Skip to main navigation Skip to search Skip to main content

A gene-expression signature as a predictor of survival in breast cancer

  • Marc J. van de Vijver
  • , Yudong D. He
  • , Laura J. van't Veer
  • , Hongyue Dai
  • , Augustinus A. M. Hart
  • , Dorien W. Voskuil
  • , George J. Schreiber
  • , Johannes L. Peterse
  • , Chris Roberts
  • , Matthew J. Marton
  • , Mark Parrish
  • , Douwe Atsma
  • , Anke T. Witteveen
  • , Annuska Glas
  • , Leonie Delahaye
  • , Tony van der Velde
  • , Harry Bartelink
  • , Sjoerd Rodenhuis
  • , Emiel T. Rutgers
  • , Stephen H. Friend
  • René Bernards
  • pre-AMC

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

BACKGROUND: A more accurate means of prognostication in breast cancer will improve the selection of patients for adjuvant systemic therapy. METHODS: Using microarray analysis to evaluate our previously established 70-gene prognosis profile, we classified a series of 295 consecutive patients with primary breast carcinomas as having a gene-expression signature associated with either a poor prognosis or a good prognosis. All patients had stage I or II breast cancer and were younger than 53 years old; 151 had lymph-node-negative disease, and 144 had lymph-node-positive disease. We evaluated the predictive power of the prognosis profile using univariable and multivariable statistical analyses. RESULTS: Among the 295 patients, 180 had a poor-prognosis signature and 115 had a good-prognosis signature, and the mean (+/-SE) overall 10-year survival rates were 54.6+/-4.4 percent and 94.5+/-2.6 percent, respectively. At 10 years, the probability of remaining free of distant metastases was 50.6+/-4.5 percent in the group with a poor-prognosis signature and 85.2+/-4.3 percent in the group with a good-prognosis signature. The estimated hazard ratio for distant metastases in the group with a poor-prognosis signature, as compared with the group with the good-prognosis signature, was 5.1 (95 percent confidence interval, 2.9 to 9.0; P <0.001). This ratio remained significant when the groups were analyzed according to lymph-node status. Multivariable Cox regression analysis showed that the prognosis profile was a strong independent factor in predicting disease outcome. CONCLUSIONS: The gene-expression profile we studied is a more powerful predictor of the outcome of disease in young patients with breast cancer than standard systems based on clinical and histologic criteria
Original languageEnglish
Pages (from-to)1999-2009
JournalNew England journal of medicine
Volume347
Issue number25
DOIs
Publication statusPublished - 2002
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Fingerprint

Dive into the research topics of 'A gene-expression signature as a predictor of survival in breast cancer'. Together they form a unique fingerprint.

Cite this