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

MJ Van De Vijver, YD He, LJ Van't Veer… - … England Journal of …, 2002 - Mass Medical Soc
MJ Van De Vijver, YD He, LJ Van't Veer, H Dai, AAM Hart, DW Voskuil, GJ Schreiber…
New England Journal of Medicine, 2002Mass Medical Soc
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 …
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.
The New England Journal Of Medicine