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Journal of Biopharmaceutical Statistics

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https://www.readbyqxmd.com/read/28422610/joint-bent-cable-tobit-models-for-longitudinal-and-time-to-event-data
#1
Getachew A Dagne
In this article, we show how to estimate a transition period for the evolvement of drug resistance to antiretroviral (ARV) drug or other related treatments in the framework of developing a Bayesian method for jointly analyzing time to event and longitudinal data. For HIV/AIDS longitudinal data, developmental trajectories of viral loads tend to show a gradual change from a declining trend after initiation of treatment to an increasing trend without an abrupt change. Such characteristics of trajectories are also associated with a time-to-event process...
April 19, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28422566/content-uniformity-testing-for-stratified-samples-via-parametric-tolerance-interval-testing
#2
Steven Novick, Buffy Hudson-Curtis
Historically in the biopharmaceutical setting, USP <905>has been used to establish that a batch of drug product has acceptable content uniformity. More recently, alternative approaches, such as the two one-sided parametric tolerance interval test (PTI-TOST), have been proposed to establish content uniformity. Traditionally, the PTI-TOST is implemented as a sequential, two-tiered test, under the generally accepted assumption that the data are independently and identically distributed. Since the material is sequenced through the manufacturing process over a period of time, there are conceptually arguable locations within each batch, for instance: beginning, middle, and end...
April 19, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28402165/statistical-properties-of-continuous-composite-scales-and-implications-for-drug-development
#3
Hong Liu-Seifert, Scott Andersen, Michael Case, JonDavid Sparks, Karen C Holdridge, Alette M Wessels, Suzanne Hendrix, Paul Aisen, Eric Siemers
Little research has been conducted on the statistical properties of composite measures comprising linear combinations of continuous component scales. We assessed the quantitative relationship between the composites and their individual components regarding their abilities to detect treatment effects. In particular, we developed the mathematical derivation of the treatment effect size of a continuous composite in relation to the treatment effect sizes of its components and proved multiple properties of the composite...
April 12, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28388315/a-simulation-based-sample-size-calculation-method-for-preclinical-tumor-xenograft-experiments
#4
Jianrong Wu, Shengping Yang
Pre-clinical tumor xenograft experiments usually require a small sample size that is rarely greater than 20, and data generated from such experiments very often do not have censored observations. Many statistical tests can be used for analyzing such data, but most of them were developed based on large sample approximation. We demonstrate that the type I error rates of these tests can substantially deviate from the designated rate, especially, when the data to be analyzed has a skewed distribution. Consequently, the sample size calculated based on these tests can be erroneous...
April 7, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28375811/design-of-experiment-for-nonlinear-dynamic-gene-regulatory-network-identification
#5
Tao Lu
The gene regulatory network (GRN) is critical for understanding the regulatory interaction between genes. Time-course microarray experiments provide ample information for constructing GRN. The designs for microarray experiments serve different purposes. However, the experiment design specifically for GRN identification is still sparse. In this article, we use a simulation-based approach to deal with design problems in the framework of nonparametric differential equations. We investigate a number of feasible designs...
April 4, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28375779/statistical-testing-strategies-in-the-health-sciences-edited-by-albert-vexler-et-al
#6
X Daniel Jia
No abstract text is available yet for this article.
April 4, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28281931/incorporation-of-stochastic-engineering-models-as-prior-information-in-bayesian-medical-device-trials
#7
Tarek Haddad, Adam Himes, Laura Thompson, Telba Irony, Rajesh Nair
Evaluation of medical devices via clinical trial is often a necessary step in the process of bringing a new product to market. In recent years, device manufacturers are increasingly using stochastic engineering models during the product development process. These models have the capability to simulate virtual patient outcomes. This article presents a novel method based on the power prior for augmenting a clinical trial using virtual patient data. To properly inform clinical evaluation, the virtual patient model must simulate the clinical outcome of interest, incorporating patient variability, as well as the uncertainty in the engineering model and in its input parameters...
March 10, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28272995/simultaneous-inference-for-semiparametric-mixed-effects-joint-models-with-skew-distribution-and-covariate-measurement-error-for-longitudinal-competing-risks-data-analysis
#8
Tao Lu
Semiparametric mixed-effects joint models are flexible for modeling complex longitudinal-competing risks data. Skew distributions are commonly observed for this type of data. Covariates in the joint models are usually measured with substantial errors. We propose a Bayesian method for semiparametric mixed-effects joint models with covariate measurement errors and skew distribution. The methods are illustrated with AIDS clinical data. Simulation results are conducted to validate the proposed methods.
