Table 2.

A selection of studies of overdiagnosis due to breast cancer screening, labeled according to the measure of overdiagnosis, the study design and context, and the estimation approach used. Studies were selected to reflect a range of choices of overdiagnosis measures, contexts and methods and to include recent, high-profile publications

Author	Years of study	In situ cases included ?	Estimate	Measure	Approach	Context
Morrell 2010 (10)	1999– 2001	No	30–42%	Excess cases/cases expected without screening	Excess incidence	New South Wales, Australia Ages 50–69 Biennial screening Population study
Gotzsche, 2011 (3)	Multiple	Yes	30%	Excess cases/cases expected without screening	Excess incidence*	7 clinical trials of mammography
Kalager, 2012 (5)	1996– 2005	No	15–25%	Excess cases/cases expected without screening	Excess incidence*	Norway Ages 50–69 Biennial screening Population study
Bleyer, 2012 (4)	1976– 2008	Yes	31%	Excess cases/detected cases	Excess incidence*	US SEER9 Ages 40+ Population study
Independent UK Panel on Breast Cancer Screening (11)	Multiple	Yes	11% 3	Excess cases/cases expected without screening Excess cases/lives saved	Excess incidence	UK Ages 50–70 3 clinical trials of mammography Screened every 3 years
Paci, 2006 (9)	1986– 2001	Yes No	4.6% 3.2%	Cases overdiagnosed/cases expected without screening	Lead-time	Five areas of Italy Ages 50–74 Biennial screening Population study
Olsen, 2006 (19)	1991– 1995	No	4.8%	Cases overdiagnosed/detected cases	Lead-time	Copenhagen, Denmark Ages 50–69 Biennial screening (1st two rounds) Population study
De Gelder 2011 (8)	1990– 2006	Yes	8.9% 4.6% 5%	Cases overdiagnosed/Screen-detected cases Cases overdiagnosed/detected cases Cases overdiagnosed/cases expected without screening	Lead time	The Netherlands Ages 40–69 Biennial screening Population study

SEER9 = core 9 catchment areas of the Surveillance, Epidemiology, and End Results program

^*Includes early years of screening use