Evaluating different breast tumor progression models using screening data.

Area of Science:

• Oncology
• Epidemiology
• Biostatistics

Background:

• Mammography screening detects breast cancer early, reducing mortality.
• Traditionally, breast cancer has been viewed as solely progressive.
• This study challenges the assumption of strictly progressive tumors in screening contexts.

Purpose of the Study:

• To test if incidence levels after mammography screening introduction can be reproduced assuming only progressive tumors.
• To evaluate the validity of the progressive tumor assumption in breast cancer screening.
• To understand the dynamics of breast cancer incidence following screening implementation.

Main Methods:

• Utilized breast cancer incidence data from Norwegian counties (1990-2009).
• Simulated incidence levels using estimates of tumor growth and screening sensitivity (1990-1998) for the screening period (1999-2009).
• Compared simulated incidence with observed levels, adjusting for factors like hormone replacement therapy.

Main Results:

• Simulated incidence levels were significantly lower than observed levels during repeated screenings.
• Results remained robust to model parameter changes.
• Reproducing observed incidence required assuming some tumors undergo regression or become less detectable.

Conclusions:

• Models with strictly progressive tumors partially explain incidence changes post-screening.
• More complex tumor dynamics, including regression, are needed to explain observed incidence trends.
• Findings question assumptions in over-diagnosis calculations and call for studies in diverse populations.