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P15 6 th <strong>International</strong> <strong>Workshop</strong> on Breast Densitometry and Breast Cancer Risk Assessment THE ASSOCIATION BETWEEN GEOGRAPHIC STATUS AND MAMMOGRAPHIC DENSITY Marleen J. Emaus 1 , Marije F. Bakker 1 , Petra H.M. Peeters 1, 2 , Carla H. van Gils 1 1 Julius Center for Health Sciences and Primary Care, University Medical Center, PO Box 85500, 3508 GA Utrecht, the Netherlands; 2 Department of Epidemiology, Public Health and Primary Care, Faculty of Medicine, Imperial College, Norfolk Place, London W2 1PG, UK Introduction: It is frequently observed that mammographic density varies depending upon geographic area. It is unclear whether these differences are related to the degree of urbanization (as proxy variable for environmental factors such as exposure to traffic emissions) or to differences in social economic status (SES) (as proxy variable for lifestyle and reproductive characteristics). In the present study we try to unravel this issue within the Dutch screening population. Methods: The study was performed within the Prospect-EPIC cohort. Prospect-EPIC participants were recruited through the breast cancer screening program in Utrecht and vicinity between 1993 and 1997. Urbanization was categorized according to the number of addresses per kilometer squared using the 5- group classification established by Statistics Netherlands. SES was measured at neighborhood level (Statusscore) using data from Statistics Netherlands as well as at individual level (educational level of the participant). General linear models were used to study the association between the degree of urbanization and SES on the one hand and mammographic density on the other hand (i.e. percent density and dense area). The models were adjusted for age and BMI. Analyses with additional adjustment for lifestyle and hormonal risk factors for breast density will be presented at the conference. Results: We included 2,805 women with a mean age of 57.3 years (SD: 5.9 years). Women living in urban areas showed higher percent density than women in rural areas (adjusted mean percent density urban = 21.9%, 95%CI 21.1-22.8 versus adjusted mean percent density rural = 15.1, 95% CI 12.8-17.7, p- trend
P16 INTER-SCAN REPRODUCIBILITY OF MAMMOGRAPHIC DENSITY MEASUREMENTS 6 th <strong>International</strong> <strong>Workshop</strong> on Breast Densitometry and Breast Cancer Risk Assessment Mariëtte Lokate 1 , Marleen J. Emaus 1 , Michiel Kallenberg 2,3 , Nico Karssemeijer 2 , Wouter B. Veldhuis 4 , Petra H.M. Peeters 1 , Carla H. van Gils 1 1 Julius Center for Health Sciences and Primary Care, University Medical Center, PO Box 85500, 3508 GA Utrecht, the Netherlands; 2 Department of Radiology, Radboud University Nijmegen Medical Center, Geert Grooteplein Zuid 18, 6525 GA Nijmegen, the Netherlands; 3 Matakina Technology Ltd, PO Box 24404, Manners Street Central, Wellington, 6142, New Zealand; 4 Department of Radiology, University Medical Center, PO Box 85500, 3508 GA Utrecht, the Netherlands Introduction: Changes in mammographic density are frequently used as an intermediate marker to evaluate the effect of interventions for reducing breast cancer risk. We investigated the robustness of measurement of changes in mammographic density. We assessed consistency of mammographic density measurements between pairs of mammograms. They were made within a short time interval, in which no actual change in mammographic density can be expected. ABSTRACTS Methods: We included 170 women who underwent two mammographic examinations within a median follow-up period of 12 days (maximum 6 months) : 106 had two Full-Field Digital Mammograms (FFDM), 12 had two Film-Screen Mammograms (FSM) and 52 had one FSM and one FFDM. Mammographic density was assessed by a single reader using a computer assisted threshold method (Cumulus). The correlation between percent mammographic density measurements was estimated using intraclass correlation coefficients and we also calculated mean absolute difference in density measures between both mammograms. Linear regression was performed to adjust for differences in acquisition parameters between mammograms. Results: The intraclass correlation between percent density measurements on two FFDMs was 0.93 (95%CI 0.91–0.95), between two FSMs 0.94 (95% CI 0.84-0.98), and between FFDM and FSM 0.72 (0.61-0.80). The mean absolute difference in percent density between two FFDMs of the same woman was 4.3% (95% CI 3.8% to 4.9%) and between two FSMs 6.5% (95% CI 3.4% to 9.6%). On average, FSM showed a higher percent density compared to FFDM in the same women (difference 12.9% (95% CI 11% to 14.8%). Adjustment for differences in exposure, peak kilo voltage, compression force and breast thickness between mammograms did not alter the results. Conclusion: When studying changes in mammographic density, it is important to compare mammograms of the same type (i.e. either all FSM or all FFDM). Although intraclass correlation between density measured on mammograms of the same type (either FSM or FFDM) is high, the absolute differences in percent density are of a magnitude that may influence detectability of real changes in mammographic density. 49
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