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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
Pavel Mozgunov, Thomas Jaki, Xavier Paoletti
This work considers Phase I cancer dual-agent dose-escalation clinical trials in which one of the compounds is an immunotherapy. The distinguishing feature of trials considered is that the dose of one agent, referred to as a standard of care, is fixed and another agent is dose-escalated. Conventionally, the goal of a Phase I trial is to find the maximum tolerated combination (MTC). However, in trials involving an immunotherapy, it is also essential to test whether a difference in toxicities associated with the MTC and the standard of care alone is present...
October 23, 2018: Journal of Biopharmaceutical Statistics
Dalong Patrick Huang, Janell Chen, Qianyu Dang, Yi Tsong
A concurrent positive control should be included in a thorough QTc clinical trial to validate the study according to ICH E14 guidance. Some pharmaceutical companies have started to use "hybrid TQT" study to meet ICH E14 regulatory requirements since the release of ICH E14 Q&A (R3). The "hybrid TQT" study includes the same treatment arms (therapeutic and/or supratherapeutic dose of investigational drug, placebo, and positive control) with sample size less than traditional TQT studies, but use concentration-QTc (C-QTc) analysis as primary analysis and assay sensitivity analysis...
October 22, 2018: Journal of Biopharmaceutical Statistics
Lin Wang, Chunpeng Fan
A sample size formula for comparing two groups of count data is derived using the method of moments by matching the first and second moments of the distribution of the count data, and it does not need any further distributional assumption. Compared to sample size formulas derived using a likelihood-based approach or using simulations, the proposed sample size formula applies to count data following any distribution in addition to the negative binomial distribution. The proposed sample size formula can be used even when the study is analyzed with a likelihood-based approach...
July 19, 2018: Journal of Biopharmaceutical Statistics
Tingting Zhuang, Guo-Liang Tian, Chang-Xing Ma
In stratified bilateral studies, responses from two paired body parts are correlated. Confidence intervals (CIs), which reveal various features of the data, should take the correlations into account. In this article, five CI methods (sample-size weighted naïve Maximum likelihood estimation (MLE)-based Wald-type CI, complete MLE-based Wald-type CI, profile likelihood CI, MLE-based score CI and pooled MLE-based Wald-type CI) are derived for proportion ratios under the assumption of equal correlation coefficient within each stratum...
July 16, 2018: Journal of Biopharmaceutical Statistics
Yiyue Lou, Michael P Jones, Wanjie Sun
In clinical endpoint bioequivalence (BE) studies, the primary analysis for assessing equivalence between a generic and an innovator product is based on the observed per-protocol (PP) population (usually completers and compliers). However, missing data and noncompliance are post-randomization intercurrent events and may introduce selection bias. Therefore, PP analysis is generally not causal. The FDA Missing Data Working Group recommended using "causal estimands of primary interest." In this paper, we propose a principal stratification causal framework and co-primary causal estimands to test equivalence, which was also recommended by the recently published ICH E9 (R1) addendum to address intercurrent events...
July 11, 2018: Journal of Biopharmaceutical Statistics
Robin Ristl, Susanne Urach, Gerd Rosenkranz, Martin Posch
While current guidelines generally recommend single endpoints for primary analyses of confirmatory clinical trials, it is recognized that certain settings require inference on multiple endpoints for comprehensive conclusions on treatment effects. Furthermore, combining treatment effect estimates from several outcome measures can increase the statistical power of tests. Such an efficient use of resources is of special relevance for trials in small populations. This paper reviews approaches based on a combination of test statistics or measurements across endpoints as well as multiple testing procedures that allow for confirmatory conclusions on individual endpoints...
July 9, 2018: Journal of Biopharmaceutical Statistics
Nelson T Lu, Yunling Xu, Ying Yang
Noninferiority trials are commonly utilized to evaluate the safety and effectiveness of medical devices. It could happen that the noninferiority hypothesis is rejected while the performance of the active control is clinically not satisfactory. This may pose a great challenge when making a regulatory decision. To avoid such a difficult situation, we propose to conduct a companion test to assess the performance of the active control when testing the main noninferiority hypothesis and to incorporate such a test into the study design...
