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 1 (Morning
Course) Survival Analysis Methods for Non-Proportional Hazards
Instructor – Professor Lu Tian, Stanford University
Abstract
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 approximately 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.
Biography
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.