspectives on the Thorough QT/QTc Study
2005 FDA/Industry Workshop
Washington DC
September 16, 2005
Juan (Joanne) Zhang, Ph.D.
CDER/FDA
*Acknowledgement: Drs. Stella Machado & George Rochester

2. Disclaimer
This presentation represents the opinions of the author, and not necessarily those of the U.S. Food and Drug Administration.

3. Outline I. Thorough QT/QTc Study - Introduction Design Considerations
Statistical Test for a Negative ‘Thorough QT/QTc Study’
- Statistical Hypothesis & Test
- Intersection-Union Tests
False Positive and False Negative Probabilities
Assay Sensitivity
Summary

4. Thorough QT/QTc Study

5. Introduction
QT interval represents the time between start of ventricular depolarization and end of ventricular repolarization (QT).
QTc is the QT-interval corrected for heart rates

6. Introduction (2)
QT/QTc prolongation may cause ventricular arrhythmias including ventricular fibrillation and Torsade de Pointes, which can be fatal even though the degree of this association is not known
Current ICH E 14 Guidance requests all sponsors submitting new drug applications to conduct a thorough QT/QTc study
Generally conducted in early clinical development after some knowledge of the pharmacokinetics of the drug

7. Introduction (3) ICH E14 Guidance (Step 4, Adopted May 2005)
“The ‘thorough QT/QTc study’ is intended to determine whether the drug has a threshold pharmacologic effect on cardiac repolarization, as detected by QT/QTc prolongation.”
“The study is typically carried out in healthy volunteers (as opposed to individuals at increased risk of arrhythmias) and is used to determine whether or not the effect of a drug on the QT/QTc interval in target patient populations should be studied intensively during later stages of drug development.”

8. Negative ‘Thorough QT/QTc Study’
ICH E14 Guidance (Step 4, Adopted May 2005)
“…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.”

9. Non-negative ‘Thorough QT/QTc Study’
If a ‘thorough QT/QTc study’ is not negative, i.e., if at least one upper bound of the one-sided 95% confidence interval of the time-matched difference exceeds the threshold of 10 ms, the study is termed “Non-negative”.

10. Implications of Results from the ‘Thorough QT/QTc Study’
ICH E 14:
IF the ‘thorough QT/QTc study’ is negative – “the collection of baseline and periodic on-therapy ECGs in accordance with the current investigational practices in each therapeutic field is almost always sufficient evaluation during subsequent stages of drug development.”
IF ‘thorough QT/QTc study’ is non-negative – “additional evaluation in subsequent clinical studies should be performed.” Hence, expanded ECG safety evaluation during later stages of drug development are needed.

11. Design Considerations

12. Design Considerations
To better control variability and potential bias
Randomized, double blinded, placebo and active controlled, single or multiple doses of the drug, crossover or parallel study
Healthy volunteers, it is better to have similar number of males and females in the study (randomization stratified by gender)
Crossover design recommended if possible
For a crossover study, baseline at each period is recommended

13. Design Considerations (2)
QT data are highly variable, so control of all sources of variability is critical
Replicated QT measurements at each time-point are recommended. Typically ≥3 replicates. The mean of these replicates is used.
The baseline QT measurements should be taken as close to the treatment date as possible; typically either
At matching time-points on the day prior to drug treatment; or
At time 0 before dosing, the same day of treatment
QT interval data are adjusted for heart rate (HR) to obtain QTc values which are correlated with HR as little as possible.
Fridericia’s corrected values
Individual corrected values
Bazett’s corrected values

14. Crossover Design
A crossover QT/QTc study is recommended as opposed to a parallel study if possible since
It requires smaller number of subjects
The precision of estimated treatment differences is greater since subjects act as their own control
Methods and practice applicable in any cross-over trial should be applied in a crossover QT/QTc trial.
Some issues encountered in a crossover-trial need to be considered here; including period effect and carry-over or residual effect.

15. Crossover Design (2) Suppose a 4 TRT arm study DH: drug, high dose
DL: drug, low dose
P: placebo
PC: positive control
Some designs we have seen:
(Example 1)
Problems? – Can’t distinguish the period effect from the treatment effect.
Period 1
Period 2
Period 3
Period 4 PC P DL DH

16. Crossover Design (3) Example 2 Group Period 1 Period 2 Period 3
Problems? – Period effect is confounded with the treatments. This
concern only pertains to PC though.
Group
Period 1
Period 2
Period 3
Period 4 A DL DH P PC B C D E F

17. Crossover Design (Continued)
One recommended design for a 4 treatment study (a Williams Square)
Group 
Period 1
Period 2
Period 3
Period 4 A DL DH P PC B C D

18. Parallel For drugs with long elimination half-lives
Parallel group studies may have to be used under certain circumstances:
For drugs with long elimination half-lives
For drugs whose carryover effects are prominent

19. Sample Size Required for a Crossover Design and a Parallel Design
Notations:
N1 - # of subjects in a crossover study
N2 - # of subjects per arm in a parallel study
 - observed difference in treatment (adjusted for baseline) for an individual
SD() = 1 for a crossover;
2 for a parallel
D – SD for the drug
P – SD for placebo
12 – Correlation coefficient between the drug and placebo for the same individual (>0)
Relation between N1 and N2
In order to make Var(mean of ) the same for both crossover and parallel studies, we have
N2 = (2/ 1)2N1
Relation between 1 and 2: 22 = 12 + 212DP
For a 4 arm trial, sample needed for a parallel study can be at least 4 times more than a crossover study

