Korean J Urol Oncol.
2021 Nov;19(4):232-243. 10.22465/kjuo.2021.19.4.232.
Construction of a Retrospective Cohort to Observe 10-Year Urologic Cancer Treatment Trends at the Biggest Medical Center of South Korea
- Choi SY
1,2,3 - Kim HH1,4
- Lim B1
- Lee JW5
- Kim YS6
- Kim JK7
- Lee JL8
- Cho YM9
- You D1
- Jeong IG1
- Song C1
- Hong JH1
- Kim CS1
- Ahn H1
- Hong B1
- Affiliations
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- 1Department of Urology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
- 2Department of Urology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea
- 3Biomedical Research Institute, Chung-Ang University Hospital, Seoul, Korea
- 4Department of Biomedical System Informatics, Yonsei University College of Medicine, Seoul, Korea
- 5Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
- 6Department of Radiation Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
- 7Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
- 8Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
- 9Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
- KMID: 2522844
- DOI: http://doi.org/10.22465/kjuo.2021.19.4.232
Abstract
- Purpose
To construct a urologic cancer database using a standardized, reproducible method, and to assess preliminary characteristics of this cohort.
Materials and Methods
Patients with prostate, bladder, and kidney cancers who were enrolled with diagnostic codes in the electronic medical record (EMR) at Asan Medical Center from 2007–2016 were included. Research Electronic Data Capture (REDCap) was used to design the Asan Medical Center-Urologic Cancer Database (AMC-UCD). The process included developing a data dictionary, applying branching logic, mapping clinical data warehouse structures, alpha testing, clinical record summary testing, creating “standards of procedure,” importing data, and entering data. Descriptive statistics were used to identify rates of surgeries and numbers of patients.
Results
Clinical variables (n=407) were selected to develop a data dictionary from REDCap. In total, 20,198 urologic cancer patients visited our institution from 2007–2016 (bladder cancer, 4,616; kidney cancer, 5,750; prostate cancer, 10,330). The overall numbers of patients and surgeries increased over time, with robotic surgeries rapidly growing over a decade. The most common treatment for urologic cancer was surgery, followed by chemotherapy and radiation therapy.
Conclusions
Using a standardized method, the AMC-UCD fosters multidisciplinary research. This constructed database provides access to clinical statistics to effectively assist research. Preliminary data should be refined through EMR chart review. The successful organization of data from 2007–2016 provides a framework for future periods of investigation and prospective models.
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