A case study in identifying targeted patients population in major depressive disorder by enhanced enrichment design
Pharmaceutical Statistics,Volume 17, Issue 2, Page 144-154, March/April 2018. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - November 19, 2017 Category: Statistics Source Type: research
---
Pharmaceutical Statistics, Ahead of Print. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - November 19, 2017 Category: Statistics Source Type: research
---
Pharmaceutical Statistics,Volume 17, Issue 1, Page 61-73, January/February 2018. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - November 10, 2017 Category: Statistics Source Type: research
Issue Information
Abstract
No abstract is available for this article. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - November 10, 2017 Category: Statistics Tags: ISSUE INFORMATION Source Type: research
---
Pharmaceutical Statistics,Volume 17, Issue 1, Page 12-24, January/February 2018. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - November 6, 2017 Category: Statistics Source Type: research
---
Pharmaceutical Statistics,Volume 17, Issue 1, Page 49-60, January/February 2018. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - November 2, 2017 Category: Statistics Source Type: research
---
Pharmaceutical Statistics,Volume 17, Issue 1, Page 38-48, January/February 2018. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - November 1, 2017 Category: Statistics Source Type: research
---
Pharmaceutical Statistics,Volume 17, Issue 1, Page 25-37, January/February 2018. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - November 1, 2017 Category: Statistics Source Type: research
Integrating dose estimation into a decision ‐making framework for model‐based drug development
Summary
Model‐informed drug discovery and development offers the promise of more efficient clinical development, with increased productivity and reduced cost through scientific decision making and risk management. Go/no‐go development decisions in the pharmaceutical industry are often driven by effect size estimates, with the goal of meeting commercially generated target profiles. Sufficient efficacy is critical for eventual success, but the decision to advance development phase is also dependent on adequate knowledge of appropriate dose and dose‐response. Doses which are too high or low pose risk of clinical or comm...
Source: Pharmaceutical Statistics - November 1, 2017 Category: Statistics Authors: James Dunyak, Patrick Mitchell, Bengt Hamr én, Gabriel Helmlinger, James Matcham, Donald Stanski, Nidal Al‐Huniti Tags: MAIN PAPER Source Type: research
Development of predictive signatures for treatment selection in precision medicine with survival outcomes
For survival endpoints in subgroup selection, a score conversion model is often used to convert the set of biomarkers for each patient into a univariate score and using the median of the univariate scores to divide the patients into biomarker‐positive and biomarker‐negative subgroups. However, this may lead to bias in patient subgroup identification regarding the 2 issues: (1) treatment is equally effective for all patients and/or there is no subgroup difference; (2) the median value of the univariate scores as a cutoff may be inappropriate if the sizes of the 2 subgroups are differ substantially. We utilize a univaria...
Source: Pharmaceutical Statistics - November 1, 2017 Category: Statistics Authors: Yu ‐Chuan Chen, Un Jung Lee, Chen‐An Tsai, James J. Chen Tags: MAIN PAPER Source Type: research
Use of a historical control group in a noninferiority trial assessing a new antibacterial treatment: A case study and discussion of practical implementation aspects
When recruitment into a clinical trial is limited due to rarity of the disease of interest, or when recruitment to the control arm is limited due to ethical reasons (eg, pediatric studies or important unmet medical need), exploiting historical controls to augment the prospectively collected database can be an attractive option. Statistical methods for combining historical data with randomized data, while accounting for the incompatibility between the two, have been recently proposed and remain an active field of research. The current literature is lacking a rigorous comparison between methods but also guidelines about thei...
Source: Pharmaceutical Statistics - November 1, 2017 Category: Statistics Authors: David Dejardin, Paul Delmar, Charles Warne, Katie Patel, Joost van Rosmalen, Emmanuel Lesaffre Tags: MAIN PAPER Source Type: research
Response ‐adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?
Response‐adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the ...
Source: Pharmaceutical Statistics - November 1, 2017 Category: Statistics Authors: Sof ía S. Villar, Jack Bowden, James Wason Tags: MAIN PAPER Source Type: research
Sample size re ‐estimation incorporating prior information on a nuisance parameter
Prior information is often incorporated informally when planning a clinical trial. Here, we present an approach on how to incorporate prior information, such as data from historical clinical trials, into the nuisance parameter–based sample size re‐estimation in a design with an internal pilot study. We focus on trials with continuous endpoints in which the outcome variance is the nuisance parameter. For planning and analyzing the trial, frequentist methods are considered. Moreover, the external information on the variance is summarized by the Bayesian meta‐analytic‐predictive approach. To incorporate external infor...
Source: Pharmaceutical Statistics - November 1, 2017 Category: Statistics Authors: Tobias M ütze, Heinz Schmidli, Tim Friede Tags: MAIN PAPER Source Type: research
Estimation of discrete survival function for error ‐prone diagnostic tests
We present an unbiased estimator of the true survival function and its variance. Asymptotic properties of the proposed estimators are provided, and these properties are examined through simulations. We demonstrate our methods using data from the Viral Resistance to Antiviral Therapy of Hepatitis C study. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - November 1, 2017 Category: Statistics Authors: Abidemi K. Adeniji, Jesse Y. Hsu, Abdus S. Wahed Tags: MAIN PAPER Source Type: research
Design considerations in clinical trials with cure rate survival data: A case study in oncology
Summary
For clinical trials with time‐to‐event as the primary endpoint, the clinical cutoff is often event‐driven and the log‐rank test is the most commonly used statistical method for evaluating treatment effect. However, this method relies on the proportional hazards assumption in that it has the maximal power in this circumstance. In certain disease areas or populations, some patients can be curable and never experience the events despite a long follow‐up. The event accumulation may dry out after a certain period of follow‐up and the treatment effect could be reflected as the combination of improvement of cu...
Source: Pharmaceutical Statistics - November 1, 2017 Category: Statistics Authors: Steven Sun, Grace Liu, Tianmeng Lyu, Fubo Xue, Tzu ‐Min Yeh, Sudhakar Rao Tags: MAIN PAPER Source Type: research