20. Statistical Test for a Negative ‘Thorough QT/QTc Study’

21. Calculating Time-matched Mean Difference
How to estimate the time-matched population mean effect?
Qit: (Baseline adjusted) QT/QTc value for the ith subject at time t after receiving the drug
Pit: (Baseline adjusted) QT/QTc value for the ith subject at time t after receiving placebo
Time-matched mean difference at time t (suppose equal sample size N in both the drug and placebo groups)
Qit/N -  Pit/N = (For a crossover)
N is the number of subjects

22. Statistical Hypotheses
H0: t(D) - t(P) ≥  ms for at least one t
H1: t(D) - t(P) <  ms for all t
 is the non-inferiority margin (10 ms in the guidance)
t(D) and t(P) are the population means for the drug and placebo at time t, t=1,2,…,K. K is the total number of time points where QT has been measured.
Claim a negative QT/QTc study if H0 is rejected
Use  = 0.05

23. Statistical Test
Let be the observed average time-matched drug placebo difference after baseline adjusted at time t. Let Tt be the test statistic at time t, then
Tt = ( )/SD( )
Reject H0 if Tt < -t, N-1 for all t, where t, N-1 is the upper tail 
level critical value for the t distribution with N-1 df, and N is the
sample size.
The above procedure is to test if all one sided 95% CI upper
bounds are <  ms at each time point.

24. Intersection-Union Tests
Suppose Rt is the rejection region of a level- test for H0t: t(D) - t(P) ≥  ms, t=1,2,…,K, then the Intersection-Union Test with rejection region R= is still a level-  test for H0
No need for multiplicity adjustment to test for a negative thorough QT/QTc study

25. False Positive & False Negative Probabilities

26. Definitions Type I error: False Negative Probability (FNP)
FNP = P(Tt < - t, N-1 for all t | at least one true difference ≥ )
By IUT, FNP can be controlled under  (0.05) level
Type II error: False Positive Probability (FPP)
FPP = P(Tt ≥ - t, N-1 for at least one t | true difference < 5 ms at each time point)
Why 5 ms chosen: “… drugs that prolong the mean QT/QTc interval by around 5 ms or less do not appear to cause TdP” – ICH E14

27. Simulation Study Purpose: to evaluate the FNP and FPP Assumptions:
 = 8 ms, 10 ms
SD () = 8.5 ms based on a crossover study in house
# of times evaluated K = 5 and 15
Multi-normal assumption: NK(, )
 = 0.1 and 0.9
Sample size 65
10000 simulations per scenario

28. Results: False Negative Probability
Table 1
K=5
K=15   
(0,0,8,0,0)
(0,0,8,8,0)
(0-0,8,0-0)
(0-0,8,8,0-0)  8
0.1
0.044
0.005
0.051
0.004
0.9
0.041
0.036
0.047
0.028
(0,0,10,0,0)
(0,0,10,10,0)
(0-0,10,0-0)
(0-0,10,10,0-0)
 10
0.037
0.002
0.052
0.046
0.031

29. Results: Power (1-FPP) Curves (=(2,3,4,4,3)’, =0.1)

30. Results: Power (1-FPP) Curves (=(2,3,4,4,3)’, =0.9)

31. Conclusions This simulation example shows:
FNP is well controlled under the  level
FPP (or 1 - Power) is driven by
The true mean difference of the drug and placebo
The Non-inferiority margin
Variability of the data
Sample size

32. Assumed True Mean Difference
Is it true the greater the number of time points, the higher the type II error? (N=65)
Table 2
Scenario
, K
Assumed True Mean Difference
r=0.1
r=0.9 a
8, 5
(3,4,4.9,4,1)
0.134
0.109 b 
8, 15
(0,0,0,1,1,3,4,4.9,4,1,1,1,0,0,0)
0.132
0.103 c 
(1,1,1,4.9,1)
0.101
0.106 d
(0,0,0,1,1,1,1,1,4.9,1,1,1,0,0,0)
0.112
0.097 e
10, 5
0.001 f 
10,15 g  h
10, 15

33. Findings Focus on top half of table 2.
As long as the time points chosen can capture the relatively big QT/QTc effect, the number of time points does not change FPP (Scenarios (a) vs. (b), (c) vs. (d))
FPP can increase with the number of time points (Scenario (c) vs. (b))
FPP can decrease with the number of time points (Scenario (a) vs. (d)).
Conclusion: It is not always true that the FPP is an increasing function of the time points when QT/QTc are evaluated

34. Assay Sensitivity

35. Assay Sensitivity ICH E14:
“The positive control should have an effect on the mean QT/QTc interval of about 5 ms”
The positive control “should be well-characterized and consistently produce an effect on the QT/QTc interval that is around the threshold of regulatory concern (5 ms, section 2.2.).”

36. Statistical Procedures to Assess Assay Sensitivity
H0: t(PC) - t(P) < c ms for all t
H1: t(PC) - t(P) ≥ c ms for at least one t
How to choose c? Under discussion.
Challenge: Multiple endpoint issues (can’t apply IUT here)

37. Summary
A ‘thorough QT/QTc study’ is negative when the study drug is non-inferior to placebo in terms of the effect of QT/QTc interval.
If all the one-sided 95% upper limits of the time-matched mean difference between the drug and placebo after baseline adjustment are below  (the non-inferiority margin, 10 ms) at each time point, then we can claim a negative ‘thorough QT/QTc study’.
By the Intersection-Union test, there is no need for the multiplicity adjustment to claim the drug is non-inferior to placebo.
If possible, a crossover design should be considered.
Need more thoughts on assay sensitivity issues.