Cancer Epidemiology and Prevention Biomarkers最新文献

{"title":"Abstract IA19: Can biomarkers be used to improve risk prediction models on lung cancer?","authors":"M. Johansson","doi":"10.1158/1538-7755.CARISK16-IA19","DOIUrl":"https://doi.org/10.1158/1538-7755.CARISK16-IA19","url":null,"abstract":"Lung cancer kills over 1.6 million people every year, making it the chief cause of cancer death worldwide. The US National Lung Cancer Screening Trial (NLST) demonstrated in 2011 that screening with computed tomography (CT) scans could reduce lung cancer mortality by 20% and total mortality by 7%. As a result, the US Preventive Services Task Force (USPSTF) has recommended LDCT-screening for lung cancer in ever-smokers aged 55-80 years who have smoked 30 pack-years with no more than 15 years since quitting. However, the NLST study also highlighted several important negative aspects of CT screening in terms of morbidity associated with over-diagnosis, treatment of benign nodules, and financial costs. The study also indicated important differences in the benefit of screening in different participant groups as defined by their underlying risk of lung cancer, highlighting the urgent need to improve and implement risk prediction models when identifying those individuals that are at high risk and most likely to benefit from lung cancer screening. Concurrently, multiple research groups, including ours, have explored the hypothesis that circulating biomarkers can capture information on risk that cannot be provided with questionnaires. In particular, we have evaluated the potential of improving upon the USPSTF lung cancer screening criteria using a small panel of selected tumour-related proteins, data on which will be presented during the conference. Citation Format: Mattias Johansson. Can biomarkers be used to improve risk prediction models on lung cancer? [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr IA19.","PeriodicalId":9487,"journal":{"name":"Cancer Epidemiology and Prevention Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79946209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract A09: A next generation sequencing based microsatellite instability assay suitable for routine risk stratification in colorectal cancer","authors":"Ghanim Alhilal, L. Redford, Á. Alonso, Sira Moreno, M. Arends, A. Oniscu, Ottilia O'Brien, S. Needham, J. Burn, M. Jackson, M. Santibanez-Koref","doi":"10.1158/1538-7755.CARISK16-A09","DOIUrl":"https://doi.org/10.1158/1538-7755.CARISK16-A09","url":null,"abstract":"3-5% of CRCs show microsatellite instability (MSI) caused by germline defects in mismatch repair genes (MMR) predisposing to Lynch syndrome. In addition, 12% of sporadic CRCs show MSI. Currently, MSI is tested using a fragment analysis based assay not suitable for high throughput testing with suboptimal sensitivity and specificity. Knowledge of microsatellite instability affects prognosis (MSI is a positive prognostic factor in stage II CRC), risk stratification (for the affected and at risk relatives in Lynch syndrome), prediction of lymph node involvement (lymph node metastasis is unlikely in stage I MSI positive CRC) and treatment of CRCs (MMR deficient tumours showed observable benefit from PD-1 blocking agent pembrolizumab). For all these important benefits, MSI testing is now recommended for all newly diagnosed CRCs. As a result, development of a high throughput approach is desirable. We have developed and validated a high throughput sequence based MSI assay. In this study, we tested 17 short (7-12bp) mononucleotide markers (previously identified by our team via an in silico analyses of whole genome sequencing data). These 17 markers were able to discriminate between MSI-high (MSI-H) and microsatellite stable (MSS) cases. To define the optimal parameters to discriminate between MSI-H and MSS samples, we tested these 17 markers across a panel of 141 CRC samples. This allowed us to define a scoring scheme for the 17 markers using allelic imbalance based on a linked SNP (called weighted scoring scheme), which achieved 96% sensitivity and 100% specificity. This scoring scheme was then validated using an independent cohort of 70 CRCs without knowing their MSI status. The assay achieved a 100% sensitivity and specificity. We provide here a high throughput tool to detect microsatellite instability that is less costly, uses short mononucleotide markers (eliminating the need to test matched normal tissue) and is validated on formalin fixed paraffin embedded (FFPE) samples (similar to routine samples). The ability to test the microsatellite instability status in all the newly diagnosed CRC cases would have a great clinical impact on prognosis, risk stratification and treatment of CRCs. Citation Format: Ghanim Alhilal, Lisa Redford, Angel Alonso, Sira Moreno, Mark Arends, Anca Oniscu, Ottilia O9Brien, Stephanie Needham, John Burn, Michael Jackson, Mauro Santibanez-Koref. A next generation sequencing based microsatellite instability assay suitable for routine risk stratification in colorectal cancer. