Advertisement

Annals of Surgical Oncology

, Volume 20, Issue 8, pp 2615–2624 | Cite as

Application of the Adjuvant! Online Model to Korean Breast Cancer Patients: An Assessment of Prognostic Accuracy and Development of an Alternative Prognostic Tool

  • Minkyu Jung
  • Eun Hee Choi
  • Chung Mo Nam
  • Sun Young Rha
  • Hei Cheul Jeung
  • Soo Hyun Lee
  • Woo Ick Yang
  • Jae Kyung Roh
  • Hyun Cheol ChungEmail author
Breast Oncology

Abstract

Background

Adjuvant! Online (AOL) is a Web-accessible risk-assessment model that predicts the mortality and the benefits of adjuvant therapy for breast cancer.

Methods

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.

Results

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).

Conclusions

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.

Keywords

Breast Cancer Overall Survival Breast Cancer Patient Breast Conserve Surgery Korean Patient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgment

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.

Supplementary material

10434_2013_2956_MOESM1_ESM.doc (44 kb)
Supplementary material 1 (DOC 44 kb)

References

  1. 1.
    Eifel P, Axelson JA, et al; National Institutes of Health Consensus Development Panel. National Institutes of Health Consensus Development Conference Statement: adjuvant therapy for breast cancer, November 1–3, 2000. J Natl Cancer Inst. 2001;93:979–89.PubMedCrossRefGoogle Scholar
  2. 2.
    Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet. 2005;365:1687–717.CrossRefGoogle Scholar
  3. 3.
    Goldhirsch A, Glick JH, Gelber RD, Coates AS, Senn HJ. Meeting highlights: International consensus panel on the treatment of primary breast cancer. Seventh international conference on adjuvant therapy of primary breast cancer. J Clin Oncol. 2001;19:3817–27.PubMedGoogle Scholar
  4. 4.
    Galea MH, Blamey RW, Elston CE, Ellis IO. The Nottingham prognostic index in primary breast cancer. Breast Cancer Res Treat. 1992;22:207–19.PubMedCrossRefGoogle Scholar
  5. 5.
    Ravdin PM, Siminoff LA, Davis GJ, et al. Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol. 2001;19:980–91.PubMedGoogle Scholar
  6. 6.
    Olivotto IA, Bajdik CD, Ravdin PM, et al. Population-based validation of the prognostic model Adjuvant! for early breast cancer. J Clin Oncol. 2005;23:2716–25.PubMedCrossRefGoogle Scholar
  7. 7.
    Mook S, Schmidt MK, Rutgers EJ, et al. Calibration and discriminatory accuracy of prognosis calculation for breast cancer with the online Adjuvant! program: a hospital-based retrospective cohort study. Lancet Oncol. 2009;10:1070–6.PubMedCrossRefGoogle Scholar
  8. 8.
    Parkin DM, Bray F, Ferlay J, Pisani P. Global cancer statistics, 2002. CA Cancer J Clin. 2005;55:74–108.PubMedCrossRefGoogle Scholar
  9. 9.
    Kamangar F, Dores GM, Anderson WF. Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world. J Clin Oncol. 2006;24:2137–50.PubMedCrossRefGoogle Scholar
  10. 10.
    Porter P. “Westernizing” women’s risks? Breast cancer in lower-income countries. N Engl J Med. 2008;358:213–6.PubMedCrossRefGoogle Scholar
  11. 11.
    Yoo KY, Kang D, Park SK, et al. Epidemiology of breast cancer in Korea: occurrence, high-risk groups, and prevention. J Korean Med Sci. 2002;17:1–6.PubMedGoogle Scholar
  12. 12.
    Shin HR, Won YJ, Jung KW, et al. Nationwide cancer incidence in Korea, 1999–2001: first result using the national cancer incidence database. Cancer Res Treat. 2005;37:325–31.PubMedCrossRefGoogle Scholar
  13. 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. 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. 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.
  16. 16.
    Agarwal G, Pradeep PV, Aggarwal V, Yip C, Cheung PS. Spectrum of breast cancer in Asian women. World J Surg. 2007;31:1031–40.PubMedCrossRefGoogle Scholar
  17. 17.
