Nuclear morphometric features in benign breast tissue and risk of subsequent breast cancer

Yan Cui, Esther A. Koop, Paul J. Van Diest, Rita A. Kandel, Thomas E. Rohan

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

Certain nuclear morphometric features measured in breast tumor tissue have been shown to predict the prognosis of breast cancer patients. However, the application of these features to predicting risk of breast cancer development has received little attention. We conducted a case-control study to evaluate nuclear morphometric features in benign breast tissue in association with subsequent breast cancer risk. The study was nested within a cohort of 4,888 women with a histopathologic diagnosis of benign breast disease (BBD) and involved 61 cases and 71 controls, amongst whom there were 53 matched case-control sets. Conditional logistic regression models were fitted to assess various measurements of nuclear size and nuclear shape factors in relation to subsequent breast cancer risk. In multivariate analysis, subsequent breast cancer risk was positively associated with a nuclear shape factor that takes the shortest nuclear axis and the longest nuclear axis into consideration simultaneously (highest quartile versus lowest 3 quartiles: odds ratio = 3.07, 95% confidence limits = 1.61, 5.84). In contrast, there was no alteration in subsequent breast cancer risk in association with nuclear size features and other shape factors. In conclusion, our study results suggest that the shape factor that takes both the shortest nuclear axis and the longest nuclear axis into consideration might be of value to predict subsequent development of breast cancer among women with BBD.

Original languageEnglish (US)
Pages (from-to)103-107
Number of pages5
JournalBreast Cancer Research and Treatment
Volume104
Issue number1
DOIs
StatePublished - Jul 1 2007

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Keywords

  • Benign breast disease
  • Breast cancer
  • Morphometry
  • Nuclear shape
  • Nuclear size

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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