Association of molecular subtypes with breast cancer risk factors: a case-only analysis

Eur J Cancer Prev. 2015 Nov;24(6):484-90. doi: 10.1097/CEJ.0000000000000111.

Abstract

As breast cancer (BC) screening identifies many BCs with a good prognosis, which might be overdiagnosed and therefore overtreated, the identification of subgroups with a high risk for aggressive subtypes might be helpful. The aim of this case-case analysis was to investigate the association between epidemiological risk factors and molecular subtypes in a cohort of BC patients. Epidemiological risk factors for 2587 BC patients were obtained using a structured questionnaire and from the patients' charts. The histopathological information (estrogen and progesterone receptor, HER2 and Ki-67) used in the analysis was retrieved from the original pathology reports. Analyses using conditional inference regression trees were carried out on these data. The strongest influence factor on the distribution of the molecular subtypes was age at first diagnosis of BC. An influence of BMI was also identified in patients aged either more than 42 years or 49.6 years or less. Older patients aged more than 49.6 years and perimenopausal women with a BMI of 32.4 kg/m or less were most likely to develop luminal A-like BC. Young patients aged 42 years or less and perimenopausal patients with a BMI more than 32.4 kg/m more often developed triple-negative BC. The study confirmed that age at diagnosis is an important factor influencing the distribution of molecular subtypes. In the perimenopausal group, it may be postulated that BMI plays a critical role in the pathogenesis of BC, defining a subgroup that is more likely to develop triple-negative BC or luminal B-like disease and another group in which there is a more postmenopausal distribution pattern.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Breast Neoplasms / classification*
  • Breast Neoplasms / metabolism
  • Breast Neoplasms / pathology*
  • Female
  • Humans
  • Middle Aged
  • Neoplasm Staging
  • Prognosis
  • Receptor, ErbB-2 / metabolism*
  • Receptors, Estrogen / metabolism*
  • Receptors, Progesterone / metabolism*
  • Risk Factors
  • Triple Negative Breast Neoplasms / metabolism
  • Triple Negative Breast Neoplasms / pathology*

Substances

  • Receptors, Estrogen
  • Receptors, Progesterone
  • Receptor, ErbB-2