Α Markov model for longitudinal studies with incomplete dichotomous outcomes
Missing outcome data constitute a serious threat to the validity and precision of inferences from randomized controlled trials. In this paper, we propose the use of a multistate Markov model for the analysis of incomplete individual patient data for a dichotomous outcome reported over a period of time. The model accounts for patients dropping out of the study and also for patients relapsing. The time of each observation is accounted for, and the model allows the estimation of time‐dependent relative treatment effects. We apply our methods to data from a study comparing the effectiveness of 2 pharmacological treatments fo...
Source: Pharmaceutical Statistics - October 31, 2016 Category: Statistics Authors: Orestis Efthimiou, Nicky Welton, Myrto Samara, Stefan Leucht, Georgia Salanti, Tags: MAIN PAPER Source Type: research
Disentangling estimands and the intention ‐to‐treat principle
Randomized controlled trials (RCTs) aim at providing reliable estimates of treatment benefit. Missing data and nonadherence to treatment are distinct problems that can substantially impede this task. In practice, the fact that the handling of missing data due to nonadherence affects the question that is addressed is often ignored. Estimands allow precisely predefining the question of interest. Estimands are definitions of that which is being estimated with regard to population, endpoint, and handling of postrandomization events (eg, nonadherence). Depending on the situation, different estimands are of relevance. Therefore,...
Source: Pharmaceutical Statistics - October 31, 2016 Category: Statistics Authors: Ann ‐Kristin Leuchs, Andreas Brandt, Jörg Zinserling, Norbert Benda Tags: SPECIAL ISSUE PAPER Source Type: research
Application of Bayesian hierarchical models for phase I/II clinical trials in oncology
Treatment during cancer clinical trials sometimes involves the combination of multiple drugs. In addition, in recent years there has been a trend toward phase I/II trials in which a phase I and a phase II trial are combined into a single trial to accelerate drug development. Methods for the seamless combination of phases I and II parts are currently under investigation. In the phase II part, adaptive randomization on the basis of patient efficacy outcomes allocates more patients to the dose combinations considered to have higher efficacy. Patient toxicity outcomes are used for determining admissibility to each dose combina...
Source: Pharmaceutical Statistics - October 31, 2016 Category: Statistics Authors: Shinjo Yada, Chikuma Hamada Tags: MAIN PAPER Source Type: research
Some practical considerations in three ‐arm non‐inferiority trial design
Non‐inferiority trials aim to demonstrate whether an experimental therapy is not unacceptably worse than an active reference therapy already in use. When applicable, a three‐arm non‐inferiority trial, including an experiment therapy, an active reference therapy, and a placebo, is often recommended to assess assay sensitivity and internal validity of a trial. In this paper, we share some practical considerations based on our experience from a phase III three‐arm non‐inferiority trial. First, we discuss the determination of the total sample size and its optimal allocation based on the overall power of the non‐inf...
Source: Pharmaceutical Statistics - September 28, 2016 Category: Statistics Authors: Ming Zhou, Sudeep Kundu Tags: Main Paper Source Type: research
Issue Information
Abstract
No abstract is available for this article. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - September 15, 2016 Category: Statistics Tags: Issue Information Source Type: research
A novel sample size formula for the weighted log ‐rank test under the proportional hazards cure model
The treatment of cancer has progressed dramatically in recent decades, such that it is no longer uncommon to see a cure or log‐term survival in a significant proportion of patients with various types of cancer. To adequately account for the cure fraction when designing clinical trials, the cure models should be used. In this article, a sample size formula for the weighted log‐rank test is derived under the fixed alternative hypothesis for the proportional hazards cure models. Simulation showed that the proposed sample size formula provides an accurate estimation of sample size for designing clinical trials under the pr...
Source: Pharmaceutical Statistics - August 31, 2016 Category: Statistics Authors: Xiaoping Xiong, Jianrong Wu Tags: MAIN PAPER Source Type: research
Proposed best practice for projects that involve modelling and simulation
Modelling and simulation has been used in many ways when developing new treatments. To be useful and credible, it is generally agreed that modelling and simulation should be undertaken according to some kind of best practice. A number of authors have suggested elements required for best practice in modelling and simulation. Elements that have been suggested include the pre‐specification of goals, assumptions, methods, and outputs. However, a project that involves modelling and simulation could be simple or complex and could be of relatively low or high importance to the project. It has been argued that the level of detai...
Source: Pharmaceutical Statistics - August 31, 2016 Category: Statistics Authors: O'Kelly M, Anisimov V, Campbell C, Hamilton S Tags: MAIN PAPER Source Type: research
Accounting for uncertainty in the historical response rate of the standard treatment in single ‐arm two‐stage designs based on Bayesian power functions
In phase II single‐arm studies, the response rate of the experimental treatment is typically compared with a fixed target value that should ideally represent the true response rate for the standard of care therapy. Generally, this target value is estimated through previous data, but the inherent variability in the historical response rate is not taken into account. In this paper, we present a Bayesian procedure to construct single‐arm two‐stage designs that allows to incorporate uncertainty in the response rate of the standard treatment. In both stages, the sample size determination criterion is based on the concepts...
