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Journal of Biopharmaceutical Statistics

Ariel Alonso, Wim Van Der Elst, Geert Molenberghs, Alvaro J Florez
At the beginning of the 21st century, a new paradigm was introduced for the evaluation of surrogate endpoints based on meta-analysis. In this paradigm, the putative surrogate is assessed at two different levels, the so-called, trial and individual level. Trial level surrogacy is defined as the association between the expected causal treatment effects across different trials populations, whereas the individual level is defined as the association between the surrogate and true endpoints, after adjusting by trial and treatment...
February 16, 2019: Journal of Biopharmaceutical Statistics
Zhenning Yu, Viswanathan Ramakrishnan, Caitlyn Meinzer
Multi-arm multi-stage designs, in which multiple active treatments are compared to a control and accumulated information from interim data are used to add or remove arms from the trial, may reduce development costs and shorten the drug development timeline. As such, this adaptive update is a natural complement to Bayesian methodology in which the prior clinical belief is sequentially updated using the observed probability of success. Simulation is often required for planning clinical trials to accommodate the complexity of the design and to optimize key design characteristics...
February 14, 2019: Journal of Biopharmaceutical Statistics
Charles M Beasley, Brenda Crowe, Mary Nilsson, Lieling Wu, Rebeka Tabbey, Ryan T Hietpas, Robert A Dean, Paul S Horn
The objective of this research was to compute reference limits using reference values from patients entering pharmaceutical development clinical trials by the nonparametric method and the robust method of Horn and Pesce, with and without outlier exclusion, and compare the methods with respect to influence on the limits. Reference limits were computed for 38 analytes with over 130,000 subjects contributing reference values. Subjects were partitioned into 10 demographic strata for limit computation. Limits were computed for both 95- and 98-percentile reference intervals by both methods...
February 13, 2019: Journal of Biopharmaceutical Statistics
Margaret Gamalo-Siebers, Ram Tiwari
Determining whether there are differential treatment effects in subgroups of trial participants remains an important topic in clinical trials as precision medicine becomes ever more relevant. Any assessment of differential treatment effect is predicated on being able to estimate the treatment response accurately while satisfying constraints of balancing the risk of overlooking an important subgroup with the potential to make a decision based on a false discovery. While regression models, such as marginal interaction model, have been widely used to improve accuracy of subgroup parameter estimates by leveraging the relationship between treatment and covariate, there is still a possibility that it can lead to excessively conservative or anti-conservative results...
February 12, 2019: Journal of Biopharmaceutical Statistics
Wentian Guo, Yuan Ji, Daniel Li
To shorten trial duration and improve safety of Phase I trials, we propose R-TPI, a rolling enrollment design that combines the features in model-based designs such as mTPI-2 and rule-based designs such as rolling six. R-TPI employs a novel rolling enrollment scheme, which allows concurrent patient enrollment that is faster than cohort-based enrollment. Bench-marking against rolling six, we find that the R-TPI design is as fast in completing clinical trials but with fewer toxicity events and higher chance of finding the maximum tolerated dose (MTD) in the single scenario laid out in the 2008 rolling six publication...
February 11, 2019: Journal of Biopharmaceutical Statistics
Shrabanti Chowdhury, Ram C Tiwari, Samiran Ghosh
For an existing established drug regimen, active control trials are defacto standard due to ethical reason as well as for clinical equipoise. However, when superiority claim of a new drug against the active control is unlikely to be successful, researchers often address the issue in terms of noninferiority (NI), provided the experimental drug demonstrates the evidence of other benefits beyond efficacy. Such trials aim to demonstrate that an experimental treatment is non-inferior to an existing comparator by not more than a pre-specified margin...
February 11, 2019: Journal of Biopharmaceutical Statistics
Steven Novick, Harry Yang
Parallelism in bioassay is a synonym of similarity between two concentration-response curves. Before the determination of relative potency in bioassays, it is necessary to test for and claim parallelism between the pair of concentration-response curves of reference standard and test sample. Methods for parallelism testing include p-value-based significance tests and interval-based equivalence tests. Most of the latter approaches make statistical inference about the equivalence of parameters of the concentration-response curve models...
February 4, 2019: Journal of Biopharmaceutical Statistics
William Stephen Jones
No abstract text is available yet for this article.
January 29, 2019: Journal of Biopharmaceutical Statistics
Ariel Alonso, Paul Meyvisch, Wim Van der Elst, Geert Molenberghs, Geert Verbeke
Surrogate endpoints need to be statistically evaluated before they can be used as substitutes of true endpoints in clinical studies. However, even though several evaluation methods have been introduced over the last decades, the identification of good surrogate endpoints remains practically and conceptually challenging. In the present work, the question regarding the existence of a good surrogate is addressed using information-theoretic concepts, within a causal-inference framework. The methodology can help practitioners to assess, given a clinically relevant true endpoint and a treatment of interest, the chances of finding a good surrogate endpoint in the first place...
January 26, 2019: Journal of Biopharmaceutical Statistics
Jiacheng Yuan, Jeen Liu, Ray Zhu, Ying Lu, Ulo Palm
This paper deals with the methods to augment concurrent controls (CC) in a randomized controlled trial with available historical data in clinical studies. In their article, Matching with multiple control groups and adjusting for group differences, Stuart and Rubin proposed a matching method where the primary/local control and the secondary/non-local control are both included in the propensity score estimates. The authors discuss a similar approach taking the CC as the primary and the historical control as the secondary, and find that this approach does not save the sample size of the randomized trial compared to the traditional randomized design without supplementation of historical data...
