Attenuation of Treatment Effect Due to Measurement Variability in Assessment of Progression-Free Survival

• Activity Number: 71
• Type: Topic Contributed
• Date/Time: Sunday, August 4, 2013 : 4:00 PM to 5:50 PM
• Sponsor: ENAR
• Author(s): Shengyan Hong*+ and Nicola Schmitt and Andrew Stone and Jonathan Denne
• Companies: and AstraZeneca and AstraZeneca and Eli Lilly and Company
• Keywords: progression-free survival ; measurement variability ; attenuation of treatment effect ; tumor assessment frequency ; tumor evaluation ; time to progression

Abstract

For normally distributed data analyzed with linear models, it is well known that measurement error on an independent variable leads to attenuation of the effect of the independent variable on the dependent variable. However, for time-to-event variables such as progression-free survival (PFS), the effect of the measurement variability in the underlying measurements defining the event is less well understood. We conducted a simulation study to evaluate the impact of measurement variability in tumor assessment on hazard ratio for PFS and on the median PFS, for different tumor assessment frequencies. Our results show that scan measurement variability can cause attenuation of the treatment effect (i.e. the hazard ratio is closer to one) and that the extent of attenuation is increased with more frequent scan assessments. This attenuation leads to inflation of the type II error. Therefore, scan measurement variability should be minimized as far as possible in order to reveal a treatment effect that is closest to the truth. In disease setting where the measurement variability is shown to be large, consideration may be given to inflating the sample size of the study to maintain study power.