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CLRM-04 DEVELOPING A WORD LEXICON FOR VENOUS THROMBOEMBOLISM DATA ANNOTATION USING RADIOLOGY REPORTS IN GLIOBLASTOMA PATIENTS - LINKING LARGE-SCALE DATA SETS TO EXPAND CLINICAL FEATURES FOR AI
Patients with gliomas, particularly glioblastomas (GBM), have a higher risk of developing venous thromboembolism (VTE), correlating with overall survival (OS). Artificial intelligence (AI) approaches that employ VTE as a clinical feature in brain tumor patients is understudied due to the difficulty...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402303/ http://dx.doi.org/10.1093/noajnl/vdad070.027 |
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author | Jagasia, Sarisha Krauze, Andra |
author_facet | Jagasia, Sarisha Krauze, Andra |
author_sort | Jagasia, Sarisha |
collection | PubMed |
description | Patients with gliomas, particularly glioblastomas (GBM), have a higher risk of developing venous thromboembolism (VTE), correlating with overall survival (OS). Artificial intelligence (AI) approaches that employ VTE as a clinical feature in brain tumor patients is understudied due to the difficulty in analyzing electronic health records (EHR). Data expansion by creating a word lexicon for natural language processing (NLP) of free-text clinical reports will allow exposure of VTE for the classification of large-scale data sets, NLP, and AI. Patients with a pathologic diagnosis of GBM (2005-2021) were screened for the development of VTE based on radiology free-text reports (ultrasound (US) of extremities and Computed Topography-pulmonary angiogram (CT)). Kaplan-Meier survival analyses about overall survival (OS) and progression-free survival (PFS) were generated for VTE. 163 patients (mean age = 56.1 ± 12.1, 65% male) were included, 48 (29.4%) were screened for VTE following clinical suspicion on history or physical exam, and 15 (9.2%) were found to have a VTE. Screening methods were ultrasound 83.3% (40) or CT 13.9% (6), or both 4.6% (2). 28.6% (12) of US and 37.5% (3) of CT resulted in a positive VTE diagnosis. The words “partial”, “residual”, “complete”, “critical” or “clotted” when used as an “or” boolean statement applied to US and CT radiology reports identified ~93% of the patients with VTE. Patients with VTE had worse OS (median 14 vs. 19 months, p = .0189) and PFS (median 6 vs. 9 months, p = .0239) than patients without VTE, indicating underlying pathology associated with both prevalence of VTE and tumor burden. US and CT yield a similar percentage of positive VTE findings while employing different terms to characterize VTE. We confirm that patients with VTE have poorer outcomes and present a word combination that identifies patients with VTE in large-scale radiology report data. |
format | Online Article Text |
id | pubmed-10402303 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-104023032023-08-05 CLRM-04 DEVELOPING A WORD LEXICON FOR VENOUS THROMBOEMBOLISM DATA ANNOTATION USING RADIOLOGY REPORTS IN GLIOBLASTOMA PATIENTS - LINKING LARGE-SCALE DATA SETS TO EXPAND CLINICAL FEATURES FOR AI Jagasia, Sarisha Krauze, Andra Neurooncol Adv Final Category: Clinical Research Methods Patients with gliomas, particularly glioblastomas (GBM), have a higher risk of developing venous thromboembolism (VTE), correlating with overall survival (OS). Artificial intelligence (AI) approaches that employ VTE as a clinical feature in brain tumor patients is understudied due to the difficulty in analyzing electronic health records (EHR). Data expansion by creating a word lexicon for natural language processing (NLP) of free-text clinical reports will allow exposure of VTE for the classification of large-scale data sets, NLP, and AI. Patients with a pathologic diagnosis of GBM (2005-2021) were screened for the development of VTE based on radiology free-text reports (ultrasound (US) of extremities and Computed Topography-pulmonary angiogram (CT)). Kaplan-Meier survival analyses about overall survival (OS) and progression-free survival (PFS) were generated for VTE. 163 patients (mean age = 56.1 ± 12.1, 65% male) were included, 48 (29.4%) were screened for VTE following clinical suspicion on history or physical exam, and 15 (9.2%) were found to have a VTE. Screening methods were ultrasound 83.3% (40) or CT 13.9% (6), or both 4.6% (2). 28.6% (12) of US and 37.5% (3) of CT resulted in a positive VTE diagnosis. The words “partial”, “residual”, “complete”, “critical” or “clotted” when used as an “or” boolean statement applied to US and CT radiology reports identified ~93% of the patients with VTE. Patients with VTE had worse OS (median 14 vs. 19 months, p = .0189) and PFS (median 6 vs. 9 months, p = .0239) than patients without VTE, indicating underlying pathology associated with both prevalence of VTE and tumor burden. US and CT yield a similar percentage of positive VTE findings while employing different terms to characterize VTE. We confirm that patients with VTE have poorer outcomes and present a word combination that identifies patients with VTE in large-scale radiology report data. Oxford University Press 2023-08-04 /pmc/articles/PMC10402303/ http://dx.doi.org/10.1093/noajnl/vdad070.027 Text en © The Author(s) 2023. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Final Category: Clinical Research Methods Jagasia, Sarisha Krauze, Andra CLRM-04 DEVELOPING A WORD LEXICON FOR VENOUS THROMBOEMBOLISM DATA ANNOTATION USING RADIOLOGY REPORTS IN GLIOBLASTOMA PATIENTS - LINKING LARGE-SCALE DATA SETS TO EXPAND CLINICAL FEATURES FOR AI |
title | CLRM-04 DEVELOPING A WORD LEXICON FOR VENOUS THROMBOEMBOLISM DATA ANNOTATION USING RADIOLOGY REPORTS IN GLIOBLASTOMA PATIENTS - LINKING LARGE-SCALE DATA SETS TO EXPAND CLINICAL FEATURES FOR AI |
title_full | CLRM-04 DEVELOPING A WORD LEXICON FOR VENOUS THROMBOEMBOLISM DATA ANNOTATION USING RADIOLOGY REPORTS IN GLIOBLASTOMA PATIENTS - LINKING LARGE-SCALE DATA SETS TO EXPAND CLINICAL FEATURES FOR AI |
title_fullStr | CLRM-04 DEVELOPING A WORD LEXICON FOR VENOUS THROMBOEMBOLISM DATA ANNOTATION USING RADIOLOGY REPORTS IN GLIOBLASTOMA PATIENTS - LINKING LARGE-SCALE DATA SETS TO EXPAND CLINICAL FEATURES FOR AI |
title_full_unstemmed | CLRM-04 DEVELOPING A WORD LEXICON FOR VENOUS THROMBOEMBOLISM DATA ANNOTATION USING RADIOLOGY REPORTS IN GLIOBLASTOMA PATIENTS - LINKING LARGE-SCALE DATA SETS TO EXPAND CLINICAL FEATURES FOR AI |
title_short | CLRM-04 DEVELOPING A WORD LEXICON FOR VENOUS THROMBOEMBOLISM DATA ANNOTATION USING RADIOLOGY REPORTS IN GLIOBLASTOMA PATIENTS - LINKING LARGE-SCALE DATA SETS TO EXPAND CLINICAL FEATURES FOR AI |
title_sort | clrm-04 developing a word lexicon for venous thromboembolism data annotation using radiology reports in glioblastoma patients - linking large-scale data sets to expand clinical features for ai |
topic | Final Category: Clinical Research Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402303/ http://dx.doi.org/10.1093/noajnl/vdad070.027 |
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