January 6, 2019: Journal of Biopharmaceutical Statistics
Qing Shu Lu, Shein-Chung Chow, Siu-Keung Tse
In clinical trials, where the outcome of interest is the occurrence of an event over a fixed time period, estimation of the event proportion at interim analysis can form a basis for decision-making such as early trial termination, sample size re-estimation, and/or dropping inferior treatment arms. In addition to derivation of mean squared error under an exponential time-to-event distribution, we performed a simulation study to examine the performance of five estimators of the event proportion when time to the event is assessable...
January 1, 2019: Journal of Biopharmaceutical Statistics
Chunhao Tu, Woon Yuen Koh
In this article, we conducted a simulation study to evaluate the performance of five balancing scores using the Analysis of Covariance (ANCOVA) approach, for adjusting bias in estimating average treatment effects (ATE) in observational studies. The five balancing scores which we used as the covariate(s) in the ANCOVA model were (1) propensity score (P), (2) prognostic score (G), (3) propensity score estimated by prognostic score (PG), (4) prognostic score estimated by propensity score (GP), and (5) both propensity and prognostic scores (P&G)...
December 18, 2018: Journal of Biopharmaceutical Statistics
Donglin Yan, Nolan A Wages, Emily V Dressler
In this article, we propose and evaluate three alternative randomization strategies to the adaptive randomization (AR) stage used in a seamless Phase I/II dose-finding design. The original design was proposed by Wages and Tait in 2015 for trials of molecularly targeted agents in cancer treatments, where dose-efficacy assumptions are not always monotonically increasing. Our goal is to improve the design's overall performance regarding the estimation of optimal dose as well as patient allocation to effective treatments...
November 17, 2018: Journal of Biopharmaceutical Statistics
Yu Du, Jun Yin, Daniel J Sargent, Sumithra J Mandrekar
Phase I designs traditionally use the dose-limiting toxicity (DLT), a binary endpoint from the first treatment cycle, to identify the maximum-tolerated dose (MTD) assuming a monotonically increasing relationship between dose and efficacy. In this article, we establish a general framework for a multi-stage adaptive design where we jointly model a continuous efficacy outcome and continuous/quasi-continuous toxicity endpoints from multiple treatment cycles. The normalized Total Toxicity Profile (nTTP) is used as an illustration for quasi-continuous toxicity endpoints, and we replace DLT with nTTP to take into account multiple grades and types of toxicities...
November 7, 2018: Journal of Biopharmaceutical Statistics
Alvaro J Flórez, Geert Molenberghs, Geert Verbeke, Ariel Alonso Abad
Estimating complex linear mixed models using an iterative full maximum likelihood estimator can be cumbersome in some cases. With small and unbalanced datasets, convergence problems are common. Also, for large datasets, iterative procedures can be computationally prohibitive. To overcome these computational issues, an unbiased two-stage closed-form estimator for the multivariate linear mixed model is proposed. It is rooted in pseudo-likelihood-based split-sample methodology and useful, for example, when evaluating normally distributed endpoints in a meta-analytic context...
October 26, 2018: Journal of Biopharmaceutical Statistics
Wei Li, Sophie Yu-Pu Chen, Alan Rong
In randomized controlled trials with delayed treatment effect, there is a delay period before the experimental therapy starts to exhibit a beneficial effect. The phenomenon of delayed treatment effect is often observed in the emerging and important field of immuno-oncology. It is important to estimate the duration of delay as this information helps in characterizing the pattern of comparative treatment effect, understanding the mechanism of action of the experimental therapy, and forming optimal treatment strategies...
October 25, 2018: Journal of Biopharmaceutical Statistics
Yongming Qu, Zhuqing Liu, Haoda Fu, Shanthi Sethuraman, Pandurang M Kulkarni
Dose titration becomes more and more common in improving drug tolerability as well as determining individualized treatment doses, thereby maximizing the benefit to patients. Dose titration starting from a lower dose and gradually increasing to a higher dose enables improved tolerability in patients as the human body may gradually adapt to adverse gastrointestinal effects. Current statistical analyses mostly focus on the outcome at the end-of-study follow-up without considering the longitudinal impact of dose titration on the outcome...
October 25, 2018: Journal of Biopharmaceutical Statistics
Taban Baghfalaki
Longitudinal study designs are commonly applied in much scientific research, especially in the medical, social, and economic sciences. Longitudinal studies allow researchers to measure changes in each individual's responses over time and often have higher statistical power than cross-sectional studies. Choosing an appropriate sample size is a crucial step in a successful study. In longitudinal studies, because of the complexity of their design, including the selection of the number of individuals and the number of repeated measurements, sample size determination is less studied...
October 25, 2018: Journal of Biopharmaceutical Statistics
Chenxue Li, Jinyuan Chen, Gengsheng Qin
In medical diagnostic research, medical tests with continuous values are widely employed to distinguish between diseased and non-diseased subjects. The diagnostic accuracy of a medical test can be assessed by using the receiver operating characteristic (ROC) curve of the test. To summarize the ROC curve and determine an optimal cut-off point for test results, the Youden index is commonly used. In particular, the Youden index is optimized over the entire range of values for sensitivity and specificity, which determine the ROC space...
October 25, 2018: Journal of Biopharmaceutical Statistics
Reid D Landes, Shelly Y Lensing, Martin Hauer-Jensen
The relative potency of one agent to another is commonly represented by the ratio of two quantal response parameters; for example, the LD50 of animals receiving a treatment to the LD50 of control animals, where LD50 is the dose of toxin that is lethal to 50% of animals. Though others have considered interval estimators of LD50 , here, we extend Bayesian, bootstrap, likelihood ratio, Fieller's and Wald's methods to estimate intervals for relative potency in a parallel-line assay context. In addition to comparing their coverage probabilities, we also consider their power in two types of dose designs: one assigning treatment and control the same doses vs...
October 23, 2018: Journal of Biopharmaceutical Statistics
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