Atkinson, Elizabeth J.

Abstract Advanced bone imaging with quantitative computed tomography (QCT) has had limited success in significantly improving fracture prediction beyond standard areal bone mineral density (aBMD) measurements. Thus, we examined whether a machine learning paradigm, gradient boosting machine (GBM) modeling, which can incorporate diverse measurements of bone density and geometry from central QCT imaging and of bone microstructure from high-resolution peripheral QCT imaging, can improve fracture prediction. We studied two cohorts of postmenopausal women: 105 with and 99 without distal forearm fractures (Distal Forearm Cohort) and 40 with at least one grade 2 or 3 vertebral deformity and 78 with no vertebral fracture (Vertebral Cohort). Within each cohort, individual bone density, structure, or strength variables had areas under receiver operating characteristic curves (AUCs) ranging from 0.50 to 0.84 (median 0.61) for discriminating women with and without fracture. Using all possible variables in the GBM model, the AUCs were close to 1.0. Fracture predictions in the Vertebral Cohort using the GBM models built with the Distal Forearm Cohort had AUCs of 0.82–0.95, whereas predictions in the Distal Forearm Cohort using models built with the Vertebral Cohort had AUCs of 0.80–0.83. Attempts at capturing a comparable parametric model using the top variables from the Distal Forearm Cohort resulted in resulted in an AUC of 0.81. Relatively high AUCs for differing fracture types suggest that an underlying fracture propensity is being captured by this modeling approach. More complex modeling, such as with GBM, creates stronger fracture predictions and may allow deeper insights into information provided by advanced bone imaging techniques. © 2012 American Society for Bone and Mineral Research.

Abstract Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3,628 breast cancer cases and 5,190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of single-nucleotide polymorphisms (SNP) were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case–control status as the outcome. This analysis was repeated using 10 different cutoff points for the most significant density SNPs (1%–10% representing 5,222–50,899 SNPs). Permutation analysis was also conducted across all 10 cutoff points. The association between risk score and breast cancer was significant for all cutoff points from 3% to 10% of top density SNPs, being most significant for the 6% (2-sided P = 0.002) to 10% (P = 0.001) cutoff points (overall permutation P = 0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR = 1.31; 95% confidence interval (CI), 1.08–1.59] compared with women in the bottom 10%. Together, our results show that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants. Cancer Res; 72(6); 1478–84. ©2012 AACR.

Abstract A positive association has been reported between greater bone density and higher breast cancer risk, suggesting that these women could be at reduced risk of fracture. To estimate fracture risk among unselected community women with breast cancer and to systematically assess associations with various risk factors including breast cancer treatments, we conducted a population-based historical cohort study of 608 Olmsted County, MN, USA, women with invasive breast cancer first diagnosed in 1990 to 1999 (mean age 61.6 ± 14.8 years), who were followed for 5776 person-years. Altogether, 568 fractures were observed in 270 women (98 per 1000 person-years). Overall fracture risk was elevated 1.8-fold, but the absolute increase in risk was only 9%, and 56% of the women did not experience a fracture during follow-up. Excluding pathologic fractures (15%) and those found incidentally (24%), to allow for ascertainment bias, the standardized incidence ratio was 1.2 (95% confidence interval [CI] 0.99 to 1.3) for total fracture risk and 0.9 (95% CI 0.7 to 1.2) for osteoporotic fracture risk alone. Various breast cancer treatments were associated with an increased risk of fracture, but those associations were strongest for pathologic fractures, which were relatively more common among the women who were premenopausal when their breast cancer was diagnosed. Moreover, underlying clinical characteristics prompting different treatments may have been partially responsible for the associated fracture outcomes (indication bias). These data thus demonstrate that breast cancer patients in general are not at greatly increased risk of fracture but neither are they protected from fractures despite any determinants that breast cancer and high bone density may have in common. © 2012 American Society for Bone and Mineral Research.

Abstract Previous studies using dual-energy X-ray absorptiometry (DXA) have demonstrated that age is a major predictor of bone fragility and fracture risk independent of areal bone mineral density (aBMD). Although this aBMD-independent effect of age has been attributed to poor bone “quality,” the structural basis for this remains unclear. Because high-resolution peripheral quantitative computed tomography (HRpQCT) can assess bone microarchitecture, we matched younger and older subjects for aBMD at the ultradistal radius and assessed for possible differences in trabecular or cortical microstructure by HRpQCT. From an age-stratified, random sample of community adults, 44 women aged <50 years (mean age 41.0 years) were matched to 44 women aged ≥50 years (mean age 62.7 years) by ultradistal radius aBMD (mean ± SEM, younger and older aBMD 0.475 ± 0.011 and 0.472 ± 0.011 g/cm2, respectively), and 57 men aged <50 years (mean age 41.3 years) were matched to 57 men aged ≥50 years (mean age 68.1 years; younger and older aBMD both 0.571 ± 0.008 g/cm2). In these matched subjects, there were no sex-specific differences in trabecular microstructural parameters. However, significant differences were noted in cortical microstructure (all p < 0.05): Older women and men had increased cortical porosity (by 91% and 56%, respectively), total cortical pore volume (by 77% and 61%, respectively), and mean cortical pore diameter (by 9% and 8%, respectively) compared with younger subjects. These findings indicate that younger and older women and men matched for DXA aBMD have similar trabecular microarchitecture but clearly different cortical microstructure, at least at an appendicular site represented by the radius. Further studies are needed to define the extent to which this deterioration in cortical microstructure contributes to the aBMD-independent effect of age on bone fragility and fracture risk at the distal radius and other sites of osteoporotic fractures. © 2012 American Society for Bone and Mineral Research