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr A09.","PeriodicalId":9487,"journal":{"name":"Cancer Epidemiology and Prevention Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78502356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract A25: Benign breast disease and subsequent breast cancer risk: The Detroit cohort","authors":"M. Cote, Wei Chen, J. Ruterbusch, E. Abdulfatah, V. Pardeshi, Asra N. Shaik, M. Ghanim, M. F. Daaboul, D. Visscher, S. Bandyopadhyay, R. Ali-Fehmi","doi":"10.1158/1538-7755.CARISK16-A25","DOIUrl":"https://doi.org/10.1158/1538-7755.CARISK16-A25","url":null,"abstract":"Introduction: Atypical hyperplasia (also known as proliferative disease with atypia), while categorized as a benign finding, has been consistently associated with an increased risk of subsequent breast cancer that persists for decades after initial diagnosis. There are various other lesions that are classified as benign breast disease (BBD) that are routinely identified by pathologists that may also increase risk and be of use to inform breast cancer risk models. We sought to identify which BBD lesions were associated with increased risk of breast cancer in an African American (AA) cohort. Methods: Benign breast biopsies from 3,895 AA women diagnosed with BBD between 1997 and 2010 in metropolitan Detroit were reviewed for 12 benign features including columnar alterations, ductal ectasia, ductal hyperplasia, fibrosis, apocrine metaplasia, lobular hyperplasia, calcifications, cysts, intraductal papilloma, radial scar, sclerosing adenosis, and fibroadenomas. Women were followed for subsequent breast cancer using the Metropolitan Detroit Cancer Surveillance System, part of the Surveillance, Epidemiology, and End Results (SEER) cancer registry. Associations between BBD features and subsequent breast cancer were examined using chi-square tests. Features that had a significant chi-square test result were also combined into scores describing the overall number of BBD features identified, termed busy breast score. Multivariable log-binomial regression with backward selection based on BIC criteria was performed to assess risk ratio and 95% confidence intervals of breast cancer on 12 candidate features. Multivariable log-binomial regression was performed for busy breast score as well. All regression models were adjusted for age at biopsy and overall impression for presence of proliferative disease with or without atypia using non-proliferative disease as the reference. Models were checked for multicollinearity using a variable inflation factor (VIF). Results: Of the 3,895 AA women in the BBD cohort, 210 developed a subsequent breast cancer. The median age at biopsy among those without a subsequent cancer (controls) was 47 years of age, while cases were 53 years of age (p-value Conclusions: Columnar alterations confer increased risk of breast cancer beyond the risks associated with atypical hyperplasia, as does the presence of multiple types of BBD lesions in a single biopsy. These estimates may help improve the current risk assessment models for African American women and highlight the need for additional research regarding the utility of closer surveillance and potentially chemoprevention for reduction of breast cancer in these women. Citation Format: Michele L. Cote, Wei Chen, Julie J. Ruterbusch, Eman Abdulfatah, Visakha Pardeshi, Asra N. Shaik, Marcel T. Ghanim, MHD Fayez Daaboul, Daniel W. Visscher, Sudeshna Bandyopadhyay, Rouba Ali-Fehmi. Benign breast disease and subsequent breast cancer risk: The Detroit cohort. [abstract]. In: Proceedings of the AA","PeriodicalId":9487,"journal":{"name":"Cancer Epidemiology and Prevention Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91466057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract PR09: Prostate cancer prognostication based on an actionable metabolic pathway","authors":"Konrad H. Stopsack, T. Gerke, L. Mucci, Jennifer R. Rider","doi":"10.1158/1538-7755.CARISK16-PR09","DOIUrl":"https://doi.org/10.1158/1538-7755.CARISK16-PR09","url":null,"abstract":"Background: We recently discovered that mRNA expression of SQLE, coding for squalene monooxygenase, the second rate-limiting enzyme of cholesterol synthesis, is associated with lethality after prostate cancer diagnosis. Here, we investigate how expression of SQLE and other key regulators of cholesterol homeostasis, identified by prior mechanistic studies, aid risk prediction for lethal prostate cancer. Methods: The Health Professionals Follow-up Study and the Physicians9 Health Study prostate cancer tissue cohorts collected tissue from prostatectomy or transurethral resection of the prostate at cancer diagnosis. Whole-transcriptome profiling was performed. The outcome of interest was lethal cancer defined as prostate cancer mortality or development of metastases in contrast to non-lethal cancer without evidence of metastases after at least eight years of follow up. Discrimination for prostate lethal cancer was assessed by comparing c-statistics using bootstrap resampling. Results: