Can Bias Evaluation Provide Protection Against False‐Negative Results in QT Studies Without a Positive Control Using Exposure‐Response Analysis?

Abstract

The revised ICH E14 document allows the use of exposure-response analysis to exclude a small QT effect of a drug. If plasma concentrations exceeding clinically relevant levels is achieved, a positive control is not required. In cases when this cannot be achieved, there may be a need for metrics to protect against false-negative results. The objectives of this study were to create bias in electrocardiogram laboratory QT-interval measurements and define a metric that can be used to detect bias severe enough to cause false-negative results using exposure-response analysis. Data from the IQ-CSRC study, which evaluated the QT effect of 5 QT-prolonging drugs, were used. Negative bias using 3 deterministic and 2 random methods was introduced into the reported QTc values and compared with fully automated data from the underlying electrocardiogram algorithm (COMPAS). The slope estimate of the Bland-Altman plot was used as a bias metric. With the deterministic bias methods, negative bias, measured between electrocardiogram laboratory values and COMPAS, had to be larger than approximately -20 milliseconds over a QTcF range of 100 milliseconds to cause failures to predict the QT effect of ondansetron, quinine, dolasetron, moxifloxacin, and dofetilide. With the random methods, the rate of false-negatives was ≤5% with bias severity < -10 milliseconds for all 5 drugs when plasma levels exceeded those of interest. Severe and therefore detectable bias has to be introduced into reported QTc values to cause false-negative predictions with exposure-response analysis.

Confirmation of the Cardiac Safety of PGF2αReceptor Antagonist OBE022 in a First‐in‐Human Study in Healthy Subjects, Using Intensive ECG Assessments

“…Analysis of drug‐related QT/QTc‐interval changes relative to plasma PK concentrations were conducted on all dose regimens in this part of the study. The ECGs used for this analysis required adjudication by qualified cardiologists in accordance with principles set out in the International Conference on Harmonisation (ICH) E14 guideline and subsequent question‐and‐answer documents . The principles of this analysis follow the statistical methods described by Garnett et al .…”

“…The ECGs used for this analysis required adjudication by qualified cardiologists in accordance with principles set out in the International Conference on Harmonisation (ICH) E14 guideline and subsequent question-and-answer documents. [16][17][18][19][20][21][22][23] The principles of this analysis follow the statistical methods described by Garnett et al 24 The effects of a meal on the ECG were used to establish assay sensitivity, that is, the ability of the study to detect small changes in the QTc. 22,25…”

Estimation of the Power of the Food Effect on QTc to Show Assay Sensitivity

“…Moreover, the proposed quality metric does not specifically address those types of error that could cause false‐negative results, that is, a negative bias for long QT intervals and a positive one for short QT intervals. More recently, Ferber et al (2017) investigated a measure constructed to specifically identify bias that could lead to false‐negative results by comparing the reported QTc values with those obtained by standard algorithms on continuous Holter recordings without any human intervention . This method, although promising, needs further validation before it can be applied widely.…”

“…Other methods of ensuring assay sensitivity as recommended by ICH E14 are therefore needed. Methods for bias evaluation were also considered to increase the confidence in the data collected from the IQ‐CSRC study . This published study demonstrated that significant bias has to be introduced to cause false‐negative results.…”

Early drug development: assessment of proarrhythmic risk and cardiovascular safety

“…In addition, the use of a positive control is not recommended as long as there is a placebo group and drug concentrations achieved are a multiple of the clinically relevant exposure. In addition, to mitigate against a false-negative study in cases where insufficient drug exposure occurs, method bias sensitivity (MBS) analysis [45] has been proposed by several stakeholders using the slope estimate of Bland-Altman plots as an indicator of potential bias. A bias severity <−10 msec over a range of QTcF values was proposed as the threshold measure that would confer a <5% false-negative rate of drug-mediated QT prolongation.…”