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Time-dependent effects on survival in breast carcinoma†
Results of 20 years of follow-up from the Swedish two-county study
Article first published online: 23 FEB 2004
Copyright © 2004 American Cancer Society
Volume 100, Issue 7, pages 1331–1336, 1 April 2004
How to Cite
Warwick, J., Tabàr, L., Vitak, B. and Duffy, S. W. (2004), Time-dependent effects on survival in breast carcinoma. Cancer, 100: 1331–1336. doi: 10.1002/cncr.20140
See related editorial on pages 1327–30 and accompanying article on pages 1337–44, this issue.
- Issue published online: 18 MAR 2004
- Article first published online: 23 FEB 2004
- Manuscript Revised: 18 SEP 2003
- Manuscript Accepted: 18 SEP 2003
- Manuscript Received: 21 JUL 2003
- breast carcinoma;
- Cox regression analysis;
- prognostic factors
Tumor size, lymph node status, and histologic grade are reported to be important predictors of survival in the first 5 years after the diagnosis of invasive breast carcinoma. However, to the authors' knowledge, the effect of these factors in the longer term (> 10 years after diagnosis) is not yet clear.
It is now > 20 years since the Swedish Two-County Trial of breast carcinoma screening with mammography was instigated and long-term follow-up is now available to December 1998. In the current study, the authors analyzed the effects of tumor size, lymph node status, and tumor grade on survival to death from breast carcinoma using Cox regression and frailty models that allow the baseline hazard and/or effect of a covariate to vary with time.
The effects of tumor size, lymph node status, and tumor grade were shown to progressively diminish with time from diagnosis. The Cox regression model with time-varying coefficients and a dampening parameter then was fitted to allow for the attenuation of prognostic effects; tumor size, lymph node status, and tumor grade were all found to be highly significant (P < 0.001).
The results of the current study suggest that long-term survival in women with invasive breast carcinoma could be modelled satisfactorily using either frailty models or Cox regression models with time-varying coefficients. The results also suggest that the value of tumor grade, lymph node status, and tumor size at the time of diagnosis have a lasting influence on subsequent survival, albeit attenuated in later years. The long-term effects of these prognostic factors may explain the fact that the impact of mass screening programs on breast carcinoma mortality rates is still apparent many years later. Cancer 2004;100:1331–6. © 2004 American Cancer Society.