Application of the Adjuvant! Online Model to Korean Breast Cancer Patients: An Assessment of Prognostic Accuracy and Development of an Alternative Prognostic Tool
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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.
KeywordsBreast Cancer Overall Survival Breast Cancer Patient Breast Conserve Surgery Korean Patient
This work was supported in part by the Korea Science and Engineering Fund (KOSEF) through the Cancer Metastasis Research Center (CMRC) at Yonsei University College of Medicine. (R11-2000-082-03002-0.)
Conflict of interest
The authors declare no conflict of interest.
- 13.Lee TH, Paik NS, Kim YK. Carcinoma of the breast in women 35 years of age or less. Cancer Res Treat. 1992;24:834–9.Google Scholar
- 14.Jeong J. Korean Breast Cancer Society. Nationwide Korean breast cancer data of 2004 using breast cancer registration program. J Breast Cancer. 2006;9:151–61.Google Scholar
- 15.Ries LAG, Melbert D, Krapcho M, et al.: SEER cancer statistics review, 1975–2004. http://seer.cancer.gov/csr/1975_2004/ (2007). Accessed 1 June 2009.
- 19.Klein JP, Moeschberger ML. Survival analysis: techniques for censored and truncated data. 2nd ed. New York: Springer; 2003.Google Scholar
- 20.Agresti A. An introduction to categorical data analysis. 2nd ed. Hoboken: Wiley; 2007.Google Scholar