Register for the meeting here!
The WNAR 2021 program schedule can be viewed here.
Program book can be viewed here, including abstracts for presentations.
The program includes:
Student paper sessions
Presidential invited address
Graduate student social hour
Early Career Panel (New Investigators' Luncheon)
Access the speaker page here.
Graduate Student Social Hour
Description: The newly-formed WNAR Student Committee welcomes current and recent graduate students to a social hour/mixer. Meet with students from other programs and also learn about opportunities for student engagement within WNAR.
Early Career Panel
Date/Time: Tuesday, June 15th, from 12:15 to 1:30 pm PDT
Short Course Description
As medical research continues to push into new frontiers of discovery and personalized patient care, along with new complex diseases and worldwide pandemics (COVID-19), it is imperative that clinical trial designs and statistical methodologies evolve to address the forthcoming challenges. One key innovation is the master protocol, including “platform” trial designs which can evaluate multiple therapies simultaneously in complex heterogenous diseases. In this course, we explain Bayesian adaptive methodologies underlying modern trials with master protocols. We introduce fundamental concepts in Bayesian adaptive trials, including Bayesian priors and posteriors, predictive probabilities, hierarchical modeling and “basket” trials, adaptive sample size, and response adaptive randomization. We explain the objectives and efficiencies of adaptive platform trial designs, with high profile examples investigating treatments in COVID-19, Amyotrophic Lateral Sclerosis (ALS), and Cancer. We show the role of virtual trial simulation in trial design, and discuss logistical and practical considerations in the implementation of these complex designs. In addition, we discuss the impact of the COVID-19 pandemic on both design and implementation of adaptive clinical trials.
A highlight of the course will be interactive breakout activities that encourage individual participation and teach key adaptive platform trial concepts. Upon completion of the course, participants will have a general understanding of Bayesian adaptive platform trials and underlying methodologies, and better recognize opportunities for innovation in their respective organizations.
Short Course II (half day) - RMST-based survival analysis methods for non-proportional hazards
Short Course Description
In a prospective clinical study to compare two groups, the primary end point is often the time to a specific event (for example, disease progression, death). The hazard ratio estimate is routinely used to empirically quantify the between-group difference under the assumption that the ratio of the two hazard functions is constant over time. When this assumption is plausible, such a ratio estimate may capture the relative difference between two survival curves. However, the clinical meaning of such a ratio estimate is difficult (if not impossible) to interpret when the underlying proportional hazards assumption is violated. In this course, we will discuss several critical concerns regarding this conventional practice and propose an attractive alternative for quantifying the underlying differences between groups based on restricted mean survival time (RMST). I will discuss various issues in employing RMST in practical analysis including statistical inference, result interpretation, selecting the truncation point, study design, power comparison, regression adjustment and extensions to competing risk and recurrent events settings. We will discuss the pros and cons of the RMST-based analysis and demonstrate that it is competitive to its hazard ratio-based conventional counterparts in many real world applications.
Dr. Tian is Professor at the Department of Biomedical Data Science of Stanford University. Lu Tian received his Sc.D. in Biostatistics from Harvard University. He has considerable experience in statistical methodological research, planning large epidemiological studies, performing data management for randomized clinical trials and conducting applied data analysis. His current research interest includes developing statistical methods in survival analysis, semiparametric regression modelling, high-dimensional data analysis, precision medicine and meta-analysis. He has published more than 200 peer reviewed journal articles and currently served as the Associate Editor of Chance, Biometrics and Statistics in Medicine.
2021 WNAR Conference Organizers
Scientific Program Chair: Yingqi Zhao, Fred Hutchinson Cancer Research Center
Audrey Hendricks (Chair), University of Colorado Denver
Jennifer McNichol, University of New Brunswick
Lingling An, University of Arizona
Subodh Selukar, University of Washington
Student Paper Competition Committee:
Laura Saba (Chair): University of Colorado Anschutz Medical Campus
Jarrett Barber: Arizona state University
Cindy Feng: Dalhousie University
Camille Moore: National Jewish Health
Holly Steeves: University of Victoria
Mourad Tighiouart: Cedars-Sinai Medical Center
Julie Zhou: University of Victoria