Combining both cohorts, 112 men had lethal prostate cancer; 290 men had non-lethal cancer. A prognostic model for lethal cancer including Gleason grade, pathologic stage, age, and year of diagnosis had a high c = 0.885; adding body mass index, smoking status, family history of prostate cancer, and diabetes diagnosis increased c to 0.889. A model containing only SQLE (linear) achieved c = 0.663. Adding SQLE to the fully adjusted model increased c to 0.903 (p = 0.027). None of the other cholesterol regulators ABCA1, ACAT1, LDLR, and SCARB1 improved discrimination. Conclusions: SQLE performs well as a single biomarker of prostate cancer lethality after primary therapy, in contrast to other markers of intratumoral cholesterol regulation. Improvements in prognostication are minimal when SQLE is added to a model that contains a centrally re-reviewed Gleason grade. Most importantly, SQLE may be an actionable, predictive biomarker of benefit from statin therapy, which addresses the cholesterol synthesis pathway regulated by SQLE. Citation Format: Konrad H. Stopsack, Travis A. Gerke, Lorelei A. Mucci, Jennifer R. Rider. Prostate cancer prognostication based on an actionable metabolic pathway. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR09.","PeriodicalId":9487,"journal":{"name":"Cancer Epidemiology and Prevention Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87216364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract PR13: External validation of a risk prediction model for lung cancer among smokers","authors":"L. Sakoda, L. Habel, K. Thai, C. Quesenberry","doi":"10.1158/1538-7755.CARISK16-PR13","DOIUrl":"https://doi.org/10.1158/1538-7755.CARISK16-PR13","url":null,"abstract":"Early detection strategies for lung cancer may be improved by using valid risk prediction models to identify persons at highest risk for the disease. However, external validation of lung cancer risk prediction models has been limited. We sought to externally validate the PLCOM2012 model, which predicts the probability of lung cancer within six years on the basis of age, race, education, body mass index, chronic obstructive pulmonary disease, personal history of cancer, family history of lung cancer, and smoking status, quantity, duration, and quit years, in the Kaiser Permanente Northern California (KPNC) Research Program on Genes, Environment, and Health (RPGEH) cohort. To increase comparability to the populations of smokers used to initially develop and validate the PLCOM2012 model, we restricted our analysis to the 28,757 ever smokers ages 55 to 74 with no history of lung cancer, no history of other non-melanoma skin cancers in the prior five years, and complete data on all model predictors. For each person, the predicted probability of lung cancer risk was estimated with data ascertained from the RPGEH survey on all predictors except quit years, which was ascertained from electronic health records. Using KPNC Cancer Registry data, we identified 672 diagnosed with lung cancer within six years post-survey. Both calibration and discrimination were examined to assess model performance. Calibration was assessed by determining the mean absolute difference in observed and predicted probabilities of lung cancer for each decile of predicted risk. Discrimination was assessed by estimating the area under curve (AUC). The absolute difference in observed and predicted probabilities of lung cancer risk was generally small: Citation Format: Lori C. Sakoda, Laurel A. Habel, Khanh K. Thai, Charles P. Quesenberry, Jr. External validation of a risk prediction model for lung cancer among smokers. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR13.","PeriodicalId":9487,"journal":{"name":"Cancer Epidemiology and Prevention Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84771025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract PR15: Projecting individualized absolute risk of developing gastric cancer in Koreans","authors":"Minkyo Song, Jae-Jeong Yang, H. Sung, S. Kong, H. Lee, Hyung-Ho Kim, S. Kim, Han-Kwang Yang, N. Sawada, S. Tsugane, M. Inoue, D. Kang","doi":"10.1158/1538-7755.CARISK16-PR15","DOIUrl":"https://doi.org/10.1158/1538-7755.CARISK16-PR15","url":null,"abstract":"Background: Despite the rapid decline of the incidence and mortality over the past few decades, gastric cancer still remains to be the third leading cause of cancer death and the fifth most common cancer worldwide. Furthermore, the absolute number of gastric cancer cases is increasing globally due to the aging of the world population. With available methods to detect and treat precancerous and early stage lesions, development of a prediction model to estimate the probability of developing gastric cancer for various age intervals and risk profiles have important public health implications. Methods: Candidate predictors were selected combining expert opinion and literature search. Using a case-control study with 4,603 Korean subjects, a logistic regression model was used for estimating relative risks, separately for