July 9, 2018: Journal of Biopharmaceutical Statistics
Christy Cassarly, Renee' H Martin, Marc Chimowitz, Edsel A Peña, Viswanathan Ramakrishnan, Yuko Y Palesch
In clinical trials, longitudinally assessed ordinal outcomes are commonly dichotomized and only the final measure is used for primary analysis, partly for ease of clinical interpretation. Dichotomization of the ordinal scale and failure to utilize the repeated measures can reduce statistical power. Additionally, in certain emergent settings, the same measure cannot be assessed at baseline prior to treatment. For such a data set, a piecewise-constant multistate Markov model that incorporates a latent model for the unobserved baseline measure is proposed...
July 9, 2018: Journal of Biopharmaceutical Statistics
Bo Huang, Enayet Talukder, Lixin Han, Pei-Fen Kuan
One of the most critical decision points in clinical development is Go/No-Go decision-making after a proof-of-concept study. Traditional decision-making relies on a formal hypothesis testing with control of type I and type II error rates, which is limited by assessing the strength of efficacy evidence in a small isolated trial. In this article, we propose a quantitative Bayesian/frequentist decision framework for Go/No-Go criteria and sample size evaluation in Phase II randomized studies with a time-to-event endpoint...
July 3, 2018: Journal of Biopharmaceutical Statistics
Elahe Tashakor, Vernon M Chinchilli
In many clinical studies, Lin's (1989) concordance correlation coefficient (CCC) is a popular measure of agreement for continuous outcomes. Most commonly, it is used under the assumption that data are normally distributed. However, in many practical applications, data are often skewed and/or thick-tailed. King and Chinchilli (2001) proposed robust estimation methods of alternative CCC indices, and we propose an approach that extends the existing methods of robust estimators by focusing on functionals that yield robust L-statistics...
June 28, 2018: Journal of Biopharmaceutical Statistics
Dan Wang, Yingdong Feng, Kristopher Attwood, Lili Tian
Receiver operating characteristic (ROC) curve is a popular tool for evaluating diagnostic accuracy of biomarkers. In ROC framework, there exist several optimal threshold selection methods for binary classification. For diseases with multi-classes, an important category of scenarios is tree or umbrella ordering in which the marker measurement for one particular class is lower or higher than those for the rest classes. Tree or umbrella ordering has important clinical applications, especially in the molecular diagnostics of cancer subtypes...
June 25, 2018: Journal of Biopharmaceutical Statistics
Karl K Lin, Mohammad A Rahman
Interest has been expressed in using a joint test procedure that requires that the results of both a trend test and a pairwise comparison test between the control and the high groups be statistically significant simultaneously at the levels of significance recommended in the FDA 2001 draft guidance for industry document for the separate tests in order for the drug effect on the development of an individual tumor type to be considered as statistically significant. Results of our simulation studies show that there is a serious consequence of large inflations of the false negative rate through large decreases of false positive rate in the use of the above joint test procedure in the final interpretation of the carcinogenicity potential of a new drug if the levels of significance recommended for separate tests are used...
May 21, 2018: Journal of Biopharmaceutical Statistics
M A Montero-Alonso, J A Roldán-Nofuentes
The classic parameters used to assess the accuracy of a binary diagnostic test (BDT) are sensitivity and specificity. Other parameters used to describe the performance of a BDT are likelihood ratios (LRs). The LRs depend on the sensitivity and the specificity of the diagnostic test, and they reflect how much greater the probability of a positive or negative diagnostic test result for individuals with the disease than that for the individuals without the disease. In this study, several confidence intervals are studied for the LRs of a BDT in the presence of missing data...
March 27, 2018: Journal of Biopharmaceutical Statistics
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