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Trial Prospector: Matching Patients with Cancer Research Studies Using an Automated and Scalable Approach

Cancer is responsible for approximately 7.6 million deaths per year worldwide. A 2012 survey in the United Kingdom found dramatic improvement in survival rates for childhood cancer because of increased participation in clinical trials. Unfortunately, overall patient participation in cancer clinical...

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Autores principales: Sahoo, Satya S, Tao, Shiqiang, Parchman, Andrew, Luo, Zhihui, Cui, Licong, Mergler, Patrick, Lanese, Robert, Barnholtz-Sloan, Jill S, Meropol, Neal J, Zhang, Guo-Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Libertas Academica 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4259509/
https://www.ncbi.nlm.nih.gov/pubmed/25506198
http://dx.doi.org/10.4137/CIN.S19454
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author Sahoo, Satya S
Tao, Shiqiang
Parchman, Andrew
Luo, Zhihui
Cui, Licong
Mergler, Patrick
Lanese, Robert
Barnholtz-Sloan, Jill S
Meropol, Neal J
Zhang, Guo-Qiang
author_facet Sahoo, Satya S
Tao, Shiqiang
Parchman, Andrew
Luo, Zhihui
Cui, Licong
Mergler, Patrick
Lanese, Robert
Barnholtz-Sloan, Jill S
Meropol, Neal J
Zhang, Guo-Qiang
author_sort Sahoo, Satya S
collection PubMed
description Cancer is responsible for approximately 7.6 million deaths per year worldwide. A 2012 survey in the United Kingdom found dramatic improvement in survival rates for childhood cancer because of increased participation in clinical trials. Unfortunately, overall patient participation in cancer clinical studies is low. A key logistical barrier to patient and physician participation is the time required for identification of appropriate clinical trials for individual patients. We introduce the Trial Prospector tool that supports end-to-end management of cancer clinical trial recruitment workflow with (a) structured entry of trial eligibility criteria, (b) automated extraction of patient data from multiple sources, (c) a scalable matching algorithm, and (d) interactive user interface (UI) for physicians with both matching results and a detailed explanation of causes for ineligibility of available trials. We report the results from deployment of Trial Prospector at the National Cancer Institute (NCI)-designated Case Comprehensive Cancer Center (Case CCC) with 1,367 clinical trial eligibility evaluations performed with 100% accuracy.
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spelling pubmed-42595092014-12-12 Trial Prospector: Matching Patients with Cancer Research Studies Using an Automated and Scalable Approach Sahoo, Satya S Tao, Shiqiang Parchman, Andrew Luo, Zhihui Cui, Licong Mergler, Patrick Lanese, Robert Barnholtz-Sloan, Jill S Meropol, Neal J Zhang, Guo-Qiang Cancer Inform Methodology Cancer is responsible for approximately 7.6 million deaths per year worldwide. A 2012 survey in the United Kingdom found dramatic improvement in survival rates for childhood cancer because of increased participation in clinical trials. Unfortunately, overall patient participation in cancer clinical studies is low. A key logistical barrier to patient and physician participation is the time required for identification of appropriate clinical trials for individual patients. We introduce the Trial Prospector tool that supports end-to-end management of cancer clinical trial recruitment workflow with (a) structured entry of trial eligibility criteria, (b) automated extraction of patient data from multiple sources, (c) a scalable matching algorithm, and (d) interactive user interface (UI) for physicians with both matching results and a detailed explanation of causes for ineligibility of available trials. We report the results from deployment of Trial Prospector at the National Cancer Institute (NCI)-designated Case Comprehensive Cancer Center (Case CCC) with 1,367 clinical trial eligibility evaluations performed with 100% accuracy. Libertas Academica 2014-12-04 /pmc/articles/PMC4259509/ /pubmed/25506198 http://dx.doi.org/10.4137/CIN.S19454 Text en © 2014 the author(s), publisher and licensee Libertas Academica Ltd. This is an open-access article distributed under the terms of the Creative Commons CC-BY-NC 3.0 License.
spellingShingle Methodology
Sahoo, Satya S
Tao, Shiqiang
Parchman, Andrew
Luo, Zhihui
Cui, Licong
Mergler, Patrick
Lanese, Robert
Barnholtz-Sloan, Jill S
Meropol, Neal J
Zhang, Guo-Qiang
Trial Prospector: Matching Patients with Cancer Research Studies Using an Automated and Scalable Approach
title Trial Prospector: Matching Patients with Cancer Research Studies Using an Automated and Scalable Approach
title_full Trial Prospector: Matching Patients with Cancer Research Studies Using an Automated and Scalable Approach
title_fullStr Trial Prospector: Matching Patients with Cancer Research Studies Using an Automated and Scalable Approach
title_full_unstemmed Trial Prospector: Matching Patients with Cancer Research Studies Using an Automated and Scalable Approach
title_short Trial Prospector: Matching Patients with Cancer Research Studies Using an Automated and Scalable Approach
title_sort trial prospector: matching patients with cancer research studies using an automated and scalable approach
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4259509/
https://www.ncbi.nlm.nih.gov/pubmed/25506198
http://dx.doi.org/10.4137/CIN.S19454
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