A prediction model for breast cancer recurrence after adjuvant hormone therapy

P. Boracchi, D. Coradini, L. Antolini, S. Oriana, R. Dittadi, M. Gion, M. G. Daidone, Elia Biganzoli

Research output: Contribution to journalArticle

Abstract

Hormone therapy with tamoxifen has long been the established adjuvant treatment for node-positive, estrogen-receptor-positive breast cancer in postmenopausal women. Since 30-40% of these patients fail to respond, reliable outcome prediction is necessary for successful treatment allocation. Using pathobiological variables (available in most clinical records: tumor size, nodal involvement, estrogen and progesterone receptor content) from 596 patients recruited at a comprehensive cancer center, we developed a prediction model which we validated in an independent cohort of 175 patients recruited at a general hospital. Calculated at 3 and 4 years of follow-up, the discrimination indices were 0.716 [confidence limits (CL) 0.641, 0.752] and 0.714 (CL 0.650, 0.750) for the training data, and 0.726 (CL 0.591, 0.769) and 0.677 (CL 0.580, 0.745) for the testing data. Waiting for more effective approaches from genomic and proteomic studies, a model based on consolidated pathobiological variables routinely assessed at relatively low costs may be considered as the reference for assessing the gain of new markers over traditional ones, thus substantially improving the conventional use of prognostic criteria.

Original languageEnglish
Pages (from-to)199-206
Number of pages8
JournalInternational Journal of Biological Markers
Volume23
Issue number4
Publication statusPublished - 2008

Keywords

  • Adjuvant tamoxifen
  • Breast cancer
  • Nomogram
  • Relapse prediction

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Cancer Research
  • Oncology
  • Pathology and Forensic Medicine

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    Boracchi, P., Coradini, D., Antolini, L., Oriana, S., Dittadi, R., Gion, M., Daidone, M. G., & Biganzoli, E. (2008). A prediction model for breast cancer recurrence after adjuvant hormone therapy. International Journal of Biological Markers, 23(4), 199-206.