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Natural Language Processing of Computed Tomography Reports to Label Metastatic Phenotypes With Prognostic Significance in Patients With Colorectal Cancer.

Authors :
Causa Andrieu P
Golia Pernicka JS
Yaeger R
Lupton K
Batch K
Zulkernine F
Simpson AL
Taya M
Gazit L
Nguyen H
Nicholas K
Gangai N
Sevilimedu V
Dickinson S
Paroder V
Bates DDB
Do R
Source :
JCO clinical cancer informatics [JCO Clin Cancer Inform] 2022 Sep; Vol. 6, pp. e2200014.
Publication Year :
2022

Abstract

Purpose: Natural language processing (NLP) applied to radiology reports can help identify clinically relevant M1 subcategories of patients with colorectal cancer (CRC). The primary purpose was to compare the overall survival (OS) of CRC according to American Joint Committee on Cancer TNM staging and explore an alternative classification. The secondary objective was to estimate the frequency of metastasis for each organ.<br />Methods: Retrospective study of CRC who underwent computed tomography (CT) chest, abdomen, and pelvis between July 1, 2009, and March 26, 2019, at a tertiary cancer center, previously labeled for the presence or absence of metastasis by an NLP prediction model. Patients were classified in M0, M1a, M1b, and M1c (American Joint Committee on Cancer), or an alternative classification on the basis of the metastasis organ number: M1, single; M2, two; M3, three or more organs. Cox regression models were used to estimate hazard ratios; Kaplan-Meier curves were used to visualize survival curves using the two M1 subclassifications.<br />Results: Nine thousand nine hundred twenty-eight patients with a total of 48,408 CT chest, abdomen, and pelvis reports were included. On the basis of NLP prediction, the median OS of M1a, M1b, and M1c was 4.47, 1.72, and 1.52 years, respectively. The median OS of M1, M2, and M3 was 4.24, 2.05, and 1.04 years, respectively. Metastases occurred most often in liver (35.8%), abdominopelvic lymph nodes (32.9%), lungs (29.3%), peritoneum (22.0%), thoracic nodes (19.9%), bones (9.2%), and pelvic organs (7.5%). Spleen and adrenal metastases occurred in < 5%.<br />Conclusion: NLP applied to a large radiology report database can identify clinically relevant metastatic phenotypes and be used to investigate new M1 substaging for CRC. Patients with three or more metastatic disease organs have the worst prognosis, with an OS of 1 year.<br />Competing Interests: Rona YaegerConsulting or Advisory Role: Array BioPharma, Natera, Mirati TherapeuticsResearch Funding: Array BioPharma (Inst), Boehringer Ingelheim (Inst), Pfizer (Inst), Mirati Therapeutics (Inst) Farhana ZulkernineResearch Funding: Pfizer (Inst), Medlior (Inst) Lior GazitStock and Other Ownership Interests: Within HealthConsulting or Advisory Role: Within Health Huy NguyenEmployment: Caremark LLC David D.B. BatesOther Relationship: GE Healthcare (Inst) Richard DoHonoraria: ALK (I), Genentech (I)Consulting or Advisory Role: DBV Technologies (I), Bayer, GE HealthcarePatents, Royalties, Other Intellectual Property: UptoDate chapters on Food Allergy (I)No other potential conflicts of interest were reported.

Details

Language :
English
ISSN :
2473-4276
Volume :
6
Database :
MEDLINE
Journal :
JCO clinical cancer informatics
Publication Type :
Academic Journal
Accession number :
36103642
Full Text :
https://doi.org/10.1200/CCI.22.00014