    Jung M, Shin HJ, Rha SY, et al. The clinical outcome of chemotherapy-induced amenorrhea in premenopausal young patients with breast cancer with long-term follow-up. Ann Surg Oncol. 2010;17:3259–68.PubMedCrossRefGoogle Scholar
  18. 18.
    Harrell FE, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361–87.PubMedCrossRefGoogle Scholar
  19. 19.
    Klein JP, Moeschberger ML. Survival analysis: techniques for censored and truncated data. 2nd ed. New York: Springer; 2003.Google Scholar
  20. 20.
    Agresti A. An introduction to categorical data analysis. 2nd ed. Hoboken: Wiley; 2007.Google Scholar
  21. 21.
    Campbell HE, Taylor MA, Harris AL, Gray AM. An investigation into the performance of the Adjuvant! Online prognostic programme in early breast cancer for a cohort of patients in the United Kingdom. Br J Cancer. 2009;101:1074–84.PubMedCrossRefGoogle Scholar
  22. 22.
    Han W, Ko S, Jeong J, et al. Poor outcome of hormone receptor-positive breast cancer at very young age is due to tamoxifen resistance: nationwide survival data in Korea—a report from the Korean Breast Cancer Society. J Clin Oncol. 2007;25:2360–8.PubMedCrossRefGoogle Scholar
  23. 23.
    Goldhirsch A, Coates AS, Werner ID, et al. Is chemotherapy alone adequate for young women with oestrogen-receptor-positive breast cancer? Lancet. 2000;355:1869–74.PubMedCrossRefGoogle Scholar
  24. 24.
    Tan BK, Lim GH, Czene K, Hall P, Chia KS. Do Asian breast cancer patients have poorer survival than their western counterparts? A comparison between Singapore and Stockholm. Breast Cancer Res. 2009;11:R4.PubMedCrossRefGoogle Scholar
  25. 25.
    Lim S, Back M, Quek E, Iau P, Putti T, Wong JE. Clinical observations from a breast cancer registry in Asian women. World J Surg. 2007;31:1387–92.PubMedCrossRefGoogle Scholar
  26. 26.
    Chu KC, Anderson WF, Fritz A, Ries LA, Brawley OW. Frequency distributions of breast cancer characteristics classified by estrogen receptor and progesterone receptor status for eight racial/ethnic groups. Cancer. 2001;92:37–45.PubMedCrossRefGoogle Scholar
  27. 27.
    Chow LW, Ho P. Hormonal receptor determination of 1,052 Chinese breast cancers. J Surg Oncol. 2000;75:172–5.PubMedCrossRefGoogle Scholar
  28. 28.
    Chuang E, Christos P, Flam A, et al. Breast cancer subtypes in Asian-Americans differ according to Asian ethnic group. J Immigr Minor Health. 2012;14(5):754–8.PubMedCrossRefGoogle Scholar
  29. 29.
    Telli ML, Chang ET, Kurian AW, et al. Asian ethnicity and breast cancer subtypes: a study from the California Cancer Registry. Breast Cancer Res Treat. 2011;127:471–8.PubMedCrossRefGoogle Scholar
  30. 30.
    Bhoo Pathy N, Yip C, Hartman M, et al. Adjuvant! Online is overoptimistic in predicting survival of Asian breast cancer patients. Eur J Cancer. 2012;48:982–9.PubMedCrossRefGoogle Scholar

Copyright information

© Society of Surgical Oncology 2013

Authors and Affiliations

  • Minkyu Jung
    • 1
    • 2
    • 3
  • Eun Hee Choi
    • 4
  • Chung Mo Nam
    • 4
  • Sun Young Rha
    • 1
    • 2
    • 3
    • 6
  • Hei Cheul Jeung
    • 1
    • 2
    • 3
  • Soo Hyun Lee
    • 1
    • 2
  • Woo Ick Yang
    • 5
    • 6
  • Jae Kyung Roh
    • 1
    • 2
    • 3
    • 6
  • Hyun Cheol Chung
    • 1
    • 2
    • 3
    • 6
    Email author
  1. 1.Division of Medical Oncology, Department of Internal MedicineYonsei University College of MedicineSeoulKorea
  2. 2.Yonsei Cancer CenterYonsei University College of MedicineSeoulKorea
  3. 3.Cancer Metastasis Research CenterYonsei University College of MedicineSeoulKorea
  4. 4.Department of BiostatisticsYonsei University College of MedicineSeoulKorea
  5. 5.Department of PathologyYonsei University College of MedicineSeoulKorea
  6. 6.BK2 1 Project for Medical ScienceYonsei University College of MedicineSeoulKorea

Personalised recommendations