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Journal of Biopharmaceutical Statistics

George Kordzakhia, Alex Dmitrienko, Eiji Ishida
Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to "multivariate" multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach...
December 28, 2017: Journal of Biopharmaceutical Statistics
Tao Lu, Minggen Lu, Min Wang, Jun Zhang, Guang-Hui Dong
Longitudinal competing risks data frequently arise in clinical studies. Skewness and missingness are commonly observed for these data in practice. However, most joint models do not account for these data features (Huang et al., 2010; Lu et al., 2016; Tang et al., 2017b). In this article, we propose partially linear mixed-effects joint models to analyze skew longitudinal competing risks data with missingness. In particular, to account for skewness, we replace the commonly assumed symmetric distributions by asymmetric distribution for model errors...
December 18, 2017: Journal of Biopharmaceutical Statistics
George Kordzakhia, Thomas Brechenmacher, Eiji Ishida, Alex Dmitrienko, Winston Wenxiang Zheng, David Fuyuan Li
It is increasingly common to encounter complex multiplicity problems with several multiplicity components in confirmatory Phase III clinical trials. These components are often based on several endpoints (primary and secondary endpoints) and several dose-control comparisons. When constructing a multiplicity adjustment in these settings, it is important to control the Type I error rate over all multiplicity components. An important class of multiple testing procedures, known as gatekeeping procedures, was derived using the mixture method that enables clinical trial sponsors to set up efficient multiplicity adjustments that account for clinically relevant logical relationships among the hypotheses of interest...
December 14, 2017: Journal of Biopharmaceutical Statistics
Hyang Kim, Greg Cable
Assessing treatment effectiveness in longitudinal data can be complex when treatments are not randomly assigned and patients are allowed to switch treatment to other or no treatment, often in a manner that is driven by changes in one or more variables associated with patient or clinical characteristics. There can be confounding of the treatment effect from a time-varying variable, i.e., one which is affected by previous exposure and can in turn also influence subsequent treatment changes. Precision medicine relies on validated biomarkers to better classify patients by their probable response to treatment...
December 4, 2017: Journal of Biopharmaceutical Statistics
Sin-Ho Jung, Ho Yun Lee, Shein-Chung Chow
We investigate the survival distribution of the patients who have survived over a certain time period. This is called a conditional survival distribution. In this paper, we show that one-sample estimation, two-sample comparison and regression analysis of conditional survival distributions can be conducted using the regular methods for unconditional survival distributions that are provided by the standard statistical software, such as SAS and SPSS. We conduct extensive simulations to evaluate the finite sample property of these conditional survival analysis methods...
November 29, 2017: Journal of Biopharmaceutical Statistics
Lisa Ying, Fuyu Song, Shein-Chung Chow, Na Zeng, Jiayin Zheng, Xiaodong Li, David Henry, Venkat Sethuraman
In recent years, multi-regional clinical trials (MRCT) that conduct clinical trials simultaneously in Asian Pacific region, Europe, and the United States have become very popular for global pharmaceutical development. The main purpose of multi-regional clinical trials is to shorten the time for pharmaceutical development and regulatory submission, and approval around the world. In practice, however, clinical results observed from some regions (sub-population) may not be consistent with the results from other regions and/or all regions combined (entire population)...
November 28, 2017: Journal of Biopharmaceutical Statistics
Donglin Zeng, Jean Pan, Kuolung Hu, Eric Chi, D Y Lin
To improve patients' access to safe and effective biological medicines, abbreviated licensure pathways for biosimilar and interchangeable biological products have been established in the US, Europe, and other countries around the world. The US Food and Drug Administration and European Medicines Agency have published various guidance documents on the development and approval of biosimilars, which recommend a "totality-of-the-evidence" approach with a stepwise process to demonstrate biosimilarity. The approach relies on comprehensive comparability studies ranging from analytical and nonclinical studies to clinical pharmacokinetic/pharmacodynamic (PK/PD) and efficacy studies...
