Main page > Education > Training > Web-based training program > Spring 2008 training series

Presented by Dr. Alex Dmitrienko (Lilly) on Thursday, May 22, 2008 (noon-2:00 Eastern time).

Download a copy of the white paper written by Dr. Alex Dmitrienko, Dr. Charles Beasley and Dr. Malcolm Mitchell to facilitate an open discussion of issues related to the design and analysis of thorough QT studies.

Comments submitted by QT experts across the industry.

Alfuzosin thorough QT study, Darifenacin thorough QT study, Duloxetine thorough QT study, Levetiracetam thorough QT study, Tadalafil thorough QT study, Tolterodine thorough QT study, Vardenafil thorough QT study. See thorough QT study references in the Cardiac Safety Annotated Bibliography.

Antunes M. Optimising the design of thorough QT/QTc studies. 2006 [Download presentation].

Bazett HC. An analysis of time relation of electrocardiograms. Heart. 1920; 20:174-195.

Boos D, Hoffman D, Kringle R, Zhang J. New confidence bounds for QT studies. Statistics in Medicine. 2007; 26: 3801-3817.

Cheng B, Chow SC, Burt D, Cosmatos D. Statistical assessment of QT/QTc prolongation based on maximum of correlated normal random variables. Journal of Biopharmaceutical Statistics. 2008; 18: 494–501.

Dmitrienko A, Smith B. Repeated-measures models in the analysis of QT interval. Pharmaceutical Statistics. 2003; 2: 175-190.

Eaton ML, Muirhead RJ, Mancuso JY, Lolluri S. A confidence interval for the maximal mean QT interval change due drug effect. Drug Information Journal. 2006; 40: 267-271.

Ferber G. Statistical aspects of a thorough QT safety assessment. 2008 [Download presentation].

Fridericia LS. Die Systolendauer im Elecktrokardiogramm bei normalen Menschen und bei Herzkranken. Acta Medica Scandinavia. 1920; 53: 469-486 [English translation: Fridericia LS. The duration of systole in an electrocardiogram in normal humans and in patients with heart disease. Annals of Noninvasive Electrocardiology. 2003; 8: 343-351]

Garnett CE, Beasley N, Bhattaram VA, Jadhav P, Madabushi R, Stockbridge N, Tornoe CW, Wang Y, Zhu H, Gobburu JV. Concentration-QTc relationships play a key role in the evaluation of pro-arrhythmic risk during regulatory review. The Journal of Clinical Pharmacology. 2008; 48: 13-18.

Glomb P, Ring A. Use of baseline ECGs in the evaluation of thorough QT studies with crossover design. 2008 [Download poster].

Lipicky RJ. Cardiac safety of noncardiac drugs. Morganroth J, Gussak I (Editors). Humana Press. 2005: 3-9.

Ma H, Smith B, Dmitrienko A. Statistical analysis methods for QT/QTc prolongation. Journal of Biopharmaceutical Statistics. 2008; 18: 553-563.

Morganroth J, Brozovich FV, McDonald JT, Jacobs RA. Variability of the QT measurement in healthy men, with implications for selection of an abnormal QT value to predict drug toxicity and proarrhythmia. American Journal of Cardiology. 1991; 67: 774-776.

Muirhead R. Recent developments in the analysis of QT interval data. 2008 [Download presentation].

Nagy D, DeMeersman R, Gallagher D, Pietrobelli A, Zion AS, Daly D, Heymsfield SB. QTc interval (cardiac repolarization): lengthening after meals. Obesity Research. 1997; 5: 531-537.

Offen W, Chuang-Stein C, Dmitrienko A, Littman G, Maca J, Meyerson L, Muirhead R, Stryszak P, Boddy A, Chen K, Copley-Merriman K, Dere W, Givens S, Hall D, Henry D, Jackson JD, Krishen A, Liu T, Ryder S, Sankoh AJ, Wang J, Yeh CH. Multiple co-primary endpoints: Medical and statistical solutions. A report from the Multiple Endpoints Expert Team of the Pharmaceutical Research and Manufacturers of America. Drug Information Journal. 2007; 41: 31-46.

Ring A. The relationship between pharmacokinetic exposure and QT prolongation in cardiac safety trials. 2008 [Download presentation].

Sagie A, Larson MG, Goldberg RJ, Bengtson JR, Levy D. An improved method for adjusting the QT interval for Heart Rate (the Framingham Heart Study). American Journal of Cardiology. 1992; 70: 797-801.

