ArticlePloS one2017
A prediction model for advanced colorectal neoplasia in an asymptomatic screening population.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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16 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.
- Risk Scores for Predicting Advanced Colorectal Neoplasia in the Average-risk Population: A Systematic Review and Meta-analysis.The American journal of gastroenterology · 2018Pooled it
- Association Between Colorectal Neoplasia and Subclinical Coronary Atherosclerosis in Asymptomatic Individuals.Journal of Korean medical science · 2026Article
- Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review.JMIR medical informatics · 2023Review
- Prediction algorithm for gastric cancer in a general population: A validation study.Cancer medicine · 2023Article
- Colorectal Cancer Risk Assessment and Precision Approaches to Screening: Brave New World or Worlds Apart?Gastroenterology · 2023Review
- Deep learning approach to detection of colonoscopic information from unstructured reports.BMC medical informatics and decision making · 2023Article
- A deep learning and natural language processing-based system for automatic identification and surveillance of high-risk patients undergoing upper endoscopy: A multicenter study.EClinicalMedicine · 2022Article
- External validation of models for predicting risk of colorectal cancer using the China Kadoorie Biobank.BMC medicine · 2022Article
- Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review.JMIR medical informatics · 2022Review
- Risk factors and prediction algorithm for advanced neoplasia on screening colonoscopy for average-risk individuals.Therapeutic advances in gastroenterology · 2022Article
- Evolving Role and Future Directions of Natural Language Processing in Gastroenterology.Digestive diseases and sciences · 2021Review
- Risk prediction rule for advanced neoplasia on screening colonoscopy for average-risk individuals.World journal of gastroenterology · 2020Article
- Head-to-Head Comparison of the Performance of 17 Risk Models for Predicting Presence of Advanced Neoplasms in Colorectal Cancer Screening.The American journal of gastroenterology · 2019Article
- Article
- Colorectal cancer screening from 45 years of age: Thesis, antithesis and synthesis.World journal of gastroenterology · 2019Review
- An Automated Feature Engineering for Digital Rectal Examination Documentation using Natural Language Processing.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAn electronic medical record (EMR) database of a large unselected population who received screening colonoscopies may minimize sampling error and represent real-world estimates of risk for screening target lesions of advanced colorectal neoplasia (CRN). Our aim was to develop and validate a prediction model for assessing the probability of advanced CRN using a clinical data warehouse.
methodsA total of 49,450 screenees underwent their first colonoscopy as part of a health check-up from 2002 to 2012 at Samsung Medical Center, and the dataset was constructed by means of natural language processing from the computerized EMR system. The screenees were randomized into training and validation sets. The prediction model was developed using logistic regression. The model performance was validated and compared with existing models using area under receiver operating curve (AUC) analysis.
resultsIn the training set, age, gender, smoking duration, drinking frequency, and aspirin use were identified as independent predictors for advanced CRN (adjusted P < .01). The developed model had good discrimination (AUC = 0.726) and was internally validated (AUC = 0.713). The high-risk group had a 3.7-fold increased risk of advanced CRN compared to the low-risk group (1.1% vs. 4.0%, P < .001). The discrimination performance of the present model for high-risk patients with advanced CRN was better than that of the Asia-Pacific Colorectal Screening score (AUC = 0.678, P < .001) and Schroy's CAN index (AUC = 0.672, P < .001).
conclusionThe present 5-item risk model can be calculated readily using a simple questionnaire and can identify the low- and high-risk groups of advanced CRN at the first screening colonoscopy. This model may increase colorectal cancer risk awareness and assist healthcare providers in encouraging the high-risk group to undergo a colonoscopy.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.