Enabling robust assessment of QTc prolongation in early phase clinical trials
Since the implementation of the International Conference on Harmonization (ICH) E14 guideline in 2005, regulators have required a “thorough QTc” (TQT) study for evaluating the effects of investigational drugs on delayed cardiac repolarization as manifested by a prolonged QTc interval. However, TQT studies have increasingly been viewed unfavorably because of their low cost effectiveness. Several researchers have noted that a robust drug concentration‐QTc (conc‐QTc) modeling assessment in early phase development should, in most cases, obviate the need for a subsequent TQT study. In December 2015, ICH released an “E...
Source: Pharmaceutical Statistics - March 1, 2017 Category: Statistics Authors: Devan V. Mehrotra, Li Fan, Fang Liu, Kuenhi Tsai Tags: MAIN PAPER Source Type: research
Addressing potential prior ‐data conflict when using informative priors in proof‐of‐concept studies
(Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - February 22, 2017 Category: Statistics Authors: Timothy Mutsvari, Dominique Tytgat, Rosalind Walley Tags: ERRATUM Source Type: research
Issue Information
Abstract
No abstract is available for this article. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - January 26, 2017 Category: Statistics Tags: ISSUE INFORMATION Source Type: research
Balanced covariates with response adaptive randomization
Abstract
Response adaptive randomization (RAR) methods for clinical trials are susceptible to imbalance in the distribution of influential covariates across treatment arms. This can make the interpretation of trial results difficult, because observed differences between treatment groups may be a function of the covariates and not necessarily because of the treatments themselves. We propose a method for balancing the distribution of covariate strata across treatment arms within RAR. The method uses odds ratios to modify global RAR probabilities to obtain stratum‐specific modified RAR probabilities. We provide illustrative...
Source: Pharmaceutical Statistics - December 31, 2016 Category: Statistics Authors: Benjamin R. Saville, Scott M. Berry Tags: MAIN PAPER Source Type: research
A Bayesian sequential design with binary outcome
Several researchers have proposed solutions to control type I error rate in sequential designs. The use of Bayesian sequential design becomes more common; however, these designs are subject to inflation of the type I error rate. We propose a Bayesian sequential design for binary outcome using an alpha‐spending function to control the overall type I error rate. Algorithms are presented for calculating critical values and power for the proposed designs. We also propose a new stopping rule for futility. Sensitivity analysis is implemented for assessing the effects of varying the parameters of the prior distribution and maxi...
Source: Pharmaceutical Statistics - December 31, 2016 Category: Statistics Authors: Han Zhu, Qingzhao Yu, Donald E. Mercante Tags: MAIN PAPER Source Type: research
Probability of success for phase III after exploratory biomarker analysis in phase II
The probability of success or average power describes the potential of a future trial by weighting the power with a probability distribution of the treatment effect. The treatment effect estimate from a previous trial can be used to define such a distribution.
During the development of targeted therapies, it is common practice to look for predictive biomarkers. The consequence is that the trial population for phase III is often selected on the basis of the most extreme result from phase II biomarker subgroup analyses. In such a case, there is a tendency to overestimate the treatment effect. We investigate whether the overe...
Source: Pharmaceutical Statistics - December 31, 2016 Category: Statistics Authors: Heiko G ötte, Marietta Kirchner, Martin Oliver Sailer Tags: MAIN PAPER Source Type: research
Statistical issues in first ‐in‐human studies on BIA 10‐2474: Neglected comparison of protocol against practice
By setting the regulatory‐approved protocol for a suite of first‐in‐human studies on BIA 10‐2474 against the subsequent French investigations, we highlight 6 key design and statistical issues, which reinforce recommendations by a Royal Statistical Society Working Party, which were made in the aftermath of cytokine release storm in 6 healthy volunteers in the United Kingdom in 2006.
The 6 issues are dose determination, availability of pharmacokinetic results, dosing interval, stopping rules, appraisal by safety committee, and clear algorithm required if combining approvals for single and multiple ascending dose stud...
