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 DC IS. Similar results were found for histological grade. We have developed a computer simulation for mammographic screening data which models progression and detection of Ductal carcinoma in situ. Based on various options for growth, detection and invasion, we have simulated various distributions of DCIS sizes for a screening program. These distributions can then be used to test hypotheses regarding different scenarios of growth and invasion of DOIS. Our preliminary results to date 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. We are presently validating our findings on an independent data set.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2005
- Accession Number
- ADA446423
Entities
People
- Bircan Erbas
- Dorota M. Gertig
- Gram Bymes
- James Dowty
Organizations
- University of Melbourne