title: Mammographic density defined by higher than conventional brightness threshold better predicts breast cancer risk for full-field digital mammograms.
abstract: BACKGROUND
  When measured using the computer-assisted method CUMULUS, mammographic density adjusted for age and body mass index predicts breast cancer risk. We asked if new mammographic density measures defined by higher brightness thresholds gave better risk predictions.
  
  
  METHODS
  The Korean Breast Cancer Study included 213 women diagnosed with invasive breast cancer and 630 controls matched for age at full-field digital mammogram and menopausal status. Mammographic density was measured using CUMULUS at the conventional threshold (Cumulus), and in effect at two increasingly higher thresholds, which we call Altocumulus and Cirrocumulus, respectively. All measures were Box-Cox transformed and adjusted for age, body mass index, menopausal status and machine. We used conditional logistic regression to estimate the change in Odds PER standard deviation of transformed and Adjusted density measures (OPERA). The area under the receiver operating characteristic curve (AUC) was estimated.
  
  
  RESULTS
  Corresponding Altocumulus and Cirrocumulus density measures were correlated with Cumulus measures (r approximately 0.8 and 0.6, respectively). Altocumulus and Cirrocumulus measures were on average 25% and 80% less, respectively, than the Cumulus measure. For dense area, the OPERA was 1.18 (95% confidence interval: 1.01-1.39, P = 0.03) for Cumulus; 1.36 (1.15-1.62, P < 0.001) for Altocumulus; and 1.23 (1.04-1.45, P = 0.01) for Cirrocumulus. After fitting the Altocumulus measure, the Cumulus measure was no longer associated with risk. After fitting the Cumulus measure, the Altocumulus measure was still associated with risk (P = 0.001). The AUCs for dense area was 0.59 for the Altocumulus measure, greater than 0.55 and 0.57 for the Cumulus and Cirrocumulus measures, respectively (P = 0.001). Similar results were found for percentage dense area measures.
  
  
  CONCLUSIONS
  Altocumulus measures perform better than Cumulus measures in predicting breast cancer risk, and Cumulus measures are confounded by Altocumulus measures. The mammographically bright regions might be more aetiologically important for breast cancer, with implications for biological, molecular, genetic and epidemiological research and clinical translation.
authors.affiliation: Melbourne School of Population and Global Health, Centre for Epidemiology and Biostatistics, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia. nguk@unimelb.edu.au.
authors.forename: Tuong Linh
authors.initials: TL
authors.lastname: Nguyen
authors.affiliation: Melbourne School of Population and Global Health, Centre for Epidemiology and Biostatistics, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia. ye.aung@unimelb.edu.au.
authors.forename: Ye Kyaw
authors.initials: YK
authors.lastname: Aung
authors.affiliation: Melbourne School of Population and Global Health, Centre for Epidemiology and Biostatistics, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia. cfevans@unimelb.edu.au.
authors.forename: Christopher Francis
authors.initials: CF
authors.lastname: Evans
authors.affiliation: Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, 25-2 Sungkyunkwan-ro, Jongno-gu, 110-745, Seoul, Korea. choismc@skku.edu.
authors.forename: Choi
authors.initials: C
authors.lastname: Yoon-Ho
authors.affiliation: Melbourne School of Population and Global Health, Centre for Epidemiology and Biostatistics, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia. m.jenkins@unimelb.edu.au.
authors.forename: Mark Anthony
authors.initials: MA
authors.lastname: Jenkins
authors.affiliation: Seoul Department of Epidemiology and Institute of Health and Environment, School of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, 151-742, Seoul, Korea. jsung@snu.ac.kr.
authors.forename: Joohon
authors.initials: J
authors.lastname: Sung
authors.affiliation: Melbourne School of Population and Global Health, Centre for Epidemiology and Biostatistics, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia. j.hopper@unimelb.edu.au.|Seoul Department of Epidemiology and Institute of Health and Environment, School of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, 151-742, Seoul, Korea. j.hopper@unimelb.edu.au.
authors.forename: John Llewelyn
authors.initials: JL
authors.lastname: Hopper
authors.affiliation: Department of Family Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 25-2 Sungkyunkwan-ro, Jongno-gu, 110-745, Seoul, Korea. yunmisong@skku.edu.
authors.forename: Yun-Mi
authors.initials: YM
authors.lastname: Song
mesh_terms: D019540:Area Under Curve; D015992:Body Mass Index; D001940:Breast / Q000473:pathology*; D000071060:Breast Density; D001943:Breast Neoplasms / Q000473:pathology*; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D042361:Mammary Glands, Human / Q000002:abnormalities* / Q000473:pathology; D008327:Mammography / Q000379:methods; D008875:Middle Aged; D012307:Risk Factors