Volume 143, Issue 6 pp. 1287-1294
Cancer Epidemiology

As you like it: How the same data can support manifold views of overdiagnosis in breast cancer screening

Sisse Helle Njor

Corresponding Author

Sisse Helle Njor

Department of Public Health Programmes, Randers Regional Hospital, Randers, Denmark

Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark

Correspondence to: Sisse Helle Njor, Department of Public Health Programmes, Randers Regional Hospital, Skovlyvej 15, 8930 Randers NØ, Denmark, Tel.: +45-7842-0183; E-mail: [email protected]Search for more papers by this author
Eugenio Paci

Eugenio Paci

Former: ISPO Cancer Prevention and Research Institute, Florence, Italy

Search for more papers by this author
Matejka Rebolj

Matejka Rebolj

Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts & The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom

Search for more papers by this author
First published: 06 April 2018
Citations: 9

MR attended meetings with various manufacturers of Human Papillomavirus technologies. She and her former employer received fees for lectures on her behalf from Qiagen.

Abstract

Overdiagnosis estimates have varied substantially, causing confusion. The discussions have been complicated by the fact that population and study design have varied substantially between studies. To help assess the impact of study design choices on the estimates, we compared them on a single population. A cohort study from Funen County, Denmark, recently suggested little (∼1%) overdiagnosis. It followed previously screened women for up to 14 years after screening had ended. Using publically available data from Funen, we recreated the designs from five high-estimate, highly cited studies from various countries. Selected studies estimated overdiagnosis to be 25–54%. Their designs were adapted only to the extent that they reflect the start of screening in Funen in 1993. The reanalysis of the Funen data resulted in overdiagnosis estimates that were remarkably similar to those from the original high-estimate age-period studies, 21–55%. In additional analyses, undertaken to elucidate the effect of the individual components of the study designs, overdiagnosis estimates were more than halved after the most likely changes in the background risk were accounted for and decreased additionally when never-screened birth cohorts were excluded from the analysis. The same data give both low and high estimates of overdiagnosis, it all depends on the study design. This stresses the need for a careful scrutiny of the validity of the assumptions underpinning the estimates. Age-period analyses of breast cancer overdiagnosis suggesting very high frequencies of overdiagnosis rested on unmet assumptions. This study showed that overdiagnosis estimates should in the future be requested to adequately control for the background risk and include an informative selection of the studied population to achieve valid and comparable estimates of overdiagnosis.

Abstract

What's new?

Breast cancer screening can lead to better survival, but it also increases the risk of overdiagnosis. Significant variability in overdiagnosis estimates has been disconcerting to both experts and women considering their screening participation. Here, the authors reproduced the analyses made in several previous studies to estimate overdiagnosis using a single recent data source. Estimates ranged widely, from 1% to 55%. However, high estimates were more than halved when accounting for changes in background risk, and further decreased when excluding never-screened birth cohorts. Thus, considering underlying study assumptions is important to produce more informative overdiagnosis estimates, and potentially avoid unwarranted confusion.

The full text of this article hosted at iucr.org is unavailable due to technical difficulties.