Applying Statistical Models to Mammographic Screening Data to Understand Growth and Progression of Ductal Carcinoma in Situ
Abstract
Little is known about the natural history of ductal carcinoma in-situ (DCIS). Estimates from studies of recurrence following surgery suggest about 30% recur as invasive cancer. The aim of this study is to use novel applications of statistical methods to estimate the proportion of DCIS that progress to invasive cancer. We first analysed observed screening data and showed that neither time since previous negative screen or HRT use were associated with size of DCIS. Similar results were found for histological grade. We then developed a computer simulation for mammographic screening data which models progression and detection of ductal carcinoma in situ. The purpose of the simulation is to infer the distribution of DCIS sizes we would expect in mammography data finder different scenarios of tumor initiation, growth, invasion and detection. The simulation therefore provides the user with a test for these competing theories by enabling comparison with actual mammagraphy data. Preliminary results show that low growth rates and low invasion rates provide the best fit to the data. Further work will include the addition of screening round and different mechanisms of invasion to the modeling.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2004
- Accession Number
- ADA430024
Entities
People
- Bircan Erbas
- Dorota Gertig
- Graham Byrnes
- James Dowty
Organizations
- University of Melbourne