Risk prediction models with incomplete data with application to prediction of estrogen receptor-positive breast cancer: prospective data from the Nurses' Health Study

Introduction A number of breast cancer risk prediction models have been developed to provide insight into a woman\u27s individual breast cancer risk. Although circulating levels of estradiol in postmenopausal women predict subsequent breast cancer risk, whether the addition of estradiol levels adds significantly to a model\u27s predictive power has not previously been evaluated. Methods Using linear regression, the authors developed an imputed estradiol score using measured estradiol levels (the outcome) and both case status and risk factor data (for example, body mass index) from a nested case-control study conducted within a large prospective cohort study and used multiple imputation methods to develop an overall risk model including both risk factor data from the main cohort and estradiol levels from the nested case-control study. Results The authors evaluated the addition of imputed estradiol level to the previously published Rosner and Colditz log-incidence model for breast cancer risk prediction within the larger Nurses\u27 Health Study cohort. The follow-up was from 1980 to 2000; during this time, 1,559 invasive estrogen receptor-positive breast cancer cases were confirmed. The addition of imputed estradiol levels significantly improved risk prediction; the age-specific concordance statistic increased from 0.635 ± 0.007 to 0.645 ± 0.007 (P \u3c 0.001) after the addition of imputed estradiol. Conclusion Circulating estradiol levels in postmenopausal women appear to add to other lifestyle factors in predicting a woman\u27s individual risk of breast cancer

Breast density and polymorphisms in genes coding for CYP1A2 and COMT: the Multiethnic Cohort

BACKGROUND: Mammographic density is a strong predictor of breast cancer risk and is increased by hormone replacement therapy (HRT). Some associations with genetic polymorphisms in enzymes involved in estrogen metabolism have been described. This cross-sectional analysis examined the relation between mammographic density and the CYP1A2*1F and COMT Val(58 )Met polymorphisms among 332 breast cancer cases and 254 controls in the Hawaii component of the Multiethnic Cohort. METHODS: Mammographic density, before diagnosis in cases, was quantified by using a validated computer-assisted method. Blood samples were genotyped by standard PCR/RFLP methods. Adjusted mean percent density was calculated by genotype using mixed models with the unstructured covariance option. RESULTS: A positive association between the C allele in the CYP1A2*1F gene and percent density, but not the dense area, was suggested (p = 0.11). The relation was limited to controls (p = 0.045), postmenopausal women not using HRT (p = 0.08), and normal weight subjects (p = 0.046). We did not observe any relation between the COMT Val(58 )Met polymorphism and breast density. CONCLUSION: The lack of an association between the CYP1A2 genotype and the size of the dense areas suggests an effect on the non-dense, i.e., fatty breast tissue. The discrepancies among studies may be due to differential susceptibility; changes in enzyme activity as a result of the CYP1A2*1F polymorphism may influence breast tissue differently depending on hormonal status. Larger studies with the ability to look at interactions would be useful to elucidate the influence of genetic variation in CYP1A2 and COMT on the risk of developing breast cancer

Sex steroids, growth factors and mammographic density: a cross-sectional study of UK postmenopausal Caucasian and Afro-Caribbean women

INTRODUCTION: Sex steroids, insulin-like growth factors (IGFs) and prolactin are breast cancer risk factors but whether their effects are mediated through mammographic density, one of the strongest risk factors for breast cancer, is unknown. If such a hormonal basis of mammographic density exists, hormones may underlie ethnic differences in both mammographic density and breast cancer incidence rates. METHODS: In a cross-sectional study of 270 postmenopausal Caucasian and Afro-Caribbean women attending a population-based breast screening service in London, UK, we investigated whether plasma biomarkers (oestradiol, oestrone, sex hormone binding globulin (SHBG), testosterone, prolactin, leptin, IGF-I, IGF-II and IGF binding protein 3 (IGFBP3)) were related to and explained ethnic differences in mammographic percent density, dense area and nondense area, measured in Cumulus using the threshold method. RESULTS: Mean levels of oestrogens, leptin and IGF-I:IGFBP3 were higher whereas SHBG and IGF-II:IGFBP3 were lower in Afro-Caribbean women compared with Caucasian women after adjustment for higher mean body mass index (BMI) in the former group (by 3.2 kg/m(2) (95% confidence interval (CI): 1.8, 4.5)). Age-adjusted percent density was lower in Afro-Caribbean compared with Caucasian women by 5.4% (absolute difference), but was attenuated to 2.5% (95% CI: -0.2, 5.1) upon BMI adjustment. Despite ethnic differences in biomarkers and in percent density, strong ethnic-age-adjusted inverse associations of oestradiol, leptin and testosterone with percent density were completely attenuated upon adjustment for BMI. There were no associations of IGF-I, IGF-II or IGFBP3 with percent density or dense area. We found weak evidence that a twofold increase in prolactin and oestrone levels were associated, respectively, with an increase (by 1.7% (95% CI: -0.3, 3.7)) and a decrease (by 2.0% (95% CI: 0, 4.1)) in density after adjustment for BMI. CONCLUSIONS: These findings suggest that sex hormone and IGF levels are not associated with BMI-adjusted percent mammographic density in cross-sectional analyses of postmenopausal women and thus do not explain ethnic differences in density. Mammographic density may still, however, be influenced by much higher premenopausal hormone levels

Design of the sex hormones and physical exercise (SHAPE) study

<p>Abstract</p> <p>Background</p> <p>Physical activity has been associated with a decreased risk for breast cancer. The biological mechanismn(s) underlying the association between physical activity and breast cancer is not clear. Most prominent hypothesis is that physical activity may protect against breast cancer through reduced lifetime exposure to endogenous hormones either direct, or indirect by preventing overweight and abdominal adiposity. In order to get more insight in the causal pathway between physical activity and breast cancer risk, we designed the <it>Sex Hormones and Physical Exercise (SHAPE) </it>study. Purpose of SHAPE study is to examine the effects of a 1-year moderate-to-vigorous intensity exercise programme on endogenous hormone levels associated with breast cancer among sedentary postmenopausal women and whether the amount of total body fat or abdominal fat mediates the effects.</p> <p>Methods/Design</p> <p>In the SHAPE study, 189 sedentary postmenopausal women, aged 50–69 years, are randomly allocated to an intervention or a control group. The intervention consists of an 1-year moderate-to-vigorous intensity aerobic and strenght training exercise programme. Partcipants allocated to the control group are requested to retain their habitual exercise pattern. Primary study parameters measured at baseline, at four months and at 12 months are: serum concentrations of endogenous estrogens, endogenous androgens, sex hormone binding globuline and insuline. Other study parameters include: amount of total and abdominal fat, weight, BMI, body fat distribution, physical fitness, blood pressure and lifestyle factors.</p> <p>Discussion</p> <p>This study will contribute to the body of evidence relating physical activity and breast cancer risk and will provide insight into possible mechanisms through which physical activity might be associated with reduced risk of breast cancer in postmenopausal women.</p> <p>Trial registration</p> <p>NCT00359060</p