Identifying long-term survivors among metastatic breast cancer patients undergoing primary tumor surgery
- Authors
- Yoo, Tae-Kyung; Chae, Byung Joo; Kim, Sei Joong; Lee, JungSun; Yoon, Tae In; Lee, Soo Jung; Park, Ho Yong; Park, Heung Kyu; Eom, Yong Hwa; Kim, Hyung Suk; Kim, Chang Jong; Shin, Man sik; You, Sun Hyong; Song, Byung Joo
- Issue Date
- Aug-2017
- Publisher
- Kluwer Academic Publishers
- Citation
- Breast Cancer Research and Treatment, v.165, no.1, pp.109 - 118
- Indexed
- SCIE
SCOPUS
- Journal Title
- Breast Cancer Research and Treatment
- Volume
- 165
- Number
- 1
- Start Page
- 109
- End Page
- 118
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/151801
- DOI
- 10.1007/s10549-017-4309-2
- ISSN
- 0167-6806
- Abstract
- Purpose
The prognostic role of primary tumor surgery in women with metastatic breast cancer at diagnosis is contentious. A subset of patients who will benefit from aggressive local treatment is needed to be identified. Using a nationwide database, we developed and validated a predictive model to identify long-term survivors among patients who had undergone primary tumor surgery.
Methods
A total of 150,043 patients were enrolled in the Korean Breast Cancer Registry between January 1990 and December 2014. Of these, 2332 (1.6%) presented with distant metastasis at diagnosis. Using Cox proportional hazards regression, we developed and validated a model that predicts survival in patients who undergo primary tumor surgery, based on the clinicopathological features of the primary tumor.
Results
A total of 2232 metastatic breast cancer patients were reviewed. Of these, 1541 (69.0%) patients had undergone primary tumor surgery. The 3-year survival rate was 62.6% in this subgroup. Among these patients, advanced T-stage, high-grade tumor, lymphovascular invasion, negative estrogen receptor status, high Ki-67 expression, and abnormal CA 15-3 and alkaline phosphatase levels were associated with poor survival. A prediction model was developed based on these factors, which successfully identified patients with remarkable survival (score 0–3, 3-year survival rate 87.3%). The clinical significance of the model was also validated with an independent dataset.
Conclusions
We have developed a predictive model to identify long-term survivors among women who undergo primary tumor surgery. This model will provide guidance to patients and physicians when considering surgery as a treatment modality for metastatic breast cancer.
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