men and women. The discriminatory ability of the models was assessed by receiver operator characteristic area under the curve (AUC). Absolute risk parameters were then calculated combined with the relative risk estimates with baseline age-specific cancer hazard rates from Korean Cancer Registry data. The developed models were validated using an independent prospective cohort data, a Japanese population-based cohort study, which includes 40,173 subjects, by calculating the ratio of expected number (E) over observed number (O) and 95% confidence interval (CI). Results: The models for both men and women included low education, past medical history of diabetes mellitus, no regular use of nonsteroidal inflammatory drugs intake, smoking, no regular exercising, and consumption of high salted food, less fruit, less nonstarchy vegetables, and less nonfermented soy food. The AUC for the relative risk model was 0.73 (95% CI 0.71-0.75) for men and 0.76 (95% CI 0.74-0.79) for women. The overall E/O ratio was 1.05 (95% CI 0.98-1.12) in men, and 0.93 (95% CI 0.83-1.04) in women in the external validation population. Conclusions: To our knowledge this is the first study to estimate the absolute risk of gastric cancer in Korean population. The mathematical models developed in the present study will help predict the occurrence of gastric cancer for an individual considering combined risk factors which will help at a personalized level by enabling early detection and preventive efforts. A further development of a model incorporating biomarkers can provide strategies to select individuals at high risk, for screening for gastric cancer. This abstract is also being presented as PosterB11. Citation Format: Minkyo Song, Jae Jeong Yang, Hyuna Sung, Seong-Ho Kong, Hyuk-Joon Lee, Hyung-Ho Kim, Sang Gyun Kim, Han-Kwang Yang, Norie Sawada, Shoichiro Tsugane, Manami Inoue, Daehee Kang. Projecting individualized absolute risk of developing gastric cancer in Koreans. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Bio","PeriodicalId":9487,"journal":{"name":"Cancer Epidemiology and Prevention Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88138592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract A30: Affordability of screening, race and marital status predict early detection of breast cancer: Analysis of cancer registry data","authors":"A. Chandak, P. Nayar, G. Kan, N. Gupta","doi":"10.1158/1538-7755.CARISK16-A30","DOIUrl":"https://doi.org/10.1158/1538-7755.CARISK16-A30","url":null,"abstract":"Background: Breast cancer is the most common cancer diagnosis among women in Nebraska. Early diagnosis of breast cancer provides opportunities for better prognosis and treatment options and thereby improves chances of survival. Nebraska is predominantly a rural state, and hence, in addition to problems of affordability of health care due to lack of insurance or under-insurance, the people of rural Nebraska face unique challenges with regards to the availability and accessibility of cancer screening services. The purpose of this study was to examine whether access to cancer screening services, in terms of three dimensions: affordability, availability and accessibility, predict the stage of diagnosis for women diagnosed with breast cancer in Nebraska. Methods: Data on breast cancer cases in Nebraska were obtained from the Nebraska Cancer Registry for the years 2008 to 2012. Proximity to the nearest screening center was calculated as the shortest distance between the population weighted centroid of each census tract in Nebraska and the nearest screening facility, using geocoded facility locations available from the United States Food and Drug Administration website. Spatial accessibility to primary care provider (PCP) was calculated using the two-step floating catchment area method using geocoded PCP locations, using data from the University of Nebraska Medical Center Health Professions Tracking Service annual survey database. Hierarchical logistic regression models adjusted for age, race, ethnicity, marital status, rurality of residence and county poverty level were examined to assess the association of type of insurance: Medicare, Medicaid, Other (including TRICARE, Military, Veterans Affairs Indian/Public Health Service) and Private, supply of screening centers, proximity to screening center and spatial accessibility to primary care physicians with the stage at diagnosis of breast cancer. Breast cancer stage at diagnosis was categorized as early (in-situ or localized stage) or late (regional or distant stage). Geocoding and proximity distance calculations were done using ArcGIS 10.3.2 and statistical analyses were conducted using STATA 14 software. Results: Among 4,975 women aged 40 years or older and diagnosed with breast cancer in Nebraska between 2008 and 2012, 72.3% were diagnosed at an early stage (in-situ or localized). The results from the hierarchical logistic regression found that women who were uninsured were less likely (Odds Ratio [O.R]: 0.42; 95% Confidence Interval [C.I]: 0.25-0.73) to be