Breast Cancer Research and Treatment

, Volume 44, Issue 2, pp 167–178

Prognostic factors for metachronous contralateral breast cancer: A comparison of the linear Cox regression model and its artificial neural network extension

  • L. Mariani
  • D. Coradini
  • E. Biganzoli
  • P. Boracchi
  • E. Marubini
  • S. Pilotti
  • B. Salvadori
  • R. Silvestrini
  • U. Veronesi
  • R. Zucali
  • F. Rilke
Article

DOI: 10.1023/A:1005765403093

Cite this article as:
Mariani, L., Coradini, D., Biganzoli, E. et al. Breast Cancer Res Treat (1997) 44: 167. doi:10.1023/A:1005765403093

Abstract

The purpose of the present study was toassess prognostic factors for metachronous contralateral recurrence ofbreast cancer (CBC). Two factors were of particularinterest, namely estrogen (ER) and progesterone (PgR) receptorsassayed with the biochemical method in primary tumortissue. Information was obtained from a prospective clinicaldatabase for 1763 axillary node-negative women who hadreceived curative surgery, mostly of the conservative type,and followed-up for a median of 82 months.The analysis was performed based on both astandard (linear) Cox model and an artificial neuralnetwork (ANN) extension of this model proposed byFaraggi and Simon [9]. Furthermore, to assess theprognostic importance of the factors considered, model predictiveability was computed.

In agreement with already published studies, the resultsof our analysis confirmed the prognostic role ofage at surgery, histology, and primary tumor site,in that young patients (≤ 45 years) withtumors of lobular histology or located at inner/centralmammary quadrants were at greater risk of developingCBC. ER and PgR were also shown tohave a prognostic role. Their effect, however, wasnot simple in relation to the presence ofinteractions between ER and age, and between PgRand histology. In fact, ER appeared to playa protective role in young patients, whereas theopposite was true in older women. Higher levelsof PgR implied a greater hazard of CBCoccurrence in infiltrating duct carcinoma or tumors withan associated extensive intraductal component, and a lowerhazard in infiltrating lobular carcinoma or other histotypes.In spite of the above findings, the predictivevalue of both the standard and ANN Coxmodels was relatively low, thus suggesting an intrinsiclimitation of the prognostic variables considered, rather thantheir suboptimal modeling. Research for better prognostic variablesshould therefore continue.

breast neoplasmsmodelsstatistical analysismultiple primaryneural networks (computer)prognosis

Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • L. Mariani
    • 1
  • D. Coradini
    • 1
  • E. Biganzoli
    • 1
  • P. Boracchi
    • 1
  • E. Marubini
    • 1
  • S. Pilotti
    • 1
  • B. Salvadori
    • 1
  • R. Silvestrini
    • 1
  • U. Veronesi
    • 2
  • R. Zucali
    • 1
  • F. Rilke
    • 1
  1. 1.Istituto Nazionale per lo Studio e la Cura dei TumoriMilanItaly
  2. 2.European Institute of OncologyMilanItaly