Automated, High-Throughput Platform to Generate a High-Reliability, Comprehensive Rectal Cancer Database

Author:

Bhutiani Neal1ORCID,Yousef Mahmoud M.G.2ORCID,Yousef Abdelrahman2ORCID,Zeineddine Mohammad2ORCID,Knafl Mark3ORCID,Ratliff Olivia4ORCID,Fernando Uditha P.4,Turin Anastasia4,Zeineddine Fadl A.2,Jin Jeff4,Alfaro-Munoz Kristin2ORCID,Goldstein Drew5,Chang George J.1ORCID,Kopetz Scott2ORCID,Shen John Paul2ORCID,Uppal Abhineet1ORCID

Affiliation:

1. Department of Colon and Rectal Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX

2. Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX

3. Department Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX

4. Information Services, Enterprise Development & Integration, The University of Texas MD Anderson Cancer Center, Houston, TX

5. Syntropy Technologies LLC, Cambridge, MA

Abstract

PURPOSE Dynamic operations platforms allow for cross-platform data extraction, integration, and analysis, although application of these platforms to large-scale oncology enterprises has not been described. This study presents a pipeline for automated, high-fidelity extraction, integration, and validation of cross-platform oncology data in patients undergoing treatment for rectal cancer at a single, high-volume institution. METHODS A dynamic operations platform was used to identify patients with rectal cancer treated at MD Anderson Cancer Center between 2016 and 2022 who had magnetic resonance imaging (MRI) imaging and preoperative treatment details available in the electronic health record (EHR). Demographic, clinicopathologic, tumor mutation, radiographic, and treatment data were extracted from the EHR using a methodology adaptable to any disease site. Data accuracy was assessed by manual review. Accuracy before and after implementation of synoptic reporting was determined for MRI data. RESULTS A total of 516 patients with localized rectal cancer were included. In the era after institutional adoption of synoptic reports, the dynamic operations platform extracted T (tumor) category data from the EHR with 95% accuracy compared with 87% before the use of synoptic reports, and N (lymph node) category with 88% compared with 58%. Correct extraction of pelvic sidewall adenopathy was 94% compared with 78%, and extramural vascular invasion accuracy was 99% compared with 89%. Neoadjuvant chemotherapy and radiation data were 99% accurate for patients who had synoptic data sources. CONCLUSION Using dynamic operations platforms enables automated cross-platform integration of multiparameter oncology data with high fidelity in patients undergoing multimodality treatment for rectal cancer. These pipelines can be adapted to other solid tumors and, together with standardized reporting, can increase efficiency in clinical research and the translation of actionable findings toward optimizing patient outcomes.

Publisher

American Society of Clinical Oncology (ASCO)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3