Literature DB >> 24590736

Lead-time models should not be used to estimate overdiagnosis in cancer screening.

Per-Henrik Zahl1, Karsten Juhl Jørgensen, Peter C Gøtzsche.   

Abstract

Lead-time can mean two different things: Clinical lead-time is the lead-time for clinically relevant tumors; that is, those that are not overdiagnosed. Model-based lead-time is a theoretical construct where the time when the tumor would have caused symptoms is not limited by the person's death. It is the average time at which the diagnosis is brought forward for both clinically relevant and overdiagnosed cancers. When screening for breast cancer, clinical lead-time is about 1 year, while model-based lead-time varies from 2 to 7 years. There are two different methods to calculate overdiagnosis in cancer screening--the excess-incidence approach and the lead-time approach--that rely on two different lead-time definitions. Overdiagnosis when screening with mammography has varied from 0 to 75 %. We have explained that these differences are mainly caused by using different definitions and methods and not by variations in data. High levels of overdiagnosis of cancer have usually been explained by detection of many slow-growing tumors with long lead-times. This theory can be tested by studying if slow-growing tumors accumulate in the absence of screening, which they don't. Thus, it is likely that the natural history of many subclinical cancers is spontaneous regression.

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Year:  2014        PMID: 24590736      PMCID: PMC4139512          DOI: 10.1007/s11606-014-2812-2

Source DB:  PubMed          Journal:  J Gen Intern Med        ISSN: 0884-8734            Impact factor:   5.128


  12 in total

Review 1.  Influence of study features and methods on overdiagnosis estimates in breast and prostate cancer screening.

Authors:  Ruth Etzioni; Roman Gulati; Leslie Mallinger; Jeanne Mandelblatt
Journal:  Ann Intern Med       Date:  2013-06-04       Impact factor: 25.391

2.  Overdiagnosis of invasive breast cancer due to mammography screening: results from the Norwegian screening program.

Authors:  Mette Kalager; Hans-Olov Adami; Michael Bretthauer; Rulla M Tamimi
Journal:  Ann Intern Med       Date:  2012-04-03       Impact factor: 25.391

3.  Extra incidence caused by mammographic screening.

Authors:  R Boer; P Warmerdam; H de Koning; G van Oortmarssen
Journal:  Lancet       Date:  1994-04-16       Impact factor: 79.321

4.  The Wisconsin Breast Cancer Epidemiology Simulation Model.

Authors:  Dennis G Fryback; Natasha K Stout; Marjorie A Rosenberg; Amy Trentham-Dietz; Vipat Kuruchittham; Patrick L Remington
Journal:  J Natl Cancer Inst Monogr       Date:  2006

5.  Prostate cancer screening in the randomized Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial: mortality results after 13 years of follow-up.

Authors:  Gerald L Andriole; E David Crawford; Robert L Grubb; Saundra S Buys; David Chia; Timothy R Church; Mona N Fouad; Claudine Isaacs; Paul A Kvale; Douglas J Reding; Joel L Weissfeld; Lance A Yokochi; Barbara O'Brien; Lawrence R Ragard; Jonathan D Clapp; Joshua M Rathmell; Thomas L Riley; Ann W Hsing; Grant Izmirlian; Paul F Pinsky; Barnett S Kramer; Anthony B Miller; John K Gohagan; Philip C Prorok
Journal:  J Natl Cancer Inst       Date:  2012-01-06       Impact factor: 13.506

6.  Natural history of breast cancers detected in the Swedish mammography screening programme: a cohort study.

Authors:  Per-Henrik Zahl; Peter C Gøtzsche; Jan Mæhlen
Journal:  Lancet Oncol       Date:  2011-10-11       Impact factor: 41.316

7.  Overdiagnosis of breast cancer after 14 years of mammography screening.

Authors:  Per-Henrik Zahl; Jan Mæhlen
Journal:  Tidsskr Nor Laegeforen       Date:  2012-02-21

8.  Incidence of breast cancer in Norway and Sweden during introduction of nationwide screening: prospective cohort study.

Authors:  Per-Henrik Zahl; Bjørn Heine Strand; Jan Maehlen
Journal:  BMJ       Date:  2004-03-10

9.  The natural history of invasive breast cancers detected by screening mammography.

Authors:  Per-Henrik Zahl; Jan Maehlen; H Gilbert Welch
Journal:  Arch Intern Med       Date:  2008-11-24

Review 10.  Overdiagnosis in publicly organised mammography screening programmes: systematic review of incidence trends.

Authors:  Karsten Juhl Jørgensen; Peter C Gøtzsche
Journal:  BMJ       Date:  2009-07-09
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  13 in total

1.  Conditions for Valid Empirical Estimates of Cancer Overdiagnosis in Randomized Trials and Population Studies.

Authors:  Roman Gulati; Eric J Feuer; Ruth Etzioni
Journal:  Am J Epidemiol       Date:  2016-06-29       Impact factor: 4.897

2.  Estimating the frequency of indolent breast cancer in screening trials.

Authors:  Yu Shen; Wenli Dong; Roman Gulati; Marc D Ryser; Ruth Etzioni
Journal:  Stat Methods Med Res       Date:  2018-02-05       Impact factor: 3.021

3.  Oversimplifying overdiagnosis.

Authors:  Ruth Etzioni; Roman Gulati
Journal:  J Gen Intern Med       Date:  2014-09       Impact factor: 5.128

Review 4.  Missteps in Current Estimates of Cancer Overdiagnosis.

Authors:  Christoph I Lee; Ruth Etzioni
Journal:  Acad Radiol       Date:  2016-11-25       Impact factor: 3.173

5.  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

6.  Estimation of Breast Cancer Overdiagnosis in a U.S. Breast Screening Cohort.

Authors:  Marc D Ryser; Jane Lange; Lurdes Y T Inoue; Ellen S O'Meara; Charlotte Gard; Diana L Miglioretti; Jean-Luc Bulliard; Andrew F Brouwer; E Shelley Hwang; Ruth B Etzioni
Journal:  Ann Intern Med       Date:  2022-03-01       Impact factor: 51.598

Review 7.  Recognizing the Limitations of Cancer Overdiagnosis Studies: A First Step Towards Overcoming Them.

Authors:  Ruth Etzioni; Roman Gulati
Journal:  J Natl Cancer Inst       Date:  2015-11-18       Impact factor: 13.506

Review 8.  Benefits and harms of mammography screening.

Authors:  Magnus Løberg; Mette Lise Lousdal; Michael Bretthauer; Mette Kalager
Journal:  Breast Cancer Res       Date:  2015-05-01       Impact factor: 6.466

9.  Overdiagnosis: epidemiologic concepts and estimation.

Authors:  Jong-Myon Bae
Journal:  Epidemiol Health       Date:  2015-02-10

Review 10.  Four Principles to Consider Before Advising Women on Screening Mammography.

Authors:  John D Keen; Karsten J Jørgensen
Journal:  J Womens Health (Larchmt)       Date:  2015-10-23       Impact factor: 2.681

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