P21 6 th <str<strong>on</strong>g>Internati<strong>on</strong>al</str<strong>on</strong>g> <str<strong>on</strong>g>Workshop</str<strong>on</strong>g> <strong>on</strong> <strong>Breast</strong> <strong>Densitometry</strong> <strong>and</strong> <strong>Breast</strong> Cancer Risk Assessment MAMMOGRAPHIC DENSITY PHENOTYPES AND RISK OF BREAST CANCER: A META-ANALYSIS Andreas Petterss<strong>on</strong> 1 , Rebecca E. Graff 1 , Laura Baglietto 2, 3 , Marije F. Bakker 4 , Norman Boyd 5 , KeeSeng Chia 6 , Kamila Czene 7 , Isabel dos Santos Silva 8 , Louise Erikss<strong>on</strong> 7 , Graham G. Giles 2, 3, 9 , Per Hall 7 , Mikael Hartman 6, 7, 9 , John L. Hopper 3 , Kavitha Krishnan 2, 3 , Jingmei Li 11 , Qing Li 5 , Gertraud Maskarinec 12 , Valerie McCormack 13 , Ian Pagano 12 , Bernard A. Rosner 14, 15 , Christopher Scott 16 , Jennifer St<strong>on</strong>e 3 , Giske Ursin 17, 18 , Celine Vach<strong>on</strong> 16 , Carla H. van Gils 4 , Chia Si<strong>on</strong>g W<strong>on</strong>g 6 1, 14 , Rulla M. Tamimi 1) Department of Epidemiology, Harvard School of Public Health, Bost<strong>on</strong>, MA, USA; 2) Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia; 3) Centre for Molecular, Envir<strong>on</strong>mental, Genetic <strong>and</strong> Analytical Epidemiology, The University of Melbourne, Australia; 4) Julius Center for Health Sciences <strong>and</strong> Primary Care, University Medical Center, Utrecht, The Netherl<strong>and</strong>s; 5) Campbell Family Institute for <strong>Breast</strong> Cancer Research, Ontario Cancer Institute, Tor<strong>on</strong>to, Ontario, Canada; 6) Saw Swee Hock School of Public Health, Nati<strong>on</strong>al University of Singapore, Nati<strong>on</strong>al University Health System, Singapore; 7) Department of Medical Epidemiology <strong>and</strong> Biostatistics, Karolinska Institutet, Stockholm, Sweden; 8) Department of N<strong>on</strong>-Communicable Disease Epidemiology, L<strong>on</strong>d<strong>on</strong> School of Hygiene <strong>and</strong> Tropical Medicine, L<strong>on</strong>d<strong>on</strong>, United Kingdom; 9) Department of Epidemiology <strong>and</strong> Preventive Medicine, M<strong>on</strong>ash University, Melbourne, Australia; 10) Department of Surgery, Y<strong>on</strong>g Loo Lin School of Medicine, Nati<strong>on</strong>al University of Singapore, Singapore; 11) Human Genetics Divisi<strong>on</strong>, Genome Institute of Singapore, Singapore; 12) Department of Epidemiology, University of Hawaii Cancer Center, H<strong>on</strong>olulu, HI, USA; 13) Secti<strong>on</strong> of Envir<strong>on</strong>ment <strong>and</strong> Radiati<strong>on</strong>, <str<strong>on</strong>g>Internati<strong>on</strong>al</str<strong>on</strong>g> Agency for Research <strong>on</strong> Cancer, Ly<strong>on</strong>, France; 14) Channing Divisi<strong>on</strong> of Network Medicine, Department of Medicine, Brigham <strong>and</strong> Women’s Hospital <strong>and</strong> Harvard Medical School, Bost<strong>on</strong>, MA, USA; 15) Department of Biostatistics, Harvard School of Public Health, Bost<strong>on</strong>, MA, USA; 16) Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA; 17) Department of Nutriti<strong>on</strong>, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway; 18) Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA Background: Fibrogl<strong>and</strong>ular breast tissue appears dense <strong>on</strong> mammogram; fat appears n<strong>on</strong>dense. We investigated whether absolute or percent dense area more str<strong>on</strong>gly predicts breast cancer risk, <strong>and</strong> whether absolute n<strong>on</strong>dense area is independently associated with risk. Methods: We c<strong>on</strong>ducted a meta-analysis of 13 case-c<strong>on</strong>trol studies, each having provided