Relationship of patient age to pathologic features of the tumor and prognosis for patients with stage I or II breast cancer

J Clin Oncol. 1994 May;12(5):888-94. doi: 10.1200/JCO.1994.12.5.888.

Abstract

Purpose: This analysis was performed to clarify the relationship of young age at diagnosis to the pathologic features of the tumor and prognosis in patients with early-stage breast cancer.

Patients and methods: We retrospectively analyzed data from 1,398 patients with American Joint Committee on Cancer Staging stage I or II breast cancer treated by breast-conserving therapy between 1968 and 1985. One hundred seven patients were younger than 35 years at the time of diagnosis. The median follow-up duration for the 1,032 survivors was 99 months.

Results: Patients younger than 35 years had a significantly higher overall recurrence rate (P = .002), as well as a greater risk for developing distant metastases (P = .03), when compared with older patients. The cancers in younger patients more commonly showed factors associated with a worse prognosis (including grade 3 histology, lymphatic vessel invasion [LVI], necrosis, and estrogen receptor [ER] negativity) as compared with older patients. In a proportional hazards model that included clinical and treatment-related variables, as well as these pathologic features, age younger than 35 years remained a significant predictor for time to recurrence (relative risk [RR], 1.70), time to distant failure (RR, 1.60), and overall mortality (RR, 1.50).

Conclusion: Breast cancer patients younger than 35 years have a worse prognosis than older patients. This difference is only partially explained by a higher frequency of adverse pathologic factors seen in younger patients.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Actuarial Analysis
  • Adult
  • Age Factors
  • Aged
  • Breast Neoplasms / mortality*
  • Breast Neoplasms / pathology*
  • Breast Neoplasms / therapy
  • Female
  • Humans
  • Middle Aged
  • Neoplasm Metastasis
  • Neoplasm Staging
  • Prognosis
  • Proportional Hazards Models
  • Retrospective Studies
  • Survival Analysis