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Apply new statistical methods to assess screening efficacy in NLST 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
NLST (Learn more about this study)
Project ID
NLST-891
Initial CDAS Request Approval
Mar 7, 2022
Title
Apply new statistical methods to assess screening efficacy in NLST 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 NLST trial data 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.
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 NLST trial data

Collaborators

Dr. Ziding Feng, Fred Hutchinson Cancer Research Center