Evaluating different breast tumor progression models using screening data

• Published in: BMC cancer Vol. 18; no. 1; p. 209
• Main Authors: Westvik, Åsbjørn Schumacher, Weedon-Fekjær, Harald, Mæhlen, Jan, Liestøl, Knut
• Format: Journal Article
• Language: English
• Published: England BioMed Central 20.02.2018; BMC
• Subjects: Aged; Breast cancer; Breast Neoplasms - diagnostic imaging; Breast Neoplasms - epidemiology; Breast Neoplasms - pathology; Computer Simulation; Disease Progression; Early Detection of Cancer; Female; Hormone replacement therapy; Humans; Incidence; Mammography; Mammography screening; Mass Screening; Middle Aged; Models, Statistical; Norway - epidemiology; Over-diagnosis; Simulation model; Tumor regression; Mammography screening; Breast cancer; Hormone replacement therapy; Simulation model; Over-diagnosis; Tumor regression
• ISSN: 1471-2407; 1471-2407
• DOI: 10.1186/s12885-018-4130-2

Mammography screening is used to detect breast cancer at an early treatable stage, reducing breast cancer mortality. Traditionally, breast cancer has been seen as a disease with only progressive lesions, and here we examine the validity of this assumption by testing if incidence levels after introducing mammography screening can be reproduced assuming only progressive tumors. Breast cancer incidence data 1990-2009 obtained from the initially screened Norwegian counties (Akershus, Oslo, Rogaland and Hordaland) was included, covering the time-period before, during and after the introduction of mammography screening. From 1996 women aged 50-69 were invited for biennial public screening. Using estimates of tumor growth and screening sensitivity based on pre-screening and prevalence screening data (1990-1998), we simulated incidence levels during the following period (1999-2009). The simulated incidence levels during the period with repeated screenings were markedly below the observed levels. The results were robust to changes in model parameters. Adjusting for hormone replacement therapy use, we obtained levels closer to the observed levels. However, there was still a marked gap, and only by assuming some tumors that undergo regressive changes or enter a markedly less detectable state, was our model able to reproduce the observed incidence levels. Models with strictly progressive tumors are only able to partly explain the changes in incidence levels observed after screening introduction in the initially screened Norwegian counties. More complex explanations than a time shift in detection of future clinical cancers seem to be needed to reproduce the incidence trends, questioning the basis for many over-diagnosis calculations. As data are not randomized, similar studies in other populations are wanted to exclude effect of unknown confounders.