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

1. Practical Issues to Consider: Design and Analysis of Thorough QT/QTc Study Venkat SethuramanFDA/Industry Workshop, 14-16 Sept., 2005

2. 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

3. 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 HR = (60/RR), with RR in sec QTcF & QTci are generally preferred correction for ‘thorough’ QT study.

4. Background - Impact on Type I Error (Simulation) Assume QTcB is the true QT-RR relationship

5. 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.

6. 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

7. 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

8. 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.

9. 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

10. 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.

11. 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?

12. Treatment Estimates from Crossover * Arth. Mean or LS mean difference

13. Categorical Results Increase in QTc> 30, 60 msec Categorical results might be affected if a diurnal variation in QTc is ignored. *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.

14. Moxifloxacin Treatment Estimates Published 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

15. Baseline Differences in a Crossover (An Example)

16. 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)

17. Time-match Pre-dose Pre-dose + placebo

18. Impact on QT Correction Method

19. Impact on QT Correction Method

20. 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 • Mean CFB QTc for study drug and placebo & • k refers to # of time points

21. 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.

22. 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. From Simulation

23. 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.

24. 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.

25. 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.

26. Reference • Bazett JC. An anlysis of time relations of electocardigrams. Heart 1920; 7:353-367. • Fridericia LS. Die Systolendauer im Elektrokardiogramm bei normalen Menschen und bei Herzkranken. Acta Medica Scandinavia 1920; 53:469-486 • Malik M. Problems of heart rate correction in the assessment of drug-induced QT interval prolongation. Journal of Cardiovascular Electrophysiology 2003; 12:411-420 • 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 • Leslie Kenna, et. al., Clinical Pharmacology Subcommittee of the Advisory Committee for Pharmaceutical Science (2003) • 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) • 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

27. 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