Application of the Adjuvant! Online Model to Korean Breast Cancer Patients: An Assessment of Prognostic Accuracy and Development of an Alternative Prognostic Tool
- Authors
- Jung, Minkyu; Choi, Eun Hee; Nam, Chung Mo; Rha, Sun Young; Jeung, Hei Cheul; Lee, Soo Hyun; Yang, Woo Ick; Roh, Jae Kyung; Chung, Hyun Cheol
- Issue Date
- Aug-2013
- Publisher
- SPRINGER
- Citation
- ANNALS OF SURGICAL ONCOLOGY, v.20, no.8, pp 2615 - 2624
- Pages
- 10
- Indexed
- SCI
SCIE
SCOPUS
- Journal Title
- ANNALS OF SURGICAL ONCOLOGY
- Volume
- 20
- Number
- 8
- Start Page
- 2615
- End Page
- 2624
- URI
- https://scholarworks.korea.ac.kr/kumedicine/handle/2020.sw.kumedicine/43573
- DOI
- 10.1245/s10434-013-2956-z
- ISSN
- 1068-9265
1534-4681
- Abstract
- Adjuvant! Online (AOL) is a Web-accessible risk-assessment model that predicts the mortality and the benefits of adjuvant therapy for breast cancer.
Using the Yonsei Tumor Registry database, patients with T1-3, N0-3, M0 breast cancer who were treated at the Yonsei Cancer Center between 1986 and 1999 were entered into AOL version 8.0 to calculate survival.
The median age of the study population was 45 years (range, 23-76 years) and the median follow-up duration was 10.8 years (range, 0.1-25.9 years) for all 699 patients. AOL significantly overestimated overall survival (OS) (by 11.1 %, P < 0.001), breast cancer-specific survival (BCSS) (by 11.6 %, P < 0.001), and event free-free survival (EFS) (by 9.25 %, P < 0.001) in Korean patients. Therefore, we developed a Korean version of AOL (KAOL), which is a new model for prognosis based on AOL's parameters. The observed 10-year OS (61.4 %), BCSS (62.3 %), and EFS (59.1 %) and the KAOL predicted OS (61.5 %), BCSS (63.5 %) and EFS (57.6 %) were not different (P = 0.976, P = 0.771, and P = 0.674, respectively).
AOL was not found to be suitable in Korean patients with breast cancer. The newly developed KAOL accurately predicted 10-year outcomes in Korean breast cancer patients.
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- Appears in
Collections - 2. Clinical Science > Department of Medical Oncology and Hematology > 1. Journal Articles
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