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P43 6 th <strong>International</strong> <strong>Workshop</strong> on Breast Densitometry and Breast Cancer Risk Assessment VISUAL ANALOGUE SCALE ASSESSMENT OF PERCENTAGE BREAST DENSITY: A STUDY OF AGREEMENT BETWEEN OBSERVERS AND WITH INTERACTIVE THRESHOLDING Jamie C. Sergeant 1 , Mary Wilson 2 , Nicky Barr 2 , Ursula Beetles 2 , Caroline Boggis 2 , Sara Bundred 2 , Megan Bydder 2 , Soujanya Gadde 2 , Emma Hurley 2 , Anil Jain 2 , Yit Lim 2 , Liz Lord 2 , Valerie Reece 2 , D. Gareth Evans 2 , Anthony Howell 2 , Susan M. Astley 1 1 Centre for Imaging Sciences, Institute for Population Health, University of Manchester, Manchester, UK: 2 Nightingale Centre and Genesis Prevention Centre, University Hospital of South Manchester, Manchester, UK Aim: The measurement of percentage breast density on a visual analogue scale (VAS) has been shown to have an association with breast cancer risk comparable to that of interactive thresholding software such as Cumulus (Sunnybrook Health Sciences Centre, Toronto, Canada). While interactive thresholding is too labour intensive to implement in a breast screening programme for the purposes of prospective risk estimation, the quick and simple VAS method is more well-suited to this application. However, for VAS density measurement to be satisfactorily used for this purpose, there must be comparability between estimates produced by different observers. We examine the agreement between a group of observers assessing VAS breast density and their agreement with Cumulus. Method: 120 screening cases were sampled from the Predicting Risk Of Cancer At Screening (PROCAS) study, a large clinical study based in Manchester, UK, which aims to predict the risk of breast cancer when women attend routine breast screening. The cases all had Full-Field Digital Mammography (FFDM) images acquired on GE Senographe Essential equipment. The breast density of the cases was independently assessed by 12 experienced mammographic readers using a separate VAS for each radiographic projection (craniocaudal and mediolateral oblique) of both breasts. In addition, a trained and validated Cumulus user also estimated the density for each image. Assessment of inter-observer agreement and agreement with Cumulus was performed using the Bland-Altman limits of agreement approach and the concordance correlation coefficient (CCC). All density estimates were also discretised to the four BI-RADS breast composition categories and agreement on this ordinal scale measured with Cohen’s weighted kappa. Results: The maximum observed difference between estimates by two readers assessing the same case was 67.75 percentage points, while the mean difference between pairs of readers ranged from 0.76 to 28.58 percentage points and the mean difference from Cumulus ranged from 0.38 to 22.98 percentage points. 95% limits of agreement between reader pairs, between which 95% of differences are expected to lie, were (-6.96, 18.62) at their narrowest and (-59.13, 1.97) at their widest, while between readers and Cumulus they ranged from (-32.55, -3.29) to (-49.71, 3.94). Pairwise CCC values ranged from 0.44 to 0.92, while the overall CCC across the 12 readers was 0.70. Concordance with Cumulus ranged from 0.48 to 0.87. Pairwise kappa values for the BI-RADS classification ranged from 0.37 to 0.84 for the 12 readers, with a mean of 0.66. Kappa values between the readers and Cumulus ranged from 0.40 to 0.80. ABSTRACTS Conclusion: A lack of agreement was found between the readers visually assessing breast density and a comparable lack of agreement was also found between the readers and Cumulus. This group of readers had varying levels of experience of VAS breast density assessment, but were all routinely performing estimation in the PROCAS study. The current study suggests that for VAS density to be used for risk stratification and personalised screening, inter-observer variation must be accounted for, either through standardised training or by applying a correction to results after reading has been performed. 78
P44 6 th <strong>International</strong> <strong>Workshop</strong> on Breast Densitometry and Breast Cancer Risk Assessment LARGE INTERNATIONAL STUDY REVEALS NOVEL ASSOCIATIONS BETWEEN COMMON BREAST CANCER SUSCEPTIBILITY VARIANTS AND RISK- PREDICTING MAMMOGRAPHIC DENSITY MEASURES Jennifer Stone 1 , Deborah Thompson 2 , Isabel dos Santos Silva 3 , Christopher Scott 4 , Melissa Southey 5 , Laura Baglietto 6 , Fergus Couch 4 , Sara Lindström 7,8 , Jingmei Li 9 , Gretchen Gierach 10 , Julie A Douglas 11 , Javier Benitez 12 , Peter Fasching 13 , Graham Giles 6 , Marina Pollan 12 , Jonine Figueroa 10 , Kristen Stevens 4 , Norman F. Boyd 14 , Per Hall 9 , Douglas F. Easton 2 , Rulla M. Tamimi 7,8,15 , John L. Hopper 1 and Celine Vachon 4 for the DENSNP and Markers of Density (MODE) consortia ABSTRACTS 1 Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia; 2 Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; 3 Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK; 4 Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; 5 Genetic Epidemiology Laboratory (GEL), Department of Pathology, The University of Melbourne, Melbourne, Australia; 6 Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia; 7 Program in Molecular and Genetic Epidemiology, 8 Department of Epidemiology , Harvard School Of Public Health, Boston, MA, USA; 9 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; 10 Hormonal and Reproductive Epidemiology Branch, National Cancer Institute, Rockville, MD ; 11 Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI; 12 Centro Nacional de Investigaciones Oncologicas, Madrid, Spain; 13 Erlangen University Perinatal Center, Department of Gynaecology and Obstetrics, Erlangen University Hospital, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen, Germany; 14 Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada; 15 Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA Background: Mammographic density adjusted for age and body mass index (BMI) is a heritable predictor of breast cancer risk but the underlying biological processes are unclear. To date, 77 common variants have been found to be associated with breast cancer susceptibility. Methods: We examined the associations between these variants and mammographic density measures (absolute dense area, percent dense area and absolute non-dense area) adjusted for study, age and BMI using mixed linear models using 10,727 women from the international DENSNP and Markers Of DEnsity (MODE) consortia. Results: We found strong support for previously reported associations of rs10995190 (in the region of ZNF365), rs2046210 (ESR1) and rs3817198 (LSP1) with adjusted absolute and percent dense areas (all p
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