Alcohol Usage. (Units / Day) 1.1 ± 1.0 Smoking History (Cigarettes / Day) 0.0 ± 0.0 Cafeine Usage (Units / Day) 1.56 ± 1.16 HbA1c (%) 32.63 ± 2.6 ALAT (U / L) 25.84 ± 12.28 ASAT (U / L) 27.72 ± 7.16 Total Cholesterol (mmol / L) 4.2 ± 0.77 Creatinin (µmol / L) 81.03 ± 8.59 Glucose (mmol / L) 4.67 ± 0.45 pr Interval (ms) 149.13 ± 19.94 QrS Duration (ms) 101.0 ± 8.39 QT interval (ms) 405.89 ± 23.69 Mean and upper limit of 90%CI of ΔΔqtc The variability of the mean ΔΔqtc reduced substantially with each additional ecg replicate and remained within 0.5 ms (10 % of the safety limit of 5 ms) after 14 ecg replicates for all qt correction formulas. In Figure 1, the mean ΔΔΔqtc for each number of ecg replicates for each qt correction formula is displayed. In addition, Figure 3 displays the results for a single cohort, with green squares that indicate a ΔΔqtc prolongation <5 ms and red squares that indicate a ΔΔqtc prolongation of >= 5 ms. Decile Estimated mean ± SD investigational Mean ± SD QT prolongation (ms) using Mean ± SD QT prolongation (ms) using Mean ± SD QT prolongation (ms) using medicinal 3 EcG 5 EcG 18 EcG compound wreplicates replicates replicates concentration (ng/mL) 1 7.6 ± 2.5 6.51 ± 16.59 5.21 ± 12.47 4.84 ± 11.54 2 23.2 ± 3.1 6.08 ± 7.13 8.37 ± 5.63 7.31 ± 5.2 3 59.6 ± 10.7 -1.04 ± 10.79 0.45 ± 14.15 0.83 ± 13.11 4 119.6 ± 18.8 5.93 ± 11.59 8.78 ± 10.08 6.53 ± 9.6 5 181.3 ± 12.8 0.81 ± 9.06 2.82 ± 6.54 3.55 ± 7.93 6 238.5 ± 22.7 9.74 ± 13.30 9.01 ± 11.84 9.28 ± 12.15 7 335.3 ± 30.2 16.61 ± 13.63 15.65 ± 12.52 15.11 ± 11.96 8 397.9 ± 16.2 16.12 ± 18.56 14.56 ± 13.02 15.42 ± 12.72 9 485.3 ± 32.0 5.06 ± 13.22 7.46 ± 13.38 6.77 ± 13.71 10 616.1 ± 55.5 19.40 ± 13.37 20.17 ± 9.01 19.78 ± 10.98 Slope (ml*ng-1*ms) 0.022492 0.021380 0.022055 R2 0.462857 0.539141 0.583485 p-value 0.030387 0.015601 0.010115 The variability of the range of the 90% CI of the ΔΔqtc also reduced substantially with additional (>1) ecg replicates and remained within 0.5 ms after 11 ecg replicates for all qt correction formulas. Different qt correction formulas and the ecg replicates are displayed in Figure 2 for the range of the 90% CI of the ΔΔqtc. Concentration-effect analysis of ΔΔqtc The result of the assessment of the effect of the number of ecg replicates on the concentration-effect analysis is shown in Table 3. Figure 3 Mean ΔΔqtc in milliseconds of an example cohort (Cohort 1) for each number of ECG replicates for every correction method. In this Figure the variation between the number of ECG replicates and between the correction formulas can be clearly seen. The mean IMp concentration per decile is displayed together with the estimated qt prolongation measured using 3, 5 and 18 ecg replicates corrected with the Fridericia formula and corresponding slope. For all qt correction formulas, a significant association was found in the concentration-effect analysis. This was also observed for all numbers of ecg replicates. Discussion Based on our analysis we showed that the number of ecg replicates in qt studies has a substantial effect on the interpretation of a compound’s qt interval prolonging potential for all deployed qtc formulas.We observed an effect on the mean qtc interval prolongation and on the range of the 90% confidence interval of the qtc interval prolongation – parameters that are required by the regulators. To the best of our knowledge this is the first study to address the influence of the number of ecg replicates on the qt prolongation. The ICH e14 document4 dictates that, for accurate assessment of the qt interval, at least triplicate ecgs are implemented although evidence for this is limited. The specified cut-off for a positive tqt is 5 ms for mean ΔΔqtc prolongation. The present analysis showed that all qt correction formulas have a mean difference of 1 ms when triplicate ecgs were extracted compared to 18 ecg replicate extraction. This implies that triplicate ecg extractions are likely to results in inaccurate qt-estimation and can only be used as exploratory method, but not to unambiguously quantify a qt prolonging effect. The concentration-effect analysis has recently gained more at- tention in assessing the qt prolonging effect of a compound.8 The present analysis corroborates these observations, as the concen- tration-effect analysis was substantially more robust in detecting a qt prolonging effect of the investigated compound as it was in- dependent from the qt correction formula that was used and the number of ecg replicates. It is shown also here that the difference in qt prolongation between subjects becomes less when more qt replicates are measured. This can be deduced from the standard deviations, the R2 and the p-values. However, despite the decrease in variance in qt prolongation with an increase in the number of ecg replicates, the dose-effect relationship (slope) hardly changes. Noteworthy, applying ▇▇▇▇▇▇’ qt correction formula underesti- mated the drug plasma concentration that would result in a 10 ms qt interval prolongation. Several studies have compared the agreement of multiple qt correction formulas in large datasets that were collected in healthy volunteers.12,13 In those studies it was reported that the agreement between the most frequently deployed qt correction formulas is limited (Bazett’s and ▇▇▇▇▇▇▇▇▇▇’s correction formulas). The two main issues with qt correction for rr interval are 1) the intrinsic variability of qtc interval due to the beat-to-beat rr interval variation, and 2) the absence of a gold standard – which makes complete validation of qt correction formulas virtually impossible. Other studies have suggested that an individual qt/rr interval calculation may provide the best rr correction of the qt interval.15,16 Unfortunately we could not confirm this in the current work due to limitations of the data set, requiring a wider range of rr intervals to be available for analysis. The present analysis shows that the variability of mean ΔΔqtc for all qt formulas exceeds 0.5ms until 14 ecgs have been recorded and included in the analysis. This finding indicates that on average, the mean ΔΔqtc deviates by more than 10% of the safety limit from the best measured mean ΔΔqtc (based on 18 replicates per subject), when based on fewer than 14 replicates per subject. This underlines the previously identified issues with correction of qt for the rr interval, but also indicates that the performance of these qt correction formulas is comparable. The present analysis, in line with previous studies, confirms the suitability ofa phase I SAD study as replacement for a tqt.8,9 in particular with implementation of a 24 hour 12-lead ▇▇▇▇▇▇ ecg. This provides optimal flexibility to accurately assess the effect of a compound on the qt interval. Furthermore, the analysis on a large volume of ecg replicates can be performed after the compound’s development has been moved into a later stage and can be cancelled in case the development of the compound is abandoned, thereby saving resources.
Appears in 3 contracts
Sources: Doctoral Thesis, Doctoral Thesis, Doctoral Thesis