Cost Effectiveness in Screening Policies for Breast Cancer in the Presence of Over-diagnosis

Open Access
Chawaranggoon, Chanyakan
Area of Honors:
Industrial Engineering
Bachelor of Science
Document Type:
Thesis Supervisors:
  • Paul Griffin, Thesis Supervisor
  • Paul Griffin, Honors Advisor
  • M Jeya Chandra, Faculty Reader
  • breast cancer screening
  • over-diagnosis
  • cost effectiveness
  • QALY
  • TreeAge Pro
Although breast cancer screening can help reduce the rate of mortality and morbidity, it can also cause harm when there is a presence of over-diagnosis. Over-diagnosis is a medical term, recently used in the healthcare field, indicating harm that is caused by screening mammography. This study aims to explore the issue of breast cancer screening policies in the presence of over-diagnosis and to determine an optimal policy in each scenario. Sensitivity analysis over a range of over-diagnosis rates between 0% and 50%, starting ages between 35 to 50, and screening intervals between 1 year and 5 years is conducted using a Markov chain and decision tree model of breast cancer screening. TreeAge Pro 2013 software was used to perform the analysis. The method incorporates Monte Carlo simulation as well as cost effectiveness analysis with the purpose of determining a recommended policy in breast cancer screening. Quality adjusted life years (QALYs), number of mammograms, and cumulative screening costs were also determined.