Modeling Ductal Carcinoma In Situ (DCIS): An Overview of CISNET Model Approaches.

Area of Science:

• Oncology
• Biostatistics
• Health Services Research

Background:

• Ductal carcinoma in situ (DCIS) is a precursor to invasive breast cancer, with incidence rising due to mammography.
• The clinical value of detecting and treating DCIS remains controversial.
• Uncertainty exists regarding the extent to which DCIS detection and treatment prevent invasive disease and reduce mortality.

Purpose of the Study:

• To provide an overview of Cancer Intervention and Surveillance Modelling Network (CISNET) models for DCIS natural history.
• To compare CISNET models with other DCIS modeling approaches in the literature.

Main Methods:

• Review and comparison of existing CISNET and external modeling approaches for DCIS.
• Analysis of model assumptions, data sources, and parameter estimation for DCIS progression.
• Evaluation of model outcomes, including overdiagnosis rates and progression probabilities.

Main Results:

• Five of six CISNET models incorporate DCIS, generally assuming partial progression to invasive cancer.
• Significant variation exists in DCIS overdiagnosis estimates (34%-72%) and progression rates (20%-91%) across models.
• DCIS grade is not yet integrated into current CISNET models.

Conclusions:

• CISNET models consistently indicate substantial overdiagnosis of DCIS.
• Future improvements may arise from active surveillance trial data, predictive markers, and new screening modalities like tomosynthesis.
• Current findings support the safety and value of observational trials for low-risk DCIS.