November 27, 2017: Journal of Biopharmaceutical Statistics
Ilya Lipkovich, Alex Dmitrienko, Christoph Muysers, Bohdana Ratitch
The general topic of subgroup identification has attracted much attention in the clinical trial literature due to its important role in the development of tailored therapies and personalized medicine. Subgroup search methods are commonly used in late-phase clinical trials to identify subsets of the trial population with certain desirable characteristics. Post-hoc or exploratory subgroup exploration has been criticized for being extremely unreliable. Principled approaches to exploratory subgroup analysis based on recent advances in machine learning and data mining have been developed to address this criticism...
November 27, 2017: Journal of Biopharmaceutical Statistics
Kalyan Das, Subrata Rana, Surupa Roy
In clinical trials, patient's disease severity is usually assessed on a Likert-type scale. Patients, however, may miss one or more follow-up visits (non-monotone missing). The statistical analysis of non-Gaussian longitudinal data with non-monotone missingness is difficult to handle, particularly when both response and time-dependent covariates are subject to such missingness. Even when the number of patients with intermittent missing data is small, ignoring those patients from analysis seems to be unsatisfactory...
November 27, 2017: Journal of Biopharmaceutical Statistics
Mohammad Huque, Thamban Valappil, Mohamed Alosh
Noninferiority (NI) clinical trials are designed to demonstrate that a new treatment is not unacceptably worse than an active control on a clinically meaningful endpoint. While such an endpoint can be of any type, the focus of this manuscript is on the binary-type endpoint. Examples of this endpoint can be clinical cure endpoint for patients with bacterial diseases or based on a pre-specified virological threshold for viral diseases. However, in addition to assessing such a binary endpoint for the NI comparison, the trial may also evaluate a second clinically relevant endpoint for providing additional support to the evidence of the designated primary endpoint...
November 27, 2017: Journal of Biopharmaceutical Statistics
Tim Holland-Letz, Nikolas Gunkel, Eberhard Amtmann, Annette Kopp-Schneider
In toxicology and related areas, interaction effects between two substances are commonly expressed through a combination index [Formula: see text] evaluated separately at different effect levels and mixture ratios. Often, these indices are combined into a graphical representation, the isobologram. Instead of estimating the combination indices at the experimental mixture ratios only, we propose a simple parametric model for estimating the underlying interaction function. We integrate this approach into a joint model where both the parameters of the dose-response functions of the singular substances and the interaction parameters can be estimated simultaneously...
November 27, 2017: Journal of Biopharmaceutical Statistics
Weidong Zhang, Jing Wang, Sandeep Menon
Precision medicine has been a hot topic in drug development over the last decade. Biomarkers have been proven useful for understanding the disease progression and treatment response in precision medicine development. Advancement of high-throughput omics technologies has enabled fast identification of molecular biomarkers with low cost. Although biomarkers have brought many promises to drug development, steep challenges arise due to a large amount of data, complexity of technology, and lack of full understanding of biology...
November 27, 2017: Journal of Biopharmaceutical Statistics
J A Roldán-Nofuentes, R M Amro
The combination of two binary diagnostic tests in order to increase the accuracy of the diagnosis of a disease is a frequent procedure in clinical practice. When considering the losses associated with an erroneous classification with a binary diagnostic test, the parameter that is used to assess the diagnostic test is the weighted kappa coefficient. The weighted kappa coefficient depends on the sensitivity and the specificity of the diagnostic test, on the disease prevalence and on the weighting index. In this article, we study the combination of the weighted kappa coefficients of two binary diagnostic tests, defining the parameters and studying the conditions under which the combination of the two diagnostic tests increases the value of the weighted kappa coefficient of the combination...
