Stat4Onc 2019 Symposium Short Courses

April 25, 2019             Morning courses         8:30 AM to 12:00 noon          with one break

Afternoon courses      1:30 PM to 5:00 PM               with one break

Course 3    (Afternoon Course)  Statistical Remedies for Flawed Conventions in Medical Research

Instructor – Dr. Peter Thall, University of Texas, M.D. Anderson Cancer Center

Abstract

Many statistical methods commonly used for data analysis or clinical trial design by medical researchers are deeply flawed.  Unfortunately, many of these dysfunctional statistical conventions and paradigms are deeply embedded in the medical research community, and have become standard or even required practice. Ultimately, the consequence is that practicing physicians are misled to choose inferior or harmful treatments for their patients. In this half day short course, I will identify and describe, by example, severe problems with a variety of statistical practices commonly used by medical statisticians and physician researchers. For each flawed practice, I will provide at least one practical alternative.

Prerequisites: The short course will include limited mathematical detail, with each example presented from a practical viewpoint.  Attendees should have some knowledge of elementary probability and statistics, and clinical trial design.

Target Audience: Attendees may be anyone involved in statistical analysis of medical data, or clinical design and conduct, including statisticians, physicians, research nurses, professionals in the pharmaceutical industry, and federal employees in the NIH or FDA.

Topics Covered, as time permits

Misinterpreting tests of hypotheses

P-values, strength of evidence, and Bayesian inference

Relationships between treatment response and survival time 

Being misled by single-arm trials

Futile futility stopping rules

Unsafe safety monitoring rules

Simpson’s paradox

Sexy biomarkers and stratification

Simple graphical methods to avoid disaster

Randomization and causality

Inverse probability of treatment weighted estimation

Outcome adaptive randomization

Cherry picking

Treatment screening and phase II-III designs

Estimating treatment-covariate interactions

Avoiding overfitting regression models

Salvage therapy and dynamic treatment regimes

SMART designs

Choosing doses the wrong and right way

Biography

Peter F. Thall is the Anise J. Sorrell Professor in the Department of Biostatistics at M.D. Anderson Cancer Center, and an adjunct professor in the Department of Statistics at Rice University.  He is a Fellow of the American Statistical Association and the Society for Clinical Trials, and received the Don Owen Award in 2014.  Dr. Thall has published over 250 papers and book chapters in the statistical and medical literature, and co-authored the 2016 book Bayesian Designs for Phase I-II Clinical Trials. His latest book, Statistical Remedies for Medical Researchers, is in press and should become available in the summer of 2019. Dr. Thall’s research areas include clinical trial design, precision medicine, Bayesian nonparametric statistics, incorporating expert opinion into Bayesian inference, and dynamic treatment regimes. He has presented over 200 invited talks and 30 short courses, served as an associate editor for Journal of the National Cancer Institute, Statistics in Medicine, Statistics in Biosciences, Clinical Trials, and Biometrics, and is an ASA media expert.