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. 2002 Dec 19;347(25):1999-2009.
doi: 10.1056/NEJMoa021967.

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

Marc J van de Vijver  1 , 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 Witteveen, Annuska Glas, Leonie Delahaye, Tony van der Velde, Harry Bartelink, Sjoerd Rodenhuis, Emiel T Rutgers, Stephen H Friend, René Bernards
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Free article

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

Marc J van de Vijver et al. N Engl J Med. .
Free article

Abstract

Background: A more accurate means of prognostication in breast cancer will improve the selection of patients for adjuvant systemic therapy VSports手机版. .

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 V体育安卓版. 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 V体育ios版. 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. VSports最新版本.

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