Source: Pharmaceutical Statistics - August 31, 2016 Category: Statistics Authors: Francesca Matano, Valeria Sambucini Tags: Main Paper Source Type: research
Response ‐adaptive clinical trials: case studies in the medical literature
We describe some statistical details underlying the designs, but our main focus is to describe and comment on ADs from the medical research literature. Copyright © 2016 John Wiley & Sons, Ltd. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - August 31, 2016 Category: Statistics Authors: Andrew P. Grieve Tags: Main Paper Source Type: research
Estimating the reliability of repeatedly measured endpoints based on linear mixed ‐effects models. A tutorial
There are various settings in which researchers are interested in the assessment of the correlation between repeated measurements that are taken within the same subject (i.e., reliability). For example, the same rating scale may be used to assess the symptom severity of the same patients by multiple physicians, or the same outcome may be measured repeatedly over time in the same patients.
Reliability can be estimated in various ways, for example, using the classical Pearson correlation or the intra‐class correlation in clustered data. However, contemporary data often have a complex structure that goes well beyond the res...
Source: Pharmaceutical Statistics - August 31, 2016 Category: Statistics Authors: Wim Van der Elst, Geert Molenberghs, Ralf ‐Dieter Hilgers, Geert Verbeke, Nicole Heussen Tags: Main Paper Source Type: research
A comparison of five approaches to decision ‐making for a first clinical trial of efficacy
The first trial of clinical efficacy is an important step in the development of a compound. Such a trial gives the first indication of whether a compound is likely to have the efficacy needed to be successful. Good decisions dictate that good compounds have a large probability of being progressed and poor compounds have a large probability of being stopped. In this paper, we consider and contrast five approaches to decision‐making that have been used. To illustrate the use of the five approaches, we conduct a comparison for two plausible scenarios with associated assumptions for sample sizing. The comparison shows some l...
Source: Pharmaceutical Statistics - August 31, 2016 Category: Statistics Authors: Simon Kirby, Christy Chuang ‐Stein Tags: Main Paper Source Type: research
Implementation of pattern ‐mixture models in randomized clinical trials
Modern analysis of incomplete longitudinal outcomes involves formulating assumptions about the missingness mechanisms and then using a statistical method that produces valid inferences under this assumption. In this manuscript, we define missingness strategies for analyzing randomized clinical trials (RCTs) based on plausible clinical scenarios. Penalties for dropout are also introduced in an attempt to balance benefits against risks. Some missingness mechanisms are assumed to be non‐future dependent, which is a subclass of missing not at random. Non‐future dependent stipulates that missingness depends on the past and ...
Source: Pharmaceutical Statistics - August 31, 2016 Category: Statistics Authors: P. Bunouf, G. Molenberghs Tags: Main Paper Source Type: research
On logistic regression analysis of dichotomized responses
We study the properties of treatment effect estimate in terms of odds ratio at the study end point from logistic regression model adjusting for the baseline value when the underlying continuous repeated measurements follow a multivariate normal distribution. Compared with the analysis that does not adjust for the baseline value, the adjusted analysis produces a larger treatment effect as well as a larger standard error. However, the increase in standard error is more than offset by the increase in treatment effect so that the adjusted analysis is more powerful than the unadjusted analysis for detecting the treatment effect...
Source: Pharmaceutical Statistics - August 31, 2016 Category: Statistics Authors: Kaifeng Lu Tags: Main Paper Source Type: research
Effect of correlation on covariate selection in linear and nonlinear mixed effect models
The effect of correlation among covariates on covariate selection was examined with linear and nonlinear mixed effect models. Demographic covariates were extracted from the National Health and Nutrition Examination Survey III database. Concentration‐time profiles were Monte Carlo simulated where only one covariate affected apparent oral clearance (CL/F). A series of univariate covariate population pharmacokinetic models was fit to the data and compared with the reduced model without covariate. The “best” covariate was identified using either the likelihood ratio test statistic or AIC. Weight and body surface area (ca...
Source: Pharmaceutical Statistics - August 31, 2016 Category: Statistics Authors: Peter L. Bonate Tags: Main Paper Source Type: research
Effect of design specifications in dose ‐finding trials for combination therapies in oncology
In this study, we featured the well‐known four design aspects and evaluated the impact of each independent effect on the operating characteristics of the dose‐finding method including these aspects. We performed simulation studies to examine the effect of these design aspects on the determination of the true maximum tolerated dose combinations as well as exposure to unacceptable toxic dose combinations. The results demonstrated that the selection rates of maximum tolerated dose combinations and UTDCs vary depending on the patient cohort size and restrictions on dose‐level skipping However, the three‐parameter dose...
Source: Pharmaceutical Statistics - August 18, 2016 Category: Statistics Authors: Akihiro Hirakawa, Hiroyuki Sato, Masahiko Gosho Tags: Main Paper Source Type: research
