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It Is Time to Initiate Another Breast Cancer Screening TrialIt Is Time to Initiate Another Breast Cancer Screening Trial

Peter Jüni, MD; and Marcel Zwahlen, PhD
[+] Article and Author Information

This article was published online first at www.annals.org on 8 April 2014.


From Institute of Social and Preventive Medicine, University of Bern, Switzerland.

Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M14-0569.

Requests for Single Reprints: Peter Jüni, MD, Institute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, CH-3012, Bern, Switzerland; e-mail, juni@ispm.unibe.ch.

Current Author Addresses: Drs. Jüni and Zwahlen: Institute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, CH-3012, Bern, Switzerland.

Author Contributions: Conception and design: P. Jüni, M. Zwahlen.

Analysis and interpretation of the data: P. Jüni, M. Zwahlen.

Drafting of the article: P. Jüni.

Critical revision of the article for important intellectual content: P. Jüni, M. Zwahlen.

Final approval of the article: P. Jüni, M. Zwahlen.

Statistical expertise: P. Jüni, M. Zwahlen.

Administrative, technical, or logistic support: P. Jüni.

Collection and assembly of data: P. Jüni, M. Zwahlen.


Ann Intern Med. 2014;160(12):864-866. doi:10.7326/M14-0569
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Recent reports have found that mammography screening did not reduce deaths from breast cancer. The authors of this commentary discuss the evidence about the benefits and harms of screening and suggest that it is time to initiate another breast cancer screening trial.

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Appendix Figure.

Modified Galbraith plot of the estimated effects of mammography screening on deaths from causes other than breast cancer against the statistical precision of 11 screening trials.

The Z score was calculated as ln(RR)/[SE of the ln(RR)]; statistical precision was calculated as 1/[SE of the ln(RR)]. The fixed Z score boundaries at −1.96 and 1.96, represented by the solid lines, divide the plot into areas of significant differences between the screening and control groups (Z < −1.96 and Z > 1.96, respectively) and nonsignificant differences (−1.96 < Z < 1.96). Three trials (Edinburgh 1978, Göteborg 1982, Stockholm 1981) are below the bounds and are associated with a significant benefit of mammography screening on deaths from other causes, whereas 2 others (Malmö II 1978 and Kopparberg 1977) are above the bounds and are associated with a significant harm from mammography screening. If the true RR equals 1, then 1 trial will be outside the boundaries with a probability of 43.1%, 2 trials with 10.2%, and 3 trials with 1.5%. The probability that 5 trials lie outside the boundaries, as is the case, is 0.01%. Data are from reference (5). RR = relative risk.

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Figure.

Forest plot of random-effects meta-analyses of relative risks for breast cancer deaths, deaths from other causes, and all-cause mortality after 7 to 13 years of follow-up, stratified by consistency of trials.

Data are from reference (4). RR = relative risk.

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