Apply new statistical methods to assess screening efficacy in PLCO trial addressing overdiagnosis
Principal Investigator
Name
Ying Huang
Degrees
Ph.D.
Institution
Fred Hutchinson Cancer Research Center
Position Title
Full Professor
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-935
Initial CDAS Request Approval
Mar 7, 2022
Title
Apply new statistical methods to assess screening efficacy in PLCO trial addressing overdiagnosis
Summary
Cancer screening can allow for detection of cancer early in its development when treatment is most effective. At the same time, it might have potential harm associated with overdiagnosis, namely a diagnosis made by screening that would have never caused symptoms or death during a patient's lifetime. We have been developing new statistical methods for efficiently addressing over-diagnosis when assessing screening efficacy in phase IV trials based on cancer stage shift. We will apply the methods to analyze the PLCO data for various cancer sites and compare the performance with the default method that assesses screening efficacy based on cumulative incidence. We will write a statistical method paper presenting the analysis and provide guidelines on strategies to handle overdiagnosis under different levels of overdiagnosis.
Aims
1) Develop statistical methods to address overdiagnosis when assessing screening efficacy in phase IV trials
2) Gauge the performance of the proposed methods using PLCO trial data for different cancer sites
Collaborators
Dr. Ziding Feng, Fred Hutchinson Cancer Research Center