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Journal of Biopharmaceutical Statistics

Md Abu Manju, Edwin R Van Den Heuvel, Pieta C IJzerman-Boon
The detection proportion of a qualitative microbiological test method is the probability to detect a single micro-organism. A general expression for the moment estimator of the detection proportion is provided. It depends on the distribution of the spikes used in a validation study through its moment-generating function. Several forms of spiking experiments are compared on their estimation performance using simulations and assuming a generalized Poisson distribution (GPD) for the spikes. The optimal design, which minimizes the mean squared error of our proposed moment estimator, depends on the dispersion parameter of the GPD...
March 19, 2018: Journal of Biopharmaceutical Statistics
Guogen Shan, Hua Zhang, Tao Jiang
To compare a new binary diagnostic test with the gold standard, sensitivity and specificity are the two common measurements used to evaluate the new test. When not all the patients are verified by the gold standard due to time, budget, or cost considerations, several approaches have been proposed to compute sample size for such studies under the assumption of missing completely at random. However, the majority of them are based on asymptotic approaches that generally do not guarantee the type I and II error rates, and the remaining approaches use exact binomial distributions in sample size calculation but only the verified samples are used...
March 19, 2018: Journal of Biopharmaceutical Statistics
Lucy Kerns
In risk assessment, it is often desired to make inferences on the risk at certain low doses or on the dose(s) at which a specific benchmark risk (BMR) is attained. At times, [Formula: see text] dose levels or BMRs are of interest, and some form of multiplicity adjustment is necessary to ensure a valid [Formula: see text] simultaneous inference. Bonferroni correction is often employed in practice for such purposes. Though relative simple to implement, the Bonferroni strategy can suffer from extreme conservatism (Nitcheva et al...
March 15, 2018: Journal of Biopharmaceutical Statistics
Yi Zhao, Yu-Wei Chang, Shein-Chung Chow
For approval of biosimilar products, the U.S. Food and Drug Administration (FDA) recommends a stepwise approach for obtaining the totality-of-the-evidence for assessing biosimilarirty between a proposed biosimilar product and its corresponding innovative (reference) biologic product. The stepwise approach starts with the assessment of analytical similarity of critical quality attributes (CQAs) for structural/physicochemical and functional properties in the manufacturing process of biosimilar products. For Tier 1 CQAs which are most relevant to clinical outcomes, the FDA recommends an equivalence test be performed for similarity assessment based on an equivalence acceptance criterion (EAC)...
March 7, 2018: Journal of Biopharmaceutical Statistics
Ying-Ying Zhang, Naitee Ting
When Phase III treatment effect is diluted from what was observed from Phase II results, we propose to determine the Bayesian sample size for a Phase III clinical trial based on the normal, uniform, and truncated normal prior distributions of the treatment effects on an interval, which starts from an acceptable treatment effect to the observed treatment effect from Phase II. After incorporating the prior information of the treatment effects, the Bayesian sample size is the number of patients of the Phase III trial for a given Bayesian Predictive Power (BPP) or Bayesian Historical Predictive Power (BHPP)...
March 7, 2018: Journal of Biopharmaceutical Statistics
Atanu Biswas, Rahul Bhattacharya, Soumyadeep Das
A two treatment response adaptive design is developed for phase III clinical trials with ordinal categorical treatment outcome using Goodman-Kruskal measure of association. Properties of the proposed design are studied both empirically and theoretically and the acceptability is further illustrated using two real data-sets; one from a clinical trial with trauma patients and the other from a trial with patients having rheumatoid arthritis.
March 5, 2018: Journal of Biopharmaceutical Statistics
Zhishen Ye, B Nebiyou Bekele
Mixed Effects Models for Repeated Measures (MMRM) is often used in clinical trials with longitudinal data. However, there has not been an in-depth examination available on how investigators can implement interim analysis while also controlling the overall alpha for clinical trials under an MMRM analysis framework. Statistical independence among measurements, which is often assumed in group sequential testing (GST), is not valid under an MMRM framework due to the correlations induced by longitudinal within-subject measurements...
February 20, 2018: Journal of Biopharmaceutical Statistics
Kung-Jong Lui, Lixia Zhu
Using Prescott's model-free approach, we develop an asymptotic procedure and an exact procedure for testing equality between treatments with binary responses under an incomplete block crossover design. We employ Monte Carlo simulation and note that these test procedures can not only perform well in small-sample cases but also outperform the corresponding test procedures accounting for only patients with discordant responses published elsewhere. We use the data taken as a part of the crossover trial comparing two different doses of an analgesic with placebo for the relief of primary dysmenorrhea to illustrate the use of test procedures discussed here...