March 8, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28346083/logistic-regression-likelihood-ratio-test-analysis-for-detecting-signals-of-adverse-events-in-post-market-safety-surveillance
#9
Kijoeng Nam, Nicholas C Henderson, Patricia Rohan, Emily Jane Woo, Estelle Russek-Cohen
The Vaccine Adverse Event Reporting System (VAERS) and other product surveillance systems compile reports of product-associated adverse events (AEs), and these reports may include a wide range of information including age, gender, and concomitant vaccines. Controlling for possible confounding variables such as these is an important task when utilizing surveillance systems to monitor post-market product safety. A common method for handling possible confounders is to compare observed product-AE combinations with adjusted baseline frequencies where the adjustments are made by stratifying on observable characteristics...
March 2, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28340333/the-randomized-crm-an-approach-to-overcoming-the-long-memory-property-of-the-crm
#10
Joseph S Koopmeiners, Andrew Wey
The primary object of a Phase I clinical trial is to determine the maximum tolerated dose (MTD). Typically, the MTD is identified using a dose-escalation study, where initial subjects are treated at the lowest dose level and subsequent subjects are treated at progressively higher dose levels until the MTD is identified. The continual reassessment method (CRM) is a popular model-based dose-escalation design, which utilizes a formal model for the relationship between dose and toxicity to guide dose finding. Recently, it was shown that the CRM has a tendency to get "stuck" on a dose level, with little escalation or de-escalation in the late stages of the trial, due to the long-memory property of the CRM...
March 1, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28375746/an-escalation-for-bivariate-binary-endpoints-controlling-the-risk-of-overtoxicity-ebe-cro-managing-efficacy-and-toxicity-in-early-oncology-clinical-trials
#11
P Colin, M Delattre, P Minini, S Micallef
For about a decade, early clinical development in oncology is facing new challenges. This is due to two main reasons. The first one is linked to the developed molecular targeted agents (MTA) themselves for which the maximum tolerated dose (MTD) is no longer the only dose of interest. The second reason is related to the fact that costs and attrition rates are huge. When selecting a dose, evidence of early activity signal becomes required for future engagements. This implies the need to handle both toxicity and activity endpoints in the analysis and also in the dose escalation design of early-phase trials...
February 21, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28362145/phase-ii-dose-response-trials-a-simulation-study-to-compare-analysis-method-performance-under-design-considerations
#12
Jan Rekowski, Claudia Köllmann, Björn Bornkamp, Katja Ickstadt, André Scherag
Phase II trials are intended to provide information about the dose-response relationship and to support the choice of doses for a pivotal phase III trial. Recently, new analysis methods have been proposed to address these objectives, and guidance is needed to select the most appropriate analysis method in specific situations. We set up a simulation study to evaluate multiple performance measures of one traditional and three more recent dose-finding approaches under four design options and illustrate the investigated analysis methods with an example from clinical practice...
February 21, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28323532/comparing-three-regularization-methods-to-avoid-extreme-allocation-probability-in-response-adaptive-randomization
#13
Yining Du, John D Cook, J Jack Lee
We examine three variations of the regularization methods for response-adaptive randomization (RAR) and compare their operating characteristics. A power transformation (PT) is applied to refine the randomization probability. The clip method is used to bound the randomization probability within specified limits. A burn-in period of equal randomization (ER) can be added before adaptive randomization (AR). For each method, more patients are assigned to the superior arm and overall response rate increase as the scheme approximates simple AR, while statistical power increases as it approximates ER...
February 21, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28328286/identification-of-the-minimum-effective-dose-for-normally-distributed-data-using-a-bayesian-variable-selection-approach
#14
Martin Otava, Ziv Shkedy, Ludwig A Hothorn, Willem Talloen, Daniel Gerhard, Adetayo Kasim
The identification of the minimum effective dose is of high importance in the drug development process. In early stage screening experiments, establishing the minimum effective dose can be translated into a model selection based on information criteria. The presented alternative, Bayesian variable selection approach, allows for selection of the minimum effective dose, while taking into account model uncertainty. The performance of Bayesian variable selection is compared with the generalized order restricted information criterion on two dose-response experiments and through the simulations study...
