Literature DB >> 8826919

Benefit of mammography screening in women ages 40 to 49 years. Current evidence from randomized controlled trials.

C R Smart1, R E Hendrick, J H Rutledge, R A Smith.   

Abstract

BACKGROUND: Eight randomized controlled trials (RCTs) of screening mammography were conducted involving women ages 40 to 49 years at entry. Current data gathered for periods ranging from 7 to 18 years of follow-up are available from these trials.
METHODS: Meta-analyses were performed using a Mantel-Haenszel estimator method to combine current follow-up data from the eight RCTs of mammography that included women ages 40 to 49 years.
RESULTS: Combining all current data on women ages 40 to 49 years at entry into the trials yielded a 16% [corrected] benefit from screening mammography, without statistical significance at the 95% confidence level. Combining all data on women ages 40 to 49 years at entry, excluding results from the Canadian National Breast Screening Study, yielded a 24% [corrected] benefit to women invited for screening, with statistical significance at the 95% confidence level.
CONCLUSIONS: These results suggest that screening mammography in women ages 40 to 49 years at entry can reduce mortality from breast cancer when combined with adequate follow-up.

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Mesh:

Year:  1995        PMID: 8826919     DOI: 10.1002/1097-0142(19950401)75:7<1619::aid-cncr2820750711>3.0.co;2-t

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  29 in total

1.  Mammography in New Hampshire: characteristics of the women and the exams they receive.

Authors:  P A Carney; M E Goodrich; D M O'Mahony; A N Tosteson; M S Eliassen; S P Poplack; S Birnbaum; B G Harwood; K A Burgess; B T Berube; W S Wells; J P Ball; M M Stevens
Journal:  J Community Health       Date:  2000-06

Review 2.  Preventive health care, 2001 update: screening mammography among women aged 40-49 years at average risk of breast cancer.

Authors:  J Ringash
Journal:  CMAJ       Date:  2001-02-20       Impact factor: 8.262

3.  Computer-aided detection of breast masses on full field digital mammograms.

Authors:  Jun Wei; Berkman Sahiner; Lubomir M Hadjiiski; Heang-Ping Chan; Nicholas Petrick; Mark A Helvie; Marilyn A Roubidoux; Jun Ge; Chuan Zhou
Journal:  Med Phys       Date:  2005-09       Impact factor: 4.071

4.  Dual system approach to computer-aided detection of breast masses on mammograms.

Authors:  Jun Wei; Heang-Ping Chan; Berkman Sahiner; Lubomir M Hadjiiski; Mark A Helvie; Marilyn A Roubidoux; Chuan Zhou; Jun Ge
Journal:  Med Phys       Date:  2006-11       Impact factor: 4.071

5.  Bilateral analysis based false positive reduction for computer-aided mass detection.

Authors:  Yi-Ta Wu; Jun Wei; Lubomir M Hadjiiski; Berkman Sahiner; Chuan Zhou; Jun Ge; Jiazheng Shi; Yiheng Zhang; Heang-Ping Chan
Journal:  Med Phys       Date:  2007-08       Impact factor: 4.071

6.  Characterization of mammographic masses based on level set segmentation with new image features and patient information.

Authors:  Jiazheng Shi; Berkman Sahiner; Heang-Ping Chan; Jun Ge; Lubomir Hadjiiski; Mark A Helvie; Alexis Nees; Yi-Ta Wu; Jun Wei; Chuan Zhou; Yiheng Zhang; Jing Cui
Journal:  Med Phys       Date:  2008-01       Impact factor: 4.071

7.  Addressing women's breast cancer risk and perceptions of control in medical settings.

Authors:  R Royak-Schaler; B Cheuvront; K R Wilson; C M Williams
Journal:  J Clin Psychol Med Settings       Date:  1996-09

8.  Mammography and the politics of randomised controlled trials.

Authors:  J Wells
Journal:  BMJ       Date:  1998-10-31

9.  Identification of findings suspicious for breast cancer based on natural language processing of mammogram reports.

Authors:  N L Jain; C Friedman
Journal:  Proc AMIA Annu Fall Symp       Date:  1997

Review 10.  State of the art of current modalities for the diagnosis of breast lesions.

Authors:  Cosimo Di Maggio
Journal:  Eur J Nucl Med Mol Imaging       Date:  2004-04-15       Impact factor: 9.236

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