Estimating Patient-Specific Benefits and Harms of Low-Dose Computed Tomography Screening For Lung Cancer
Principal Investigator
Name
Kyle Schmaus
Degrees
MA
Institution
Archimedes, Inc.
Position Title
Associate Scientist
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-43
Initial CDAS Request Approval
Jul 29, 2013
Title
Estimating Patient-Specific Benefits and Harms of Low-Dose Computed Tomography Screening For Lung Cancer
Summary
Recent studies indicate that lung cancer screening using low-dose CT scan may reduce lung cancer mortality. However, lung cancer screening is not without potential harms, including radiation exposure, and significant rates of false positives, which in turn trigger further imaging and invasive diagnostic procedures. It remains unclear which groups of patients derive the greatest benefits from screening, and whether the eligibility criteria for screening should be extended beyond the populations enrolled in randomized controlled trials. The most effective duration or frequency of screening is similarly unknown.
The Archimedes Model is a trial-validated, clinically detailed simulation model of human physiology, disease progression, and healthcare delivery. Data from the The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial will be used to update and validate the current Archimedes lung cancer model. The updated model will be used to investigate optimal guidelines for lung cancer screening that maximize benefits and minimize risks for patients, and potentially reduce costs.
The Archimedes Model is a trial-validated, clinically detailed simulation model of human physiology, disease progression, and healthcare delivery. Data from the The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial will be used to update and validate the current Archimedes lung cancer model. The updated model will be used to investigate optimal guidelines for lung cancer screening that maximize benefits and minimize risks for patients, and potentially reduce costs.
Aims
The objective of the proposed modeling analysis is to answer the following questions:
1. For a given group of patients, what are the impacts of lung cancer screening on clinical and economic outcomes?
2. For which group of patients would the risks of lung cancer screening likely outweigh its benefits?
3. For which group of patients does lung cancer screening improve outcomes and reduce costs?
Collaborators
Tuan Dinh, PhD. Vice President of Analytics and Modeling, Archimedes Inc.
Michael K. Gould, MD, MS. Assistant Director for Health Services Research, Department of Research & Evaluation, Kaiser Permanente Southern California.
Gerard A. Silvestri, MD, MS. Professor, Department of Medicine, Medical University of South Carolina