HACASA 2026 ASA Traveling Short Course
Friday 9/11/2026
Survival Analysis Methods Correcting for Treatment Switching Effects in Randomized Clinical Trials: Theory and SAS/R Code
Course flyer
Instructor:
Dr. Jing Xu, Senior Director, Takeda
Dr. Bingxia Wang, Senior Director, Takeda
Dr. Qingxia (Cindy) Chen, Professor, Department of Biostatistics, Vanderbilt University
Date: Friday, September 11, 2026 (9:00am – 4:00pm CT)
Location: Virtual via Zoom
Course Description
In many late phase oncology randomized controlled trials (RCTs), control arm patients are permitted to take active treatment (1-way crossover), or patients in both control and active arms are permitted to take alternative treatments (2-way treatment switching) after disease progression due to ethical considerations. In both situations, the effect of active intervention on overall survival (OS) is no longer directly observable. The intent-to-treat (ITT) analysis of the observed data will reflect the trial outcome per the treatment policy strategy but may not be able to make causal inference for the active intervention effect on OS. The latter is important for the payer agency's evaluation and is helpful for regulatory decisions on drug applications.
During the last decade, several complex statistical methods have been adapted and applied to RCTs to recover the causal OS effect of randomized active intervention under settings that allow for treatment switching. These methods include but are not limited to Marginal Structural Model, Two-Stage Estimation, Inverse Probability of Censoring Weighting, Rank-Preserving Structural Failure Time Model, Iterative Parameter Estimation, Three-State Model. This course will review theory, regulatory guidance and demonstrate SAS/R code for these methods. It will discuss the pros and cons and practical issues when each method is applied under the RCT setting. Case studies will be presented to illustrate the application of each method.
What will you learn from this course
· Available methods, regulatory policy, and appropriate approaches in handling issues associated with treatment switching.
· The principles, strengths, limitations, and practical considerations of treatment-switching adjustment methods in one-way crossover and two-way switching settings.
· How to select appropriate adjustment methods during trial design and pre-specify their use in analysis plans.
· How to construct longitudinal counting-process datasets, implement adjustment methods in SAS/R, and generate weighted log-rank tests and adjusted survival curves when needed.
· Cost: Student $25, Member $40, Non-Member $50. To become a HACASA member, the cost is $1 for students and $8 for non-students.
Schedule (CT)
09:00 – 09:05 am Opening
09:05 – 10:25 am Introduction and MSM (part 1)
10:25 – 10:40 am Break
10:40 – 12:00 pm MSM (part 2) and IPCW
12:00 – 01:00 pm Lunch
01:00 – 02:15 pm TSE and RPSFTM
02:15 – 02:30 pm Break
02:30 – 04:00 pm Three-State Model
Please register via link: Survival Analysis Methods Correcting for Treatment Switching Effects in RCT
If you have any questions, please contact HoustonASA@gmail.com
HACASA 2026 Fall Chapter Meeting
Our fall chapter meeting will be held in October. Please check back closer to the date for more details!