Within the nested case-control data set, we observed a significant association between plasma estradiol and risk of breast cancer (Ptrend < 0.001), with an RR for the top (Q4) versus bottom (Q1) quartile category of 3.3 (95% confidence interval [CI] = 1.8 to 6.0) for ER+ breast cancer (Table ). Each of the variables in the Rosner and Colditz risk prediction model was considered as a potential predictor of plasma estradiol. BMI was most strongly related to estradiol level; in addition, the birth index, case status, and duration of postmenopause each contributed modestly but significantly (Table ). Other variables, including family history of breast cancer, alcohol intake, and history of BBD, did not contribute significantly to the model and thus were dropped from further consideration. The r2, for the regression model, was 0.219.
Relative risk of estrogen receptor-positive breast cancer by quartile of postmenopausal plasma estradiol concentration (164 cases and 346 controls)a
Imputation of log estradiol using data from the Nurses' Health Study breast cancer nested case-control studya
Most variables in the Rosner and Colditz model incorporate a time component (for example, postmenopausal BMI = average BMI postmenopause × duration postmenopause). Because exposure status at the time of blood draw might be most strongly correlated with estradiol, we also evaluated each of the variables at the time of blood draw or, for variables ascertained only on the main study questionnaire (for example, alcohol intake), within 2 years of blood draw. All results were similar.
In Table , we present the standard risk prediction model without estradiol and an enhanced model with imputed estradiol based on an average of five imputations. The regression coefficient for loge estradiol varied over the five imputations (0.400 to 0.582) with an average of 0.477. For a one-unit increase in loge estradiol, the RR was 1.61 (95% CI = 1.35 to 1.93). Its inclusion also caused changes in some of the other model parameters. As expected, the regression coefficient for postmenopausal BMI decreased from 0.0038 (P < 0.001) to 0.0023 (P = 0.002). For example, if we compare two 70-year-old postmenopausal women with age at menopause of 50 years, no PMH use, and constant BMI of 20 and 30, respectively, from age 50 to 70, then the RRs of breast cancer at age 70 for the woman with BMI = 30 versus the woman with BMI = 20 would be exp(0.0038 × 10 × 20) = 2.1 (95% CI = 1.7 to 2.7) without controlling for estradiol and exp(0.0023 × 10 × 20) = 1.6 (95% CI = 1.2 to 2.1) after controlling for estradiol. Also, the regression coefficient for the birth index decreased from -0.0030 ± 0.0007 (P < 0.001) to -0.0020 ± 0.0008 (P = 0.02). To interpret this difference, we compare two postmenopausal women with age at menarche of 13 and age at menopause of 50, one of whom had four births at ages 20, 23, 26, and 29 whereas the other was nulliparous. The birth indices for these two women are 102 [(50 - 20) + (50 - 23) + (50 - 26) + (50 - 29)] and 0, respectively. The RRs for the parous versus nulliparous woman are exp [-0.0030(102)] = 0.74 (95% CI = 0.64 to 0.85) without and exp [-0.0020(102)] = 0.82 (95% CI = 0.69 to 0.96) with controlling for loge estradiol. Finally, the regression coefficient for both the duration after natural menopause and the duration after bilateral oophorectomy increased after adjusting for loge estradiol. To interpret this finding, we compare two postmenopausal women with age at natural menopause of 45 and 55 years, respectively. The RRs of breast cancer for the second compared with the first woman are exp [10(0.102-0.049)] = 1.7 (95% CI = 1.4 to 2.0) without and exp [10(0.101-0.056)] = 1.6 (95% CI = 1.3 to 1.9) with adjusting for loge estradiol. It appears that part of the effect of BMI, parity, and late menopause on the incidence of breast cancer is mediated in part by changes in loge estradiol caused by obesity (increase), multiparity with first birth at an early age (decrease), and delayed menopause (increase), respectively.
Risk prediction model for breast cancer with and without estradiol (loge)
We now present the cross-classification of model A × model B risk decile in Table . It is clear from Table that, within most model A risk deciles, there are important differences in estimated incidence according to model B risk decile (often twofold). Overall, for a given model A risk decile, the observed number of cases was higher than expected when the model B decile was high and lower than expected when the model B decile was low. The overall slope was β = 0.511 ± 0.034 (P < 0.001), indicating that there is a significant estimated 67% increase in breast cancer incidence for an increase of one model B age-specific risk decile, holding the age-specific model A risk decile constant. This indicated that there is substantial increased predictive power upon adding loge estradiol to the risk prediction model.
Cross-classification of model A risk decilea × model B risk decileb
In addition, we compared the age-specific C statistics between model A versus model B. We found C statistics of 0.635 ± 0.007 for model A and 0.645 ± 0.007 for model B (C statistic model A versus C statistic model B; P
< 0.001). Using our secondary approach (applying the population-based risk scores to the subset of women in the nested case-control study), the RRs of breast cancer by plasma hormone level were similar, though slightly attenuated, compared with those in Table . For example, the RRs of ER+
breast cancer with increasing quartile of estradiol were 1.0, 1.5, 1.4, and 2.5 (95% CI = 1.5 to 4.2). Finally, in Table , we present the 5-year incidence of breast cancer by age and model B risk decile after adjusting for competing mortality risks [23
]. The RR of breast cancer comparing women at the highest versus the lowest age-specific decile ranges from 5.0 to 8.5. For example, for 60- to 64-year-old women, the absolute 5-year risk of breast cancer is 436/105
(0.4%) for women in the first decile and 2,982/105
(3.0%) for women in the 10th decile (RR = 6.8), indicating substantial differences in absolute risk according to the model B risk equation.
Five-year risk of breast cancer by age and model B risk decile