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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
Getachew A Dagne
The major limitations of growth curve mixture models for HIV/AIDS data are the usual assumptions of normality and monophasic curves within latent classes. This article addresses these limitations by using non-normal skewed distributions and multiphasic patterns for outcomes of prospective studies. For such outcomes, new skew-t (ST) distributions are proposed for modeling heterogeneous growth trajectories, which exhibit not abrupt but gradual multiphasic changes from a declining trend to an increasing trend over time...
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
María Álvarez Hernández, Antonio Martín Andrés, Inmaculada Herranz Tejedor
Two-tailed asymptotic inferences for the difference d = p2  - p1 with independent proportions have been widely studied in the literature. Nevertheless, the case of one tail has received less attention, despite its great practical importance (superiority studies and noninferiority studies). This paper assesses 97 methods to make these inferences (test and confidence intervals [CIs]), although it also alludes to many others. The conclusions obtained are (1) the optimal method in general (and particularly for errors α = 1% and 5%) is based on arcsine transformation, with the maximum likelihood estimator restricted to the null hypothesis and increasing the successes and failures by 3/8; (2) the optimal method for α = 10% is a modification of the classic model of Peskun; (3) a more simple and acceptable option for large sample sizes and values of d not near to ±1 is the classic method of Peskun; and (4) in the particular case of the superiority and inferiority tests, the optimal method is the classic Wald method (with continuity correction) when the successes and failures are increased by one...
April 2, 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
Andrea Ghiglietti, Maria Giovanna Scarale, Rosalba Miceli, Francesca Ieva, Luigi Mariani, Cecilia Gavazzi, Anna Maria Paganoni, Valeria Edefonti
Recently, response-adaptive designs have been proposed in randomized clinical trials to achieve ethical and/or cost advantages by using sequential accrual information collected during the trial to dynamically update the probabilities of treatment assignments. In this context, urn models-where the probability to assign patients to treatments is interpreted as the proportion of balls of different colors available in a virtual urn-have been used as response-adaptive randomization rules. We propose the use of Randomly Reinforced Urn (RRU) models in a simulation study based on a published randomized clinical trial on the efficacy of home enteral nutrition in cancer patients after major gastrointestinal surgery...
March 22, 2018: 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
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