Source: Pharmaceutical Statistics - December 31, 2016 Category: Statistics Authors: Sheila M. Bird, Rosemary A. Bailey, Andrew P. Grieve, Stephen Senn Tags: VIEWPOINT Source Type: research
Robust inference for group sequential trials
This article evaluates the performance of 2 P value combining methods for group sequential trials. The emphasis is on time to event trials although results from less complex trials are also included. The gain or loss in power with the combination method relative to a single statistic is asymmetric in its favor. Depending on the power of each individual test, the combination method can give more power than any single test or give power that is closer to the test with the most power. The versatility of the method is that it can combine P values from different test statistics for analysis at different times. The robustness of...
Source: Pharmaceutical Statistics - December 31, 2016 Category: Statistics Authors: Jitendra Ganju, Yunzhi Lin, Kefei Zhou Tags: MAIN PAPER Source Type: research
Estimands —new statistical principle or the emperor's new clothes?
(Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - December 13, 2016 Category: Statistics Authors: Gerd Rosenkranz Tags: Editorial Source Type: research
Corrections: The disagreeable behaviour of the kappa statistic
(Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - December 1, 2016 Category: Statistics Authors: Laura Flight, Steven A. Julious Tags: CORRIGENDUM Source Type: research
Issue Information
Abstract
No abstract is available for this article. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - November 20, 2016 Category: Statistics Tags: Issue Information Source Type: research
A simulation study of methods for selecting subgroup ‐specific doses in phase 1 trials
We present practical guidelines for application and provide computer programs for trial simulation and conduct. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - October 31, 2016 Category: Statistics Authors: Satoshi Morita, Peter F. Thall, Kentaro Takeda Tags: MAIN PAPER Source Type: research
Analyzing multiple endpoints in a confirmatory randomized clinical trial —an approach that addresses stratification, missing values, baseline imbalance and multiplicity for strictly ordinal outcomes
Confirmatory randomized clinical trials with a stratified design may have ordinal response outcomes, ie, either ordered categories or continuous determinations that are not compatible with an interval scale. Also, multiple endpoints are often collected when 1 single endpoint does not represent the overall efficacy of the treatment. In addition, random baseline imbalances and missing values can add another layer of difficulty in the analysis plan. Therefore, the development of an approach that provides a consolidated strategy to all issues collectively is essential. For a real case example that is from a clinical trial comp...
Source: Pharmaceutical Statistics - October 31, 2016 Category: Statistics Authors: Hengrui Sun, Atsushi Kawaguchi, Gary Koch Tags: MAIN PAPER Source Type: research
Misspecification of at ‐risk periods and distributional assumptions in estimating COPD exacerbation rates: The resultant bias in treatment effect estimation
In trials comparing the rate of chronic obstructive pulmonary disease exacerbation between treatment arms, the rate is typically calculated on the basis of the whole of each patient's follow‐up period. However, the true time a patient is at risk should exclude periods in which an exacerbation episode is occurring, because a patient cannot be at risk of another exacerbation episode until recovered. We used data from two chronic obstructive pulmonary disease randomized controlled trials and compared treatment effect estimates and confidence intervals when using two different definitions of the at‐risk period. Using a sim...
Source: Pharmaceutical Statistics - October 31, 2016 Category: Statistics Authors: M. Law, M.J. Sweeting, G.C. Donaldson, J.A. Wedzicha Tags: MAIN PAPER Source Type: research
Model averaging for treatment effect estimation in subgroups
Abstract
In many clinical trials, biological, pharmacological, or clinical information is used to define candidate subgroups of patients that might have a differential treatment effect. Once the trial results are available, interest will focus on subgroups with an increased treatment effect. Estimating a treatment effect for these groups, together with an adequate uncertainty statement is challenging, owing to the resulting “random high” / selection bias. In this paper, we will investigate Bayesian model averaging to address this problem. The general motivation for the use of model averaging is to realize that subgroup...
Source: Pharmaceutical Statistics - October 31, 2016 Category: Statistics Authors: Bj örn Bornkamp, David Ohlssen, Baldur P. Magnusson, Heinz Schmidli Tags: MAIN PAPER Source Type: research