diagnosed early and those women who had Medicaid coverage were also less likely (O.R: 0.56; 95% C.I: 0.40-0.78) to be diagnosed early, as compared to women having private insurance. Further, married women were 1.3 times more likely (O.R: 1.25; 95% C.I: 1.10-1.44) to be diagnosed early, and white women were 1.4 times more likely (O.R: 1.36; 95% C.I: 1.04-1.77) to be diagnosed early. Conclusion: Affordability of cancer screening services plays an imp","PeriodicalId":9487,"journal":{"name":"Cancer Epidemiology and Prevention Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81209815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract A16: Fibroadenomas on benign breast biopsy and subsequent breast cancer risk in an African American cohort","authors":"Asra N. Shaik, J. Ruterbusch, E. Abdulfatah, M. Ghanim, M. F. Daaboul, V. Pardeshi, R. Ali-Fehmi, D. Visscher, S. Bandyopadhyay, M. Cote","doi":"10.1158/1538-7755.CARISK16-A16","DOIUrl":"https://doi.org/10.1158/1538-7755.CARISK16-A16","url":null,"abstract":"Introduction: The majority of the 1.6 million breast biopsies performed annually in the United States are benign; however, several breast cancer risk models consider a benign biopsy a factor that increases risk of subsequent breast cancer. Fibroadenomas (FA), benign tumors of epithelial and stromal tissue, occur frequently in premenopausal women and more frequently in African American (AA) women than European American (EA) women. A small increased risk of subsequent breast cancer due to FA has been reported in some studies of EA women. We sought to investigate whether the risk of this lesion differs for AA women. Methods: Benign breast biopsies from 3895 AA women diagnosed between 1997 and 2010 in metropolitan Detroit were reviewed for 12 benign features including FA, ductal ectasia, fibrosis, apocrine metaplasia, ductal hyperplasia, lobular hyperplasia, calcifications, cysts, intraductal papilloma, radial scar, sclerosing adenosis, and columnar alterations. These features were also used to categorize FA into simple and complex FA, where complex FA occurs when FA is accompanied by at least one of the following features: cysts, calcifications, apocrine metaplasia or intraductal papilloma. Women were followed for subsequent breast cancer using the Detroit Surveillance, Epidemiology, and End Results (SEER) cancer registry. Associations between FA and other benign lesions were examined using chi-square tests. Risk of breast cancer was estimated by relative risk ratios and 95% confidence intervals calculated using logistic regression. All models were adjusted for age at biopsy and additionally adjusted for presence of proliferative disease with or without atypia. Results: Of the 3895 AA women, 46.5% presented with FA on biopsy. FA occurred more frequently in biopsies of younger women (p-value Conclusions: FA are negatively associated with other benign breast disease features. Risk of breast cancer may be reduced in women with FA compared to women with other types of benign lesions. These findings have important implications for modeling breast cancer risk particularly among AA women for whom FAs are common. Citation Format: Asra N. Shaik, Julie J. Ruterbusch, Eman Abdulfatah, Marcel T. Ghanim, MHD Fayez Daaboul, Visakha Pardeshi, Rouba Ali-Fehmi, Daniel W. Visscher, Sudeshna Bandyopadhyay, Michele L. Cote. Fibroadenomas on benign breast biopsy and subsequent breast cancer risk in an African American cohort. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr A16.","PeriodicalId":9487,"journal":{"name":"Cancer Epidemiology and Prevention Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82041902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract IA22: Using risk assessment tools to motivate behavior change","authors":"Erika A. Waters","doi":"10.1158/1538-7755.CARISK16-IA22","DOIUrl":"https://doi.org/10.1158/1538-7755.CARISK16-IA22","url":null,"abstract":"Epidemiology identifies risk factors for cancer and other diseases based on the idea that conveying such information to healthcare providers, the general public, and policy makers will result in population-wide improvements in healthy behaviors and, consequently, population-wide improvements in health outcomes. These actions assume that the audience understands and uses the information to make health-related decisions. However, the language of epidemiology, which is steeped in probabilistic thinking, is not necessarily the language of the general public. Furthermore, growing evidence suggests that the language of epidemiology is not particularly well-understood by policy makers or even, disconcertingly, by some healthcare providers. This presentation will accomplish three objectives. First, it will demonstrate how a user-friendly, Internet-based, personalized risk assessment tool that uses established principles of risk communication and is grounded in health behavior change theories can increase motivation to change behavior. It will accomplish this in the context of using Your Disease Risk to inform women about the