Detection of QTc effects in small studies--implications for replacing the thorough QT study

Abstract

Background: ECG assessment with exposure response analysis applied to data from First-in-Man studies has been proposed to replace the thorough QT study for the detection of small QT effects.

Methods: Data from five thorough QT studies, three with moxifloxacin, one study with a drug with a large QTc effect (∼25 ms) and one with ketoconazole with a smaller QT effect (∼8 ms) were used. By subsampling, studies with 6-18 subjects on drug and six on placebo were simulated 1000 times per sample size to assess whether small QTc effects using ICH E14 criteria could be excluded and the impact of sample size on the estimate and variability of the slope of the concentration/QTc relation.

Results: With a sample size of nine or more on drug and six on placebo, the fraction of "false negative studies" was at or below 5% with data from the studies with moxifloxacin and from the drug with a large QTc effect. With the same sample size and no underlying QTc effect (placebo), the fraction of studies in which an effect above 10 ms could be excluded was above 85%. A treatment effect in the linear concentration-effect model resulted in a lower proportion of "false negatives." Sample size had little influence on the average slope estimate of the concentration/QTc relationship.

Conclusions: For drugs with a QTc effect of around 12-14 ms, exposure response analysis applied to First-in-Man studies with careful ECG assessment can be used to replace the through QT study.

Keywords: First-in-Man; ICH E14; QT; QTc; clinical pharmacology; thorough QT study.

© 2014 Wiley Periodicals, Inc.

Figures

Figure 1

Placebo‐corrected, change‐from‐baseline QTcF (∆∆QTcF) and drug plasma levels in the full included dataset from the five TQT studies: (A) Moxifloxacin Study 1; (B) Moxifloxacin Study 2; (C) Moxifloxacin Study 3; (D) Ketoconazole study; and (E) Study with drug with a large QT effect.

Figure 2

An example from a simulated study with nine subjects on drug with no QT effect and six on placebo, in which a QTc effect above 10 ms can be excluded (“negative QT assessment”). The upper bound of the 90% confidence interval of the predicted QTc effect (grey shaded area) is below 10 ms (dotted line) within the range of observed plasma levels.

Figure 3

(A) Fraction of negative studies across increasing sample sizes for subjects on drug and 6 subjects on placebo. Levels below 5% are highlighted in grey. The fraction of negative studies with active (QT prolonging) drugs corresponds to the rate of false negatives, i.e., when the study incorrectly concludes that a QTc effect above 10 ms can be excluded for a QT‐prolonging drug. (B) Fraction of negative studies with the no‐effect simulation using placebo QTc and drug plasma concentration data. With a sample size of nine on drug and six on placebo, the fraction is above 90% for three of the studies (studies 1, 2, and 5) and above 85% for studies 3 and 4. The fraction of nonnegative studies (1–fraction of negatives) in the no‐effect scenario corresponds to the rate of false positives, i.e., when the study cannot exclude a QTc effect above 10 ms even though the drug does not cause QTc prolongation.

Figure 4

Fraction of simulated studies with a significantly, positive slope of the plasma concentration/∆∆QTcF relationship. With a sample size of 12 subjects on drug and six on placebo, the fraction of studies with a positive slope was above 80% for three of the studies. A sample size of 15 subjects was required to achieve a fraction at or above 90% for three of the five studies (studies 1, 3, and 5).

Figure 5

(A) The mean slope of the plasma concentration/ ∆∆QTcF relationship as a function of sample size (with six subjects on placebo for all scenarios). The mean slope for all simulated studies was only to a small extent affected by the sample size. Even though not directly comparable, slopes for the simulated studies of parallel design were similar to the mean slope of the full crossover dataset: Study 1: 2.6 ms/μg per mL (90% CI: 2.00–3.19); Study 2: 3.1 ms/μg per mL (90% CI: 1.80–4.37); Study 3: 4.6 ms/μg per mL (90% CI: 3.88–5.37). Study 4: 1.0 ms/μg per mL (90% CI: 0.64–1.30) Study 5: 1.46 ms/μg per mL (90% CI: 1.38–1.55). (B) Proportion of simulated studies for which the mean concentration/effect slope fell inside the 90% CI of the corresponding slope based on the full dataset.

Figure 6

Fraction of negative studies as a function of number of subjects on active (with six on placebo) with a linear concentration /QTc effect model without treatment effect. The result should be compared with Figure 3, in which a model with a treatment effect was used. The model without treatment effect resulted in an unacceptably high proportion of false negative studies on data from drugs with a small QTc effect from studies 1, 3, and 5 (A). In the no‐effect scenario, using placebo data, the fraction of negative studies was larger for all studies, i.e., the proportion of false positives was lower (B).