The establishment of KORCC (Korean Renal Cell Carcinoma) database

Seok Soo Byun, Sung Kyu Hong, Sangchul Lee, Ha Rim Kook, Eunsik Lee, Hyeon Hoe Kim, Cheol Kwak, Ja Hyeon Ku, Chang Wook Jeong, Ji Youl Lee, Sung Hoo Hong, Yong June Kim, Eu Chang Hwang, Tae Gyun Kwon, Tae Hwan Kim, Seok Ho Kang, Sung Han Kim, Jinsoo Chung

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Purpose: The purpose of this article is to report establishment of the 1st Web-based database (DB) system to collect renal cell carcinoma (RCC) data in Korea. Materials and Methods: The new Web-based DB system was established to collect basic demographic and clinicopahtological characteristics of a large cohort of patients with RCC in Korea. Data from a total of 6,849 patients were collected from 8 tertiary care hospitals that agreed to participate in organizing the Korean Renal Cell Carcinoma (KORCC) study group as of 1 July 2015. Basic demographic and clinicopathological characteristics were collected. The data of patients who underwent surgical treatments were analyzed to characterize Korean RCC. Results: We established the 1st Web-based DB of Korean RCC, a database comprising renal mass management cases from multiple centers in Korea. The data of 5,281 patients who underwent surgical management (mean follow-up, 32 months) were analyzed. The most common symptom was incidentally detected renal mass (76.9%). Clinical T1a was the most common (54.3%) stage and mean tumor size was 4.8±4.2 cm. Radical nephrectomy accounted for 62.7% of cases and an open approach was used in 50.7% and 52.2% of radical and partial nephrectomies, respectively. The 5-year overall, cancer-specific and recurrence-free survival rates were 88.1%, 92.2%, and 88.0%, respectively. Conclusions: We report the 1st establishment of a Web-based DB system to collect RCC data in Korea. This DB system will provide a solid basis for the characterization of Korean RCC.

Original languageEnglish
Pages (from-to)50-57
Number of pages8
JournalInvestigative and Clinical Urology
Volume57
Issue number1
DOIs
StatePublished - Jan 2016

Keywords

  • Database
  • Kidney neoplasms
  • Population characteristics

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