February 16, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28319455/joint-model-imputation-to-estimate-the-treatment-effect-on-long-term-survival-using-auxiliary-events
#15
Audrey Mauguen, Stefan Michiels, Virginie Rondeau
Clinical trial duration may be a concern in clinical research, especially in cancer trials where the endpoint is overall survival. A surrogate endpoint can be used as an auxiliary variable to analyze the treatment effect earlier. At an early time point, the high number of censored observations can be compensated by the imputation of the unobserved deaths times. We propose to use predictions of the risk of death from a joint model for a recurrent event and a terminal event, which account for disease relapse information...
February 16, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28296567/flexible-parametrization-of-variance-functions-for-quantal-response-data-derived-from-counts
#16
Yuhui Chen, Timothy Hanson
Although the Poisson model has been widely used to fit count data, a well-known drawback is that the Poisson mean equals its variance. Many alternative models for counts that are overdispersed relative to Poisson have been developed to solve this issue, including the negative binomial model. In this article, the negative binomial model with a four-parameter logistic mean is proposed to handle these types of counts, with variance that flexibly depends on the mean. Various parameterizations for the variance are considered, including extra-Poisson variability modeled as an exponentiated B-spline...
February 14, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28324665/assessing-the-prediction-accuracy-of-a-cure-model-for-censored-survival-data-with-long-term-survivors-application-to-breast-cancer-data
#17
Junichi Asano, Akihiro Hirakawa
The Cox proportional hazards cure model is a survival model incorporating a cure rate with the assumption that the population contains both uncured and cured individuals. It contains a logistic regression for the cure rate, and a Cox regression to estimate the hazard for uncured patients. A single predictive model for both the cure and hazard can be developed by using a cure model that simultaneously predicts the cure rate and hazards for uncured patients; however, model selection is a challenge because of the lack of a measure for quantifying the predictive accuracy of a cure model...
February 13, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28319460/power-and-sample-size-for-the-s-t-repeated-measures-design-combined-with-a-linear-mixed-effects-model-allowing-for-missing-data
#18
Toshiro Tango
Tango (Biostatistics 2016) proposed a new repeated measures design called the S:T repeated measures design, combined with generalized linear mixed-effects models and sample size calculations for a test of the average treatment effect that depend not only on the number of subjects but on the number of repeated measures before and after randomization per subject used for analysis. The main advantages of the proposed design combined with the generalized linear mixed-effects models are (1) it can easily handle missing data by applying the likelihood-based ignorable analyses under the missing at random assumption and (2) it may lead to a reduction in sample size compared with the simple pre-post design...
February 13, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28318420/bayesian-penalized-log-likelihood-ratio-approach-for-dose-response-clinical-trial-studies
#19
Yuanyuan Tang, Chunyan Cai, Liangrui Sun, Jianghua He
In literature, there are a few unified approaches to test proof of concept and estimate a target dose, including the multiple comparison procedure using modeling approach, and the permutation approach proposed by Klingenberg. We discuss and compare the operating characteristics of these unified approaches and further develop an alternative approach in a Bayesian framework based on the posterior distribution of a penalized log-likelihood ratio test statistic. Our Bayesian approach is much more flexible to handle linear or nonlinear dose-response relationships and is more efficient than the permutation approach...
February 13, 2017: Journal of Biopharmaceutical Statistics
https://www.readbyqxmd.com/read/28296570/statistical-design-of-noninferiority-multiple-region-clinical-trials-to-assess-global-and-consistent-treatment-effects
#20
Guoqing Diao, Donglin Zeng, Joseph G Ibrahim, Alan Rong, Oliver Lee, Kathy Zhang, Qingxia Chen
Noninferiority multiregional clinical trials (MRCTs) have recently received increasing attention in drug development. While a major goal in an MRCT is to estimate the global treatment effect, it is also important to assess the consistency of treatment effects across multiple regions. In this paper, we propose an intuitive definition of consistency of noninferior treatment effects across regions under the random-effects modeling framework. Specifically, we quantify the consistency of treatment effects by the percentage of regions that meet a predefined treatment margin...
February 13, 2017: Journal of Biopharmaceutical Statistics
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