February 16, 2018: Journal of Biopharmaceutical Statistics
Annalisa V Piccorelli, Sarah A Fraker
During a clinical trial, balancing statistical and ethical considerations are important. Response-adaptive randomization methods use the information from past patients to increase the probability of the next patient receiving the better treatment while avoiding the statistical concern of selection bias. We compared three response-adaptive randomization urn designs, Randomized Play-the-Winner, Modified Play-the-Winner, and Birth-and-Death Urn with Immigration, to the traditional equal allocation design with respect to power and allocation of patients to the better treatment...
February 14, 2018: Journal of Biopharmaceutical Statistics
Guoqing Diao, Jun Dong, Donglin Zeng, Chunlei Ke, Alan Rong, Joseph G Ibrahim
Due to the importance of precision medicine, it is essential to identify the right patients for the right treatment. Biomarkers, which have been commonly used in clinical research as well as in clinical practice, can facilitate selection of patients with a good response to the treatment. In this paper, we describe a biomarker threshold adaptive design with survival endpoints. In the first stage, we determine subgroups for one or more biomarkers such that patients in these subgroups benefit the most from the new treatment...
February 13, 2018: Journal of Biopharmaceutical Statistics
Mohsen Salehi, Adel Mohammadpour, Mohammad Mohammadi, Mina Aminghafari
Nowadays, performing simultaneous hypothesis testing under small sample sizes in large-scale features has received unprecedented attention in practice. Traditional approaches are not appropriate for this purpose. Instead, a novel approach which is based on the null statistic is used in the literature. The null statistic approach, using the permutation samples of all features, permits the more accurate estimation of the [Formula: see text]-value for a target feature. However, the known methods, working based on the null statistic, cannot be applied to features with three or more levels...
February 12, 2018: Journal of Biopharmaceutical Statistics
Fumiya Shimamura, Chikuma Hamada, Shigeyuki Matsui, Akihiro Hirakawa
In Phase I/II trials for a combination therapy of two agents, we ideally want to explore as many dose combinations as possible with limited sample size in Phase I and to reduce the number of untried dose combinations before moving to Phase II. Efficient collection of toxicity data in Phase I would eventually improve the accuracy of optimal dose combination identification in Phase II. In this paper, we develop a novel dose-finding method based on efficacy and toxicity outcomes for two-agent combination Phase I/II trials...
February 8, 2018: Journal of Biopharmaceutical Statistics
Fumihiro Takahashi, Satoshi Morita
Phase II clinical trials are conducted to determine the optimal dose of the study drug for use in Phase III clinical trials while also balancing efficacy and safety. In conducting these trials, it may be important to consider subpopulations of patients grouped by background factors such as drug metabolism and kidney and liver function. Determining the optimal dose, as well as maximizing the effectiveness of the study drug by analyzing patient subpopulations, requires a complex decision-making process. In extreme cases, drug development has to be terminated due to inadequate efficacy or severe toxicity...
February 8, 2018: Journal of Biopharmaceutical Statistics
Liesbeth Bruckers, Geert Molenberghs, Bianca Pulinx, Femina Hellenthal, Geert Schurink
Degeneration of the aortic wall becomes life-threatening when the risk of rupture increases. Cluster analysis on repeated measures of the diameter of the artery revealed two subgroups of patients included in a surveillance program. These results were obtained under the assumption of missingness at random. In this article, we study the vulnerability of the cluster analysis results - the estimated trajectories and the posterior membership probabilities - by applying different missing-data models for non-ignorable dropout, as proposed by Muthen et al...
January 29, 2018: Journal of Biopharmaceutical Statistics
Chia-Min Chen, Yunchan Chi, Hsing-Ming Chang
In phase II clinical trials, patients are recruited sequentially and consequently the time required to complete the clinical trial will become long if the accrual rate is low. To speed up the drug development process and account for ethical issues, stochastically and non-stochastically curtailed two-stage designs have been proposed in single-arm phase II clinical trials. More recently, randomized phase II clinical trials are being increasingly recommended to avoid biased evaluation of the treatment effect when compared with a historical control...
January 22, 2018: Journal of Biopharmaceutical Statistics
Shaowu Tang, Parichehr Hemyari, Jesse A Canchola, John Duncan
A main challenge in molecular diagnostic research is to accurately evaluate the performance of a new nucleic acid amplification test when the reference standard is imperfect. Several approaches, such as discrepant analysis, composite reference standard (CRS) method, or latent class analysis (LCA), are commonly applied for this purpose by combining multiple imperfect (reference) test results. In discrepant analysis or LCA, test results from the new assay are often involved in the construction of a new pseudo-reference standard, which results in the potential risk of overestimating the parameters of interest...
January 22, 2018: 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
Marlina D Nasution, Xiaofei Wang
No abstract text is available yet for this article.
2018: Journal of Biopharmaceutical Statistics
Steven Sun
No abstract text is available yet for this article.
2018: Journal of Biopharmaceutical Statistics
Alex Dmitrienko
No abstract text is available yet for this article.
2018: Journal of Biopharmaceutical Statistics
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