November 27, 2017: Journal of Biopharmaceutical Statistics
Gaohong Dong, Junshan Qiu, Duolao Wang, Marc Vandemeulebroecke
The win ratio was first proposed in 2012 by Pocock and his colleagues to analyze a composite endpoint while considering the clinical importance order and the relative timing of its components. It has attracted considerable attention since then, in applications as well as methodology. It is not uncommon that some clinical trials require a stratified analysis. In this article, we propose a stratified win ratio statistic in a similar way as the Mantel-Haenszel stratified odds ratio, derive a general form of its variance estimator with a plug-in of existing or potentially new variance/covariance estimators of the number of wins for the two treatment groups, and assess its statistical performance using simulation studies...
November 27, 2017: Journal of Biopharmaceutical Statistics
Wei Jiang, Jo A Wick, Jianghua He, Jonathan D Mahnken, Matthew S Mayo
Frequentist design for two-arm randomized Phase II clinical trials with outcomes from the exponential dispersion family was proposed previously, where the total sample sizes are minimized under multiple constraints on the standard errors of the estimated group means and their difference. This design was generalized from an approach specific for dichotomous outcomes. The two previous approaches measure the central tendency of each group and treatment effect based on mean and difference in means. Other measures such as median or hazard ratio are more appropriate under certain situations...
November 27, 2017: Journal of Biopharmaceutical Statistics
Gautier Paux, Alex Dmitrienko
Given the importance of addressing multiplicity issues in confirmatory clinical trials, several recent publications focused on the general goal of identifying most appropriate methods for multiplicity adjustment in each individual setting. This goal can be accomplished using the Clinical Scenario Evaluation approach. This approach encourages trial sponsors to perform comprehensive assessments of applicable analysis strategies such as multiplicity adjustments under all plausible sets of statistical assumptions using relevant evaluation criteria...
November 27, 2017: Journal of Biopharmaceutical Statistics
Victoria Landsman, Mark Fillery, Howard Vernon, Heejung Bang
Blinding is a critical component in randomized clinical trials along with treatment effect estimation and comparisons between the treatments. Various methods have been proposed for the statistical analyses of blinding-related data, but there is little guidance for determining the sample size for this type of data, especially if blinding assessment is done in pilot studies. In this paper, we try to fill this gap and provide simple methods to address sample size calculations for a "new" study with different research questions and scenarios...
November 20, 2017: Journal of Biopharmaceutical Statistics
Hojin Moon, Yuan Zhao, Dustin Pluta, Hongshik Ahn
In treating patients diagnosed with early Stage I non-small-cell lung cancer (NSCLC), doctors must choose surgery alone, Adjuvant Cisplatin-Based Chemotherapy (ACT) alone or both. For patients with resected stages IB to IIIA, clinical trials have shown a survival advantage from 4-15% with the adoption of ACT. However, due to the inherent toxicity of chemotherapy, it is necessary for doctors to identify patients whose chance of success with ACT is sufficient to justify the risks. This research seeks to use gene expression profiling in the development of a statistical decision-making algorithm to identify patients whose survival rates will improve from ACT treatment...
November 20, 2017: Journal of Biopharmaceutical Statistics
Xiaofeng Zhou, Warren Bao, Mike Gaffney, Rongjun Shen, Sarah Young, Andrew Bate
The routine use of sequential methods is well established in clinical studies. Recently, there has been increasing interest in applying these methods to prospectively monitor the safety of newly approved drugs through accrual of real-world data. However, the application to marketed drugs using real-world data has been limited and work is needed to determine which sequential approaches are most suited to such data. In this study, the conditional sequential sampling procedure (CSSP), a group sequential method, was compared with a log-linear model with Poisson distribution (LLMP) through a SAS procedure (PROC GENMOD) combined with an alpha-spending function on two large longitudinal US administrative health claims databases...
November 20, 2017: Journal of Biopharmaceutical Statistics
Changyu Shen, Xiaochun Li
Results of industry-sponsored Phase III trials registered at include a rich amount of information on the efficacy of medical interventions. We propose that these results can be used to inform hypothesis testing of a new intervention through the Bayes principle. The posterior probability of positive efficacy offers an accessible interpretation of the uncertainty of efficacy and a convenient metric for global false-positive control.
November 20, 2017: Journal of Biopharmaceutical Statistics
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