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Computer aids and human second reading as interventions in screening mammography: two systematic reviews to compare effects on cancer detection and recall rate

Taylor, P.; Potts, H. W. W.; (2008) Computer aids and human second reading as interventions in screening mammography: two systematic reviews to compare effects on cancer detection and recall rate. European Journal of Cancer , 44 (6) pp. 798-807. 10.1016/j.ejca.2008.02.016. Green open access

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Abstract

Background: There are two competing methods for improving the accuracy of a radiologist interpreting screening mammograms: computer aids (CAD) or independent second reading. Methods: Bibliographic databases were searched for clinical trials. Meta-analyses estimated impacts of CAD and double reading on odds ratios for cancer detection and recall rates. Sub-group analyses considered double reading with arbitration. Results: Ten studies compared single reading with CAD to single reading. Seventeen compared double to single reading. Double reading increases cancer detection and recall rates. Double reading with arbitration increases detection rate (CI: 1.02-1.15) and decreases recall rate (CI: 0.92-0.96). CAD does not have a significant effect on cancer detection rate (CI: 0.96-1.13) and increases recall rate (95% CI: 1.09-1.12). However, there is considerable heterogeneity in the impact on recall rate in both sets of studies. Conclusion: The evidence that double reading with arbitration enhances screening is stronger than that for single reading with CAD.

Type: Article
Title: Computer aids and human second reading as interventions in screening mammography: two systematic reviews to compare effects on cancer detection and recall rate
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.ejca.2008.02.016
Publisher version: http://dx.doi.org/10.1016/j.ejca.2008.02.016
Language: English
Keywords: Mammography, diagnosis, computer-assisted, image interpretation, double reading
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > CHIME
URI: https://discovery.ucl.ac.uk/id/eprint/5173
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