Literature DB >> 26206144

Effect of mammographic screening from age 40 years on breast cancer mortality in the UK Age trial at 17 years' follow-up: a randomised controlled trial.

Sue M Moss1, Christopher Wale2, Robert Smith3, Andrew Evans4, Howard Cuckle5, Stephen W Duffy2.   

Abstract

BACKGROUND: Age-specific effects of mammographic screening, and the timing of such effects, are a matter of debate. The results of the UK Age trial, which compared the effect of invitation to annual mammographic screening from age 40 years with commencement of screening at age 50 years on breast cancer mortality, have been reported at 10 years of follow-up and showed no significant difference in mortality between the trial groups. Here, we report the results of the UK Age trial after 17 years of follow-up.
METHODS: Women aged 39-41 from 23 UK NHS Breast Screening Programme units years were randomly assigned by individual randomisation (1:2) to either an intervention group offered annual screening by mammography up to and including the calendar year of their 48th birthday or to a control group receiving usual medical care (invited for screening at age 50 years and every 3 years thereafter). Both groups were stratified by general practice. We compared breast cancer incidence and mortality by time since randomisation. Analyses included all women randomly assigned who could be traced with the National Health Service Central Register and who had not died or emigrated before entry. The primary outcome measures were mortality from breast cancer (defined as deaths with breast cancer coded as the underlying cause of death) and breast cancer incidence, including in-situ, invasive, and total incidence. Because there is an interest in the timing of the mortality effect, we analysed the results in different follow-up periods. This trial is registered, number ISRCTN24647151.
FINDINGS: Between Oct 14, 1990, and Sept 25, 1997, 160 921 participants were randomly assigned; 53 883 women in the intervention group and 106 953 assigned to usual medical care were included in this analysis. After a median follow-up of 17 years (IQR 16·8-18·8), the rate ratio (RR) for breast cancer mortality was 0·88 (95% CI 0·74-1·04) from tumours diagnosed during the intervention phase. A significant reduction in breast cancer mortality was noted in the intervention group compared with the control group in the first 10 years after diagnosis (RR 0·75, 0·58-0·97) but not thereafter (RR 1·02, 0·80-1·30) from tumours diagnosed during the intervention phase. The overall breast cancer incidence during 17 year follow-up was similar between the intervention group and the control group (RR 0·98, 0·93-1·04).
INTERPRETATION: Our results support an early reduction in mortality from breast cancer with annual mammography screening in women aged 40-49 years. Further data are needed to fully understand long-term effects. Cumulative incidence figures suggest at worst a small amount of overdiagnosis. FUNDING: National Institute for Health Research Health Technology Assessment programme and the American Cancer Society. Past funding was received from the Medical Research Council, Cancer Research UK, the UK Department of Health, and the US National Cancer Institute.
Copyright © 2015 Elsevier Ltd. All rights reserved.

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Year:  2015        PMID: 26206144     DOI: 10.1016/S1470-2045(15)00128-X

Source DB:  PubMed          Journal:  Lancet Oncol        ISSN: 1470-2045            Impact factor:   41.316


  43 in total

1.  Breast cancer: Doubtful health benefit of screening from 40 years of age.

Authors:  Philippe Autier
Journal:  Nat Rev Clin Oncol       Date:  2015-09-15       Impact factor: 66.675

2.  Breast cancer screening panels continue to confuse the facts and inject their own biases.

Authors:  D B Kopans
Journal:  Curr Oncol       Date:  2015-10       Impact factor: 3.677

3.  Annual mammography at age 45-49 years and biennial mammography at age 50-69 years: comparing performance measures in an organised screening setting.

Authors:  Lauro Bucchi; Alessandra Ravaioli; Flavia Baldacchini; Orietta Giuliani; Silvia Mancini; Rosa Vattiato; Fabio Falcini; Paolo Giorgi Rossi; Cinzia Campari; Debora Canuti; Enza Di Felice; Priscilla Sassoli de Bianchi; Stefano Ferretti; Nicoletta Bertozzi
Journal:  Eur Radiol       Date:  2019-03-18       Impact factor: 5.315

4.  Recommendations on screening for breast cancer in women aged 40-74 years who are not at increased risk for breast cancer.

Authors:  Scott Klarenbach; Nicki Sims-Jones; Gabriela Lewin; Harminder Singh; Guylène Thériault; Marcello Tonelli; Marion Doull; Susan Courage; Alejandra Jaramillo Garcia; Brett D Thombs
Journal:  CMAJ       Date:  2018-12-10       Impact factor: 8.262

5.  Should we expect all-cause mortality reductions in large screening studies?

Authors:  Kevin K Dobbin; Mark Ebell
Journal:  Br J Gen Pract       Date:  2018-06       Impact factor: 5.386

Review 6.  Cancer-Specific Mortality, All-Cause Mortality, and Overdiagnosis in Lung Cancer Screening Trials: A Meta-Analysis.

Authors:  Mark H Ebell; Michelle Bentivegna; Cassie Hulme
Journal:  Ann Fam Med       Date:  2020-11       Impact factor: 5.166

7.  Comparing CISNET Breast Cancer Incidence and Mortality Predictions to Observed Clinical Trial Results of Mammography Screening from Ages 40 to 49.

Authors:  Jeroen J van den Broek; Nicolien T van Ravesteyn; Jeanne S Mandelblatt; Hui Huang; Mehmet Ali Ergun; Elizabeth S Burnside; Cong Xu; Yisheng Li; Oguzhan Alagoz; Sandra J Lee; Natasha K Stout; Juhee Song; Amy Trentham-Dietz; Sylvia K Plevritis; Sue M Moss; Harry J de Koning
Journal:  Med Decis Making       Date:  2018-04       Impact factor: 2.583

Review 8.  Risk-Reducing Options for Women with a Hereditary Breast Cancer Predisposition.

Authors:  Ismail Jatoi
Journal:  Eur J Breast Health       Date:  2018-10-01

9.  Simulating the Impact of Risk-Based Screening and Treatment on Breast Cancer Outcomes with MISCAN-Fadia.

Authors:  Jeroen J van den Broek; Nicolien T van Ravesteyn; Eveline A Heijnsdijk; Harry J de Koning
Journal:  Med Decis Making       Date:  2018-04       Impact factor: 2.583

10.  The University of Wisconsin Breast Cancer Epidemiology Simulation Model: An Update.

Authors:  Oguzhan Alagoz; Mehmet Ali Ergun; Mucahit Cevik; Brian L Sprague; Dennis G Fryback; Ronald E Gangnon; John M Hampton; Natasha K Stout; Amy Trentham-Dietz
Journal:  Med Decis Making       Date:  2018-04       Impact factor: 2.583

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