Literature DB >> 26462725

Overdiagnosis in cancer screening: the need for a standardized denominator.

Theodora M Ripping1, André Lm Verbeek2, Mireille Jm Broeders3.   

Abstract

It is widely accepted that overdiagnosis is a major harm of screening, but its extent is still topic of controversy. This is partly the result of incomparable overdiagnosis estimates in scientific literature, as a variety of denominators are used to calculate the percentage of overdiagnosis in cancer screening. We propose to use the following denominator to calculate the percentage of overdiagnosis: 'all cancers detected during the screening period, both interval and screen-detected, in participants of a screening programme'. This denominator is more appropriate than existing denominators because it presents overdiagnosis as a real percentage, is unaffected by attendance percentages, is applicable to all observational study designs, and can be easily recalculated to absolute numbers. This denominator can be widely applied and increases comparability between overdiagnosis estimates, which is needed to correctly present the balance between the benefits and harms of screening.
© The Author(s) 2015.

Entities:  

Keywords:  cancer; overdiagnosis; screening

Mesh:

Year:  2015        PMID: 26462725     DOI: 10.1177/0969141315604864

Source DB:  PubMed          Journal:  J Med Screen        ISSN: 0969-1413            Impact factor:   2.136


  3 in total

1.  Editorial: Challenges in Quantifying Overdiagnosis.

Authors:  Stuart G Baker; Philip C Prorok; Barnett S Kramer
Journal:  J Natl Cancer Inst       Date:  2017-10-01       Impact factor: 13.506

Review 2.  Screening in Public Health and Clinical Care: Similarities and Differences in Definitions, Types, and Aims - A Systematic Review.

Authors:  Mark Speechley; Abraham Kunnilathu; Eby Aluckal; M S Balakrishna; Benoy Mathew; Eldhose K George
Journal:  J Clin Diagn Res       Date:  2017-03-01

3.  Estimation of overdiagnosis in colorectal cancer screening with sigmoidoscopy and faecal occult blood testing: comparison of simulation models.

Authors:  Paulina Wieszczy; Michal F Kaminski; Magnus Løberg; Marek Bugajski; Michael Bretthauer; Mette Kalager
Journal:  BMJ Open       Date:  2021-04-14       Impact factor: 2.692

  3 in total

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