association between physical activity and breast cancer risk. Second, it will illustrate the development of a novel personalized risk assessment tool that increases understanding of the link between lifestyle behaviors and overall health and wellness. Specifically, it translates cumulative incidence data about five diseases that cause significant morbidity and mortality (i.e., colon cancer, breast cancer (women), heart disease, diabetes, and stroke) into a tool that conveys personalized risk estimates in a comprehensible and useful way for laypeople from diverse socio-demographic backgrounds. The premise is that illustrating how a single behavior can affect the likelihood of developing several diseases could foster a more coherent and meaningful picture of the behavior9s importance in reducing health risks and could increase motivation to engage in the behavior. The behavioral context for this study is also physical activity. Third, this presentation discuss the limits of tools that convey only risk information and do not help users bridge the gap between wanting to change their behavior and having the knowledge, skills, and confidence to actually initiate and maintain such changes. Citation Format: Erika A. Waters. Using risk assessment tools to motivate behavior change. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr IA22.","PeriodicalId":9487,"journal":{"name":"Cancer Epidemiology and Prevention Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89427340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract B12: The effect of physical activity and body size on mammographic density in high-risk, BRCA mutation-negative women","authors":"O. Moran, Dina Nikitina, A. Gunasekara, M. Yaffe, K. Metcalfe, S. Narod, J. Kotsopoulos","doi":"10.1158/1538-7755.CARISK16-B12","DOIUrl":"https://doi.org/10.1158/1538-7755.CARISK16-B12","url":null,"abstract":"Purpose: Mammographic density (MD) reflects the proportion of dense tissue in relation to non-dense tissue in the breast and is the strongest biological marker of breast cancer risk. MD is known to be higher among women with a family history compared to women in the general population. We have previously demonstrated that women with a strong family history of breast cancer but no BRCA mutation face an elevated lifetime risk of breast cancer estimated at 40% compared to 11% in the general population. Various lifestyle factors, such as physical activity and body mass index (BMI), have been shown to modify MD in the general population. It is of interest to determine if such an association exists among high-risk women. Objective: To evaluate the relationship between physical activity, BMI and MD in high-risk women. Methods: This study included 100 women enrolled in an on-going prospective study of high-risk women with a strong family history of breast cancer (two first-degree relatives with breast cancer under age 50 or three cases at any age) and no identified BRCA mutations in their families. Current physical activity levels and BMI were collected using self-reported questionnaires. Physical activity was defined as moderate to vigorous physical activity (MVPA). Two dichotomous variables were created to define high vs. low MVPA levels: 1) based on the Canadian Society for Exercise Physiology guideline of 2.5 hours of MVPA per week and 2) the 75th percentile of MVPA in the sample (3.5 hours per week). A BMI of 25 or more was defined as high using the World Health Organization criteria of overweight. Mammograms were assigned a percentage of density (0 - 100%) using a computer-assisted method (Cumulus 6). Multivariate linear regression modelling was used to evaluate the relationships between both MVPA and BMI with MD while adjusting for age, menopausal status, and parity. BMI models also adjusted for MVPA (continuous) and MVPA models adjusted for BMI (continuous). Results: Among all women, those with a high BMI had significantly lower mean percent density compared to women with a low BMI (13% vs. 23%; P = 0.01). This association was stronger for premenopausal (27% vs. 37%; P = 0.06) vs. postmenopausal (12% vs. 20%; P = 0.10) women. Women who engaged in MVPA for 2.5 hours per week or more had significantly greater mean percent density compared to women who were less physically active (29% vs. 22%; P = 0.04). This relationship did not vary by menopausal status (P ≥ 0.15). Based on the 75th percentile of MVPA, women with high MVPA levels had significantly greater mean percent density compared to women with low MVPA levels (31% vs. 22%; P = 0.02). This relationship was significant for postmenopausal (26% vs. 13%; P = 0.04) but not premenopausal (31% vs. 25%; P = 0.27) women. Conclusion: In this cohort of high-risk women, high BMI was associated with lower MD that was suggestively stronger for premenopausal women. Although preliminary, these findings sugges","PeriodicalId":9487,"journal":{"name":"Cancer Epidemiology and Prevention Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74702790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}