Clinical utility estimation for assay cutoffs in early phase oncology enrichment trials
Predictive enrichment strategies use biomarkers to selectively enroll oncology patients into clinical trials to more efficiently demonstrate therapeutic benefit. Because the enriched population differs from the patient population eligible for screening with the biomarker assay, there is potential for bias when estimating clinical utility for the screening eligible population if the selection process is ignored. We write estimators of clinical utility as integrals averaging regression model predictions over the conditional distribution of the biomarker scores defined by the assay cutoff and discuss the conditions under whic...
Source: Pharmaceutical Statistics - March 1, 2015 Category: Statistics Authors: Jared K. Lunceford Tags: Main Paper Source Type: research
Assessing the treatment effect in a randomized controlled trial with extensive non‐adherence: the EVOLVE trial
Intention‐to‐treat (ITT) analysis is widely used to establish efficacy in randomized clinical trials. However, in a long‐term outcomes study where non‐adherence to study drug is substantial, the on‐treatment effect of the study drug may be underestimated using the ITT analysis. The analyses presented herein are from the EVOLVE trial, a double‐blind, placebo‐controlled, event‐driven cardiovascular outcomes study conducted to assess whether a treatment regimen including cinacalcet compared with placebo in addition to other conventional therapies reduces the risk of mortality and major cardiovascular events in...
Source: Pharmaceutical Statistics - March 1, 2015 Category: Statistics Authors: Yumi Kubo, Lulu Ren Sterling, Patrick S Parfrey, Karminder Gill, Kenneth W Mahaffey, Ioanna Gioni, Marie‐Louise Trotman, Bastian Dehmel, Glenn M Chertow Tags: Main Paper Source Type: research
Likelihood‐based inferences about the mean area under a longitudinal curve in the presence of observations subject to limits of detection
Comparison of groups in longitudinal studies is often conducted using the area under the outcome versus time curve. However, outcomes may be subject to censoring due to a limit of detection and specific methods that take informative missingness into account need to be applied. In this article, we present a unified model‐based method that accounts for both the within‐subject variability in the estimation of the area under the curve as well as the missingness mechanism in the event of censoring. Simulation results demonstrate that our proposed method has a significant advantage over traditionally implemented methods with...
Source: Pharmaceutical Statistics - March 1, 2015 Category: Statistics Authors: Rameela Chandrasekhar, Yi Shi, Alan D. Hutson, Gregory E. Wilding Tags: Main Paper Source Type: research
Experimental designs for detecting synergy and antagonism between two drugs in a pre‐clinical study
The identification of synergistic interactions between combinations of drugs is an important area within drug discovery and development. Pre‐clinically, large numbers of screening studies to identify synergistic pairs of compounds can often be ran, necessitating efficient and robust experimental designs. We consider experimental designs for detecting interaction between two drugs in a pre‐clinical in vitro assay in the presence of uncertainty of the monotherapy response. The monotherapies are assumed to follow the Hill equation with common lower and upper asymptotes, and a common variance. The optimality criterion used...
Source: Pharmaceutical Statistics - March 1, 2015 Category: Statistics Authors: Matthew Sperrin, Helene Thygesen, Ting‐Li Su, Chris Harbron, Anne Whitehead Tags: Main Paper Source Type: research
Issue Information
No abstract is available for this article. (Source: Pharmaceutical Statistics)
Source: Pharmaceutical Statistics - January 20, 2015 Category: Statistics Tags: Issue Information Source Type: research