parameter estimates <strong>and</strong> st<strong>and</strong>ard errors from logistic regressi<strong>on</strong>s for associati<strong>on</strong>s between <strong>on</strong>e st<strong>and</strong>ard deviati<strong>on</strong> (SD) increments in mammographic density phenotypes <strong>and</strong> breast cancer risk. We used r<strong>and</strong>om-effects models to calculate pooled odds ratios (ORs) <strong>and</strong> 95% c<strong>on</strong>fidence intervals (CIs). ABSTRACTS Results: Am<strong>on</strong>g premenopausal women (1,776 cases; 2,834 c<strong>on</strong>trols), summary ORs for <strong>on</strong>e SD increments were 1.37 (95% CI: 1.29-1.47) for absolute dense area, 0.78 (95% CI: 0.71-0.86) for absolute n<strong>on</strong>dense area, <strong>and</strong> 1.52 (95% CI: 1.39-1.66) for percent dense area when pooling estimates adjusted for age, BMI <strong>and</strong> parity. Corresp<strong>on</strong>ding ORs am<strong>on</strong>g postmenopausal women (6,643 cases; 11,187 c<strong>on</strong>trols) were 1.38 (95% CI: 1.31-1.44), 0.79 (95% CI: 0.73-0.85), <strong>and</strong> 1.53 (95% CI: 1.44-1.64). After additi<strong>on</strong>al adjustment for absolute dense area, associati<strong>on</strong>s between absolute n<strong>on</strong>dense area <strong>and</strong> breast cancer became attenuated or null in several studies <strong>and</strong> summary ORs became 0.82 (95% CI: 0.71-0.94; P- heterogeneity: 0.02) for premenopausal <strong>and</strong> 0.85 (95% CI: 0.75-0.96; P-heterogeneity:
6 th <str<strong>on</strong>g>Internati<strong>on</strong>al</str<strong>on</strong>g> <str<strong>on</strong>g>Workshop</str<strong>on</strong>g> <strong>on</strong> <strong>Breast</strong> <strong>Densitometry</strong> <strong>and</strong> <strong>Breast</strong> Cancer Risk Assessment P22 MAMMOGRAPHIC DENSITY AND EARLY MAMMOGRAPHIC SCREENING PERFORMANCE MEASURES IN THE NORWEGIAN BREAST CANCER SCREENING PROGRAM Solveig Hofvind 1,2* Isabel dos-Santos-Silva 3 , Merete Ellingjord-Dale 4 , Sofie Sebuødegård 1 , Giske Ursin 1,5 1 Cancer Registry of Norway, Oslo, Norway; 3 Department of N<strong>on</strong>-Communicable Disease Epidemiology, L<strong>on</strong>d<strong>on</strong> School of Hygiene <strong>and</strong> Tropical Medicine, L<strong>on</strong>d<strong>on</strong>, UK ; 4 Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway ; 2 Oslo <strong>and</strong> Akershus University College of Applied Sciences, Oslo, Norway; 5 University of Southern California, Los Angeles, CA ABSTRACTS Background: It is well known that mammographic density (MD) increases the risk of breast cancer <strong>and</strong> reduces sensitivity of mammographic screening. However, less is known <strong>on</strong> how MD may affect early performance measures in mammographic screening am<strong>on</strong>g those recalled for further assessments. We used data collected by the populati<strong>on</strong>-based Norwegian <strong>Breast</strong> Cancer Screening Program (NBCSP) to investigate associati<strong>on</strong>s of MD <strong>and</strong> the percentage of cancers detected am<strong>on</strong>g women recalled for further assessment (positive predictive value <strong>on</strong>e, PPV-1), as well as percentage of cancers detected am<strong>on</strong>g the women who underwent a biopsy (fine needle aspirati<strong>on</strong> cytology or core needle biopsy)(PPV-2) <strong>and</strong> MD associati<strong>on</strong>s with prognostic histopathological tumor characteristics. Methods: We analyzed data from women screened in the NBCSP during 1996-2010 who were subsequently recalled for further assessments. Visual assessment of MD was routinely performed <strong>on</strong> analogue (80%) or digital mammograms by radiologists with expertise in mammography using an inhouse visual 3-category scale (low: MD