Arjun Sharma MD, Presenter: Nothing to Disclose

James Jason Morrison MD, Abstract Co-Author: Nothing to Disclose

Jason Michael Hostetter MD, Abstract Co-Author: Nothing to Disclose

Kenneth Chung-Yi Wang MD, PhD, Abstract Co-Author: Co-founder, DexNote, LLC

Eliot L. Siegel MD, Abstract Co-Author: Research Grant, General Electric Company Speakers Bureau, Siemens AG Board of Directors, Carestream Health, Inc Research Grant, XYBIX Systems, Inc Research Grant, Steelcase, Inc Research Grant, Anthro Corp Research Grant, RedRick Technologies Inc Research Grant, Evolved Technologies Corporation Research Grant, Barco nv Research Grant, Intel Corporation Research Grant, Dell Inc Research Grant, Herman Miller, Inc Research Grant, Virtual Radiology Research Grant, Anatomical Travelogue, Inc Medical Advisory Board, Fovia, Inc Medical Advisory Board, Toshiba Corporation Medical Advisory Board, McKesson Corporation Medical Advisory Board, Carestream Health, Inc Medical Advisory Board, Bayer AG Research, TeraRecon, Inc Medical Advisory Board, Bracco Group Researcher, Bracco Group Medical Advisory Board, Merge Healthcare Incorporated Medical Advisory Board, Microsoft Corporation Researcher, Microsoft Corporation

The Prostate, Lung, Colorectal and Ovarian Cancer (PLCO) Screening Trial dataset provides an unparalleled resource for matching patients with the outcomes of demographically or diagnostically comparable patients. Using these matched data, an individualized diagnostic decision-support system can personalize imaging, testing, follow-up intervals, intervention, and prognosis. They can also be incorporated into CAD algorithms to improve diagnostic efficacy by providing a priori likelihood of disease information.

Released in 2009, the PLCO Screening Trial enrolled ~155,000 participants from 1993 to 2001 to determine whether certain screening exams reduced mortality from prostate, lung, colorectal and ovarian cancer. A web-based application was developed using JavaScript to query this subset of patient information against a given patient's demographics and risk factors. Analysis of the matched data yields outcome information which can then be used to guide management decisions and imaging software. Prognostic information is also estimated via the proportion of matched patients that progress to cancer.

The US Preventative Services Task Force provides screening recommendations for cancers of the breast, colorectal tract, and most recently lungs. Additional controversial screening modalities include the use of PSA for prostate cancer and ultrasonography or serum CA-125 for ovarian cancer. There is wide variability in adherence of clinicians to these guidelines and others published by the Fleishner Society and various cancer organizations. Data mining the PLCO dataset for clinical decision support can optimize the use of limited healthcare resources, focusing screening on patients for whom the benefit to risk ratio is the greatest and most efficacious.

A data driven, personalized approach to cancer screening maximizes the economic and clinical efficacy and enables early identification of patients in which the course of disease can be improved. Our dynamic decision support system utilizes a subset of the PLCO dataset as a reference model to determine imaging and testing appropriateness while offering prognostic information for various cancers.

Sharma, A, Morrison, J, Hostetter, J, Wang, K, Siegel, E, Personalized Medicine: A New Paradigm of Decision Support using the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial Dataset.  Radiological Society of North America 2014 Scientific Assembly and Annual Meeting, - ,Chicago IL. http://archive.rsna.org/2014/14011061.html