Feasibility of Large-Scale Identification of Sessile Serrated Polyp Patients Using Electronic Records: A Utah Study.
Dig Dis Sci
; 62(6): 1455-1463, 2017 06.
Article
em En
| MEDLINE
| ID: mdl-28315031
ABSTRACT
BACKGROUND/AIMS:
The serrated pathway accounts for 15-25% of sporadic colorectal cancer (CRC). In our study, we sought to accurately characterize sessile serrated polyps (SSP) in a population by electronically interrogating colonoscopy patients' endoscopy and pathology reports using a rules-based text search of pre-defined SSP-related terms. To this aim, we compared a sample of putative SSP and hyperplastic polyps (HP) using our algorithm to a determination of SSP or HP by pathologist and molecular examination to determine the feasibility of large-scale identification of SSP in electronic medical records.METHODS:
In 23,990 endoscopy reports from colonoscopies with pathology performed at a University of Utah Healthcare facility in 2000-2012, we identified serrated lesions and categorized each as putative SSP or HP using a text search algorithm. We obtained 93 tissue samples for histologic and molecular analysis.RESULTS:
Serrated polyps were categorized as putative SSP (N = 920) and putative HP (N = 7159) by text search algorithm. Histologic examination of 93 samples identified 37 SSP, 11 probable SSP, and 45 HP. Of 26 putative SSP, 25 were SSP/probable SSP (96%) by histology. Of 67 putative HP, 44 were HP (66%) by histology. Reducing size criterion from ≥1 to ≥5 mm in the search algorithm caused improved sensitivity (77.1%) without decline in specificity (97.8%).CONCLUSIONS:
A simple rules-based search to identify SSP provides "proof of principle" that SSP can be identified in a large electronic record set. Pilot data indicate defining large, right-sided polyps as ≥5 mm provides adequate sensitivity to detect SSP from electronic records while maintaining high specificity.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
DNA de Neoplasias
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Neoplasias Colorretais
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Adenoma
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Pólipos do Colo
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Registros Eletrônicos de Saúde
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Mineração de Dados
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
Limite:
Aged
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Female
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Humans
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Male
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Middle aged
País como assunto:
America do norte
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article