title: Associations of Breast Cancer Risk Prediction Tools With Tumor Characteristics and Metastasis.
abstract: OBJECTIVE
  The association between established risk factors for breast cancer and subtypes or prognosis of the disease is not well known. We analyzed whether the Tyrer-Cuzick-predicted 10-year breast cancer risk score (TCRS), mammographic density (MD), and a 77-single nucleotide polymorphism polygenic risk score (PRS) were associated with breast cancer tumor prognosticators and risk of distant metastasis.
  
  
  METHODS
  We used a case-only design in a population-based cohort of 5,500 Swedish patients with breast cancer. Logistic and multinomial logistic regression of outcomes, estrogen receptor (ER) status, lymph node involvement, tumor size, and grade was performed with TCRS, PRS, and percent MD as exposures. Cox proportional hazard models were used to estimate hazard ratios (HRs) of distant metastasis.
  
  
  RESULTS
  Women at high risk for breast cancer based on PRS and/or TCRS were significantly more likely to be diagnosed with favorable prognosticators, such as ER-positive and low-grade tumors. In contrast, PRS weighted on ER-negative disease was associated with ER-negative tumors. When stratifying by age, the associations of TCRS with favorable prognosticators were restricted to women younger than age 50. Women scoring high in both TCRS and PRS had a lower risk of distant metastasis (HR, 0.69; 95% CI, 0.49 to 0.98). MD was not associated with any of the examined prognosticators.
  
  
  CONCLUSIONS
  Women at high risk for breast cancer based on genetic and lifestyle factors were significantly more likely to be diagnosed with breast cancers with a favorable prognosis. Better knowledge of subtype-specific risk factors could be vital for the success of prevention programs aimed at lowering mortality.
authors.affiliation: All authors: Karolinska Institutet, Stockholm, Sweden johanna.holm@ki.se.
authors.forename: Johanna
authors.initials: J
authors.lastname: Holm
authors.affiliation: All authors: Karolinska Institutet, Stockholm, Sweden.
authors.forename: Jingmei
authors.initials: J
authors.lastname: Li
authors.affiliation: All authors: Karolinska Institutet, Stockholm, Sweden.
authors.forename: Hatef
authors.initials: H
authors.lastname: Darabi
authors.affiliation: All authors: Karolinska Institutet, Stockholm, Sweden.
authors.forename: Martin
authors.initials: M
authors.lastname: Eklund
authors.affiliation: All authors: Karolinska Institutet, Stockholm, Sweden.
authors.forename: Mikael
authors.initials: M
authors.lastname: Eriksson
authors.affiliation: All authors: Karolinska Institutet, Stockholm, Sweden.
authors.forename: Keith
authors.initials: K
authors.lastname: Humphreys
authors.affiliation: All authors: Karolinska Institutet, Stockholm, Sweden.
authors.forename: Per
authors.initials: P
authors.lastname: Hall
authors.affiliation: All authors: Karolinska Institutet, Stockholm, Sweden.
authors.forename: Kamila
authors.initials: K
authors.lastname: Czene
mesh_terms: D000071060:Breast Density; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000453:epidemiology / Q000235:genetics / Q000473:pathology; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008019:Life Style; D016015:Logistic Models; D042361:Mammary Glands, Human / Q000002:abnormalities; D008875:Middle Aged; D009362:Neoplasm Metastasis; D020641:Polymorphism, Single Nucleotide; D011379:Prognosis; D016016:Proportional Hazards Models; D018570:Risk Assessment; D012307:Risk Factors; D013548:Sweden / Q000453:epidemiology