A decision model for colorectal cancer screening and surveillance

Sally Perng, Purdue University

Abstract

This thesis presents a decision model for use of colonoscopy as a screen for colorectal cancer and for surveillance of adenomatous polyps. Colorectal cancer is the second leading causes of cancer death for both male and female in the United State. The majority of colorectal cancers develop from adenomatous polyps, but these benign neoplasia can be detected and removed during a colonoscopy before becoming malignant. Among the screening methods for colorectal cancer, colonoscopy is the method which can both observe the entire length of the colon and remove polyps during the procedure. Patient characteristics influence the risk of developing cancer, so the required testing schedule should be different for various patient groups. The goal of this study is to provide colonoscopy screening and surveillance guidelines for different patient groups. This study combines a predictive model of colorectal cancer risk with associated costs for colorectal cancer, life expectancy, and patient symptoms to build a decision tree model. To account for the variations in colorectal cancer risks of different patient groups, an odds ratio analysis study was incorporated into the decision tree model to identify the high-risk patient group. The result was presented in the Excel spreadsheet which can provide a specific surveillance schedule for each patient group.

Degree

M.S.I.E.

Advisors

Yih, Purdue University.

Subject Area

Industrial engineering|Health care management|Oncology

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