Shi J, Lasser T, Koziol T, Hinderling PH . Kinetics and dynamics of sematilide. Therapeutic drug monitoring. 1995; 17: 437-444.

Tsong Y, Shen M, Zhong J, Zhang J. Statistical issues of QT prolongation assessment based on linear concentration modeling. Journal of Biopharmaceutical Statistics. 2008; 18: 564-584.

Williams EJ. Experimental designs balanced for the estimation of residual ffects of treatments. Australian Journal of Scientific Research, Series A. 1949; 2: 149-168.

Zhang L, Dmitrienko A, Luta G. Sample size calculations in thorough QT studies. Journal of Biopharmaceutical Statistics. 2008; 18: 468-482 [SAS code for sample size calculations in thorough QT studies].

ICH E14. Clinical Evaluation of QT/QTc Interval Prolongation and Proarrhythmic Potential for Non-Antiarrhythmic Drugs [Download].

Question: Suggestions for handling missing ECG for a timepoint in a time-matched analysis (Slide 25)?
Response: Missing data do not typically cause major problems in early-stage studies. However, where there are missing measurements, repeated-measures models can be used to recover some of the missing information.

Question: Any literature on enhanced precision by increasing the number of beats measured per replicate (Slide 28)?
Response: I can't think of any papers on this topic. In general, if the information is combined across the beats within a single replicate, increasing the number of beats should reduce the measurement error.

Question: I assume a decision to go with only a supratherapeutic dose implies they did some animal studies (HERG) first and found the compound to be "clean" (Slide 38)?
Response: Yes, both pre-clinical and clinical data (multiple clinical studies are typically conducted before a thorough QT study is initiated) are taken into account to support this decision.

Question: Were these 4 studies all healthy normal volunteers (Slide 54)?
Response: Yes. Please see Zhang, Dmitrienko and Luta (2008) for more information about the studies.

Question: Why did you choose the Fridericia correction (Slide 55)? Are there any studies that show the difference in accuracy between different ways of QT correction (Bazett, Fridericia, etc)?
Response: The Fridericia correction was chosen because it is widely used in thorough QT studies. We have not specifically studied differences between the Fridericia-based variance components and variance components associated with other corrections but, based on an informal assessment, there are quite small.

Question: If you have a single post-dose time point what is the difference between Day and Time effects (Slide 56)?
Response: The model introduced on this slide assumes there are multiple post-dose time points.

Question: Why did you choose the covariance structure you are using now (Slide 56)? Any research behind that?
Response: A multivariate model with this covariance structure provides a reasonably good fit to QTc data. In general, the fit can improved by adding random terms with an autoregressive covariance structure but the magnitude of this improvement is quite small and we decided to stick with a straightforward compound symmetry assumption.

Question: Have you considered an assessment of optimal number of replicates that include the cost for the additional replicates (Slide 59)?
Response: Dr. Georg Ferber (Novartis) pointed out that, when one decides on the number of replicates and baseline measurements, one can calculate the total cost of the trial and look for a minimum. The costs for replicate ECGs and additional baseline measurements can be balanced against the savings made by a reduced sample size obtained. Monica Antunes (Novartis) discussed this topic in her 2006 presentation.

Question: How will the adjustment of multiple testing help to deal with the problem with more post-dose time points (Slides 80 and 81)?
Response: Unlike the naive approach (one-sided 95% confidence interval for the largest time-matched treatment difference is used regardless of the number of post-dose time points), the multiplicity adjustment controls the probability of incorrectly concluding that the test drug induces QTc prolongation.

Question: Does the FDA accept multiplicity corrected confidence intervals in thorough QT studies (Slides 80 and 81)?
Response: Based on information shared by statisticians across the industry, thorough QT studies in which the primary analysis utilized multiplicity corrected confidence intervals have been submitted to the FDA.

Question: In a crossover thorough QT study do you use the placebo period to calculate the QTcI (Slide 91)?
Response: Yes, all off-treatment ECG recordings are used to calculate the individual QT corrections.

Question: For your linear correction model on Slide 90, did you need to assume a variance/covariance structure?
Response: If there are multiple ECGs per subject, a random subject term can be included in the model, which will induce a compound-symmetry variance/covariance structure. More complicated variance/covariance structures can be considered as well if they improve the fit of the model.

Question: We have multiple single arm trials (3 replicates at baseline), how to define the delta QTc (vs. plasma concentration) for exposure modeling (Slide 102)?
Response: When defining the change in QTc interval in the QTc-exposure analysis, it is important to account for circadian trends in QTc duration. In other words, one needs to perform a time-matched analysis of QTc changes (see Slide 25).