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First published August 21, 2007 as JAMIA PrePrint; doi:10.1197/jamia.M2130
Journal of the American Medical Informatics Association 2007;14(6):736-745
© 2007 American Medical Informatics Association

A more recent version of this article appeared on November 1, 2007
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Submitted on April 19, 2006
Accepted on August 2, 2007

Collection of Cancer Stage Data by Classifying Free-text Medical Reports

Iain A. McCowan PhD1*, Darren C. Moore MEng1, Anthony Nguyen PhD1, Rayleen V. Bowman PhD2, Belinda E. Clarke PhD3, Edwina E. Duhig3, and Mary-Jane Fry4

Affiliation of the authors: 1 CSIRO e-Health Research Centre, Brisbane, Australia; 2 Department of Medicine, University of Queensland, Brisbane, Australia ; 3 Department of Anatomical Pathology, The Prince Charles Hospital, Brisbane, Australia ; 4 Queensland Cancer Control Analysis Team, Queensland Health, Brisbane, Australia

* To whom correspondence should be addressed.

Cancer staging provides a basis for planning clinical management, but also allows for meaningful analysis of cancer outcomes and evaluation of cancer care services. Despite this, stage data in cancer registries is often incomplete, inaccurate or simply not collected. This article describes a prototype software system (Cancer Stage Interpretation System, CSIS) which automatically extracts cancer staging information from medical reports. The system uses text classification techniques to train support vector machines (SVM) to extract elements of stage listed in cancer staging guidelines. When processing new reports, CSIS identifies sentences relevant to the staging decision, and subsequently assigns the most likely stage. The system was developed using a database of staging data and pathology reports for 710 lung cancer patients, then validated in an independent set of 179 patients against pathologic stage assigned by two independent pathologists. CSIS achieved overall accuracy of 74% for tumour (T) staging and 87% for node (N) staging, and errors were observed to mirror disagreements between human experts.






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