Identifying long-term survivors among metastatic breast cancer patients undergoing primary tumor surgery

Breast Cancer Res Treat. 2017 Aug;165(1):109-118. doi: 10.1007/s10549-017-4309-2. Epub 2017 Jun 1.

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.

Publication types

  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Alkaline Phosphatase / analysis
  • Biomarkers, Tumor / analysis
  • Breast Neoplasms / mortality
  • Breast Neoplasms / pathology
  • Breast Neoplasms / surgery*
  • Cancer Survivors*
  • Chi-Square Distribution
  • Databases, Factual
  • Decision Support Techniques*
  • Female
  • Humans
  • Kaplan-Meier Estimate
  • Ki-67 Antigen / analysis
  • Mastectomy* / adverse effects
  • Mastectomy* / mortality
  • Middle Aged
  • Mucin-1 / analysis
  • Multivariate Analysis
  • Neoplasm Grading
  • Neoplasm Metastasis
  • Neoplasm Staging
  • Patient Selection
  • Predictive Value of Tests
  • Proportional Hazards Models
  • Receptors, Estrogen / analysis
  • Registries
  • Reproducibility of Results
  • Republic of Korea
  • Risk Assessment
  • Risk Factors
  • Time Factors
  • Treatment Outcome
  • Young Adult

Substances

  • Biomarkers, Tumor
  • Ki-67 Antigen
  • MUC1 protein, human
  • Mucin-1
  • Receptors, Estrogen
  • Alkaline Phosphatase