Relationship of Predicted Risk of Developing Invasive Breast Cancer, as Assessed with Three Models, and Breast Cancer Mortality among Breast Cancer Patients

<div><p>Purpose</p><p>Breast cancer risk prediction models are used to plan clinical trials and counsel women; however, relationships of predicted risks of breast cancer incidence and prognosis after breast cancer diagnosis are unknown.</p><p>Methods</p><p>Using largely pre-diagnostic information from the Breast Cancer Surveillance Consortium (BCSC) for 37,939 invasive breast cancers (1996–2007), we estimated 5-year breast cancer risk (<1%; 1–1.66%; ≥1.67%) with three models: BCSC 1-year risk model (BCSC-1; adapted to 5-year predictions); Breast Cancer Risk Assessment Tool (BCRAT); and BCSC 5-year risk model (BCSC-5). Breast cancer-specific mortality post-diagnosis (range: 1–13 years; median: 5.4–5.6 years) was related to predicted risk of developing breast cancer using unadjusted Cox proportional hazards models, and in age-stratified (35–44; 45–54; 55–69; 70–89 years) models adjusted for continuous age, BCSC registry, calendar period, income, mode of presentation, stage and treatment. Mean age at diagnosis was 60 years.</p><p>Results</p><p>Of 6,021 deaths, 2,993 (49.7%) were ascribed to breast cancer. In unadjusted case-only analyses, predicted breast cancer risk ≥1.67% versus <1.0% was associated with lower risk of breast cancer death; BCSC-1: hazard ratio (HR) = 0.82 (95% CI = 0.75–0.90); BCRAT: HR = 0.72 (95% CI = 0.65–0.81) and BCSC-5: HR = 0.84 (95% CI = 0.75–0.94). Age-stratified, adjusted models showed similar, although mostly non-significant HRs. Among women ages 55–69 years, HRs approximated 1.0. Generally, higher predicted risk was inversely related to percentages of cancers with unfavorable prognostic characteristics, especially among women 35–44 years.</p><p>Conclusions</p><p>Among cases assessed with three models, higher predicted risk of developing breast cancer was not associated with greater risk of breast cancer death; thus, these models would have limited utility in planning studies to evaluate breast cancer mortality reduction strategies. Further, when offering women counseling, it may be useful to note that high predicted risk of developing breast cancer does not imply that if cancer develops it will behave aggressively.</p></div

Predicted risk of developing breast cancer versus risk of death (age-stratified, adjusted models).

<p>Age-stratified models, adjusted for age in single years, registry, year of diagnosis, mode of detection, AJCC stage, treatment (surgery and chemotherapy: yes/no) and income (zip code of residence)</p

Characteristics of 37,939 Women with Breast Cancer.

<p>Characteristics of 37,939 Women with Breast Cancer.</p

Predicted 5-year risk of developing breast cancer versus clinicopathologic characteristics.

<p>Predicted 5-year risk of developing breast cancer versus clinicopathologic characteristics.</p

Spearman correlations (r) of age, continuous mammographic measures and BMI^<b>a</b>.

a<p>P<0.001 for all correlations. Abbreviation-BMI: body mass index </p

Characteristics of the overall analytical sample and by percentiles of nondense mammographic area.

<p>Comparisons between groups from ANOVA for continuous variables and Chi-Square test for categorical variables. P value from Wald statistic to test for an overall effect across percentiles of nondense mammographic area. ^a Log-transformed cm², ^b Square root-transformed cm² and percent. Abbreviations-BMI: body mass index, IQR: interquartile range</p

Associations between mammographic measures (per standard deviation difference) and risk of mortality.

<p>^a Model 1 unadjusted; ^b Model 2 age-adjusted; ^c Model 3 adjusted for age, education, race, smoking history, type of mammogram (xerogram versus x-ray), diabetes and heart disease. ^d Model 4 adjusted for Model 2 covariates plus body mass index. P value from Wald statistic. All statistical tests were two-sided. Abbreviations-CI: confidence interval, HR: hazard ratio.</p

Associations between percentiles of mammographic measures and risk of mortality.

<p>^a Model 1 unadjusted; ^b Model 2 age-adjusted; ^c Model 3 adjusted for age, education, race, smoking history, type of mammogram (xerogram versus x-ray), diabetes and heart disease. ^d Model 4 adjusted for Model 2 covariates plus body mass index. P value from Wald statistic to test for an overall effect of categories of mammographic measures. All statistical tests were two-sided. Abbreviations-CI: confidence interval, HR: hazard ratio.</p

Distribution of risk factors and diagnostic factors by CIN3 size among women in SUCCEED diagnosed as CIN3 by LEEP (N = 309).

a<p>High Risk/Oncogenic HPV type defined as positive for any of the following HPV types: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68.</p

LEEPs performed among SUCCEED women in a colposcopy clinic, 2003–2010.

<p>LEEPs performed among SUCCEED women in a colposcopy clinic, 2003–2010.</p