Scott, Christopher G.

AbstractMammographic percent density (PD) is a strong risk factor for breast cancer, but there has been relatively little systematic evaluation of other features in mammographic images that might additionally predict breast cancer risk. We evaluated the association of a large number of image texture features with risk of breast cancer using a clinic-based case-control study of digitized film mammograms, all with screening mammograms before breast cancer diagnosis. The sample was split into training (123 cases and 258 controls) and validation (123 cases and 264 controls) data sets. Age-adjusted and body mass index (BMI)–adjusted odds ratios (OR) per SD change in the feature, 95% confidence intervals, and the area under the receiver operator characteristic curve (AUC) were obtained using logistic regression. A bootstrap approach was used to identify the strongest features in the training data set, and results for features that validated in the second half of the sample were reported using the full data set. The mean age at mammography was 64.0 ± 10.2 years, and the mean time from mammography to breast cancer was 3.7 ± 1.0 (range, 2.0-5.9 years). PD was associated with breast cancer risk (OR, 1.49; 95% confidence interval, 1.25-1.78). The strongest features that validated from each of several classes (Markovian, run length, Laws, wavelet, and Fourier) showed similar ORs as PD and predicted breast cancer at a similar magnitude (AUC = 0.58-0.60) as PD (AUC = 0.58). All of these features were automatically calculated (unlike PD) and measure texture at a coarse scale. These features were moderately correlated with PD (r = 0.39-0.76), and after adjustment for PD, each of the features attenuated only slightly and retained statistical significance. However, simultaneous inclusion of these features in a model with PD did not significantly improve the ability to predict breast cancer. (Cancer Epidemiol Biomarkers Prev 2009;18(3):837–45)

Abstract Purpose: Immunotherapeutic modalities are commonly used for treatment of patients with melanoma. The therapeutic success in preclinical models has not yielded the expected clinical results. To understand this discrepancy, we attempted to define immune homeostasis of 209 patients with melanoma across stages of disease relative to normal controls. Experimental Design: Peripheral blood mononuclear cells (PBMC) and plasma were collected from patients and healthy donors. PBMC were analyzed for frequencies of natural killer, dendritic, and T cells and their functional status. Matched plasma samples were analyzed for the concentrations of 27 cytokines, chemokines, and growth factors. RNA was isolated from 24 metastatic melanoma tumor biopsies and profiled by microarray analysis. Results: The frequency of natural killer, T, and dendritic cells in patients does not significantly change across stages of melanoma. However, plasma concentrations of Th2 cytokines [interleukin (IL)-4, IL-5, IL-10, and IL-13] in tumor-bearing patients were significantly higher than those with resected melanoma. Expression array analysis of metastatic melanoma revealed that the malignant melanocytes were not the source of the Th2 cytokines but did highly up-regulate vascular endothelial growth factor (VEGF) transcripts, consistent with plasma VEGF concentrations. In vitro VEGF exposure of normal PBMC lead to repolarization from Th1 to Th2 emulating the state of metastatic melanoma. Conclusions: Patients with metastatic melanoma exist in a state of Th2-mediated “chronic inflammation” as a result of at least VEGF overproduction by malignant tumors. These data support prior observations regarding the effect of VEGF on immune cell function and suggests consideration of VEGF inhibitors in future cancer immunotherapy clinical studies in metastatic melanoma.

Abstract Breast density is a strong risk factor for breast cancer; however, no standard assessment method exists. An automated breast density method was modified and compared with a semi-automated, user-assisted thresholding method (Cumulus method) and the Breast Imaging Reporting and Data System four-category tissue composition measure for their ability to predict future breast cancer risk. The three estimation methods were evaluated in a matched breast cancer case-control (n = 372 and n = 713, respectively) study at the Mayo Clinic using digitized film mammograms. Mammograms from the craniocaudal view of the noncancerous breast were acquired on average 7 years before diagnosis. Two controls with no previous history of breast cancer from the screening practice were matched to each case on age, number of previous screening mammograms, final screening exam date, menopausal status at this date, interval between earliest and latest available mammograms, and residence. Both Pearson linear correlation (R) and Spearman rank correlation (r) coefficients were used for comparing the three methods as appropriate. Conditional logistic regression was used to estimate the risk for breast cancer (odds ratios and 95% confidence intervals) associated with the quartiles of percent breast density (automated breast density method, Cumulus method) or Breast Imaging Reporting and Data System categories. The area under the receiver operator characteristic curve was estimated and used to compare the discriminatory capabilities of each approach. The continuous measures (automated breast density method and Cumulus method) were highly correlated with each other (R = 0.70) but less with Breast Imaging Reporting and Data System (r = 0.49 for automated breast density method and r = 0.57 for Cumulus method). Risk estimates associated with the lowest to highest quartiles of automated breast density method were greater in magnitude [odds ratios: 1.0 (reference), 2.3, 3.0, 5.2; P trend < 0.001] than the corresponding quartiles for the Cumulus method [odds ratios: 1.0 (reference), 1.7, 2.1, and 3.8; P trend < 0.001] and Breast Imaging Reporting and Data System [odds ratios: 1.0 (reference), 1.6, 1.5, 2.6; P trend < 0.001] method. However, all methods similarly discriminated between case and control status; areas under the receiver operator characteristic curve were 0.64, 0.63, and 0.61 for automated breast density method, Cumulus method, and Breast Imaging Reporting and Data System, respectively. The automated breast density method is a viable option for quantitatively assessing breast density from digitized film mammograms. (Cancer Epidemiol Biomarkers Prev 2008;17(11):3090–7)

AbstractBackground: Limited studies have examined the associations between mammographic density and subsequent breast tumor characteristics.Methods: Eligible women were part of a case-control study of postmenopausal breast cancer, were 40 years or older and had a routine mammogram 4 years or more before their diagnosis. Mammographic density (percent density, dense area, and nondense area) was estimated using a computer-assisted thresholding program. At the time of cancer diagnosis, cases were classified as asymptomatic or symptomatic based on medical record review and breast imaging workup. Pathologic review was done blinded to the density status. Linear regression models and tests for trend examined the association between pathologic characteristics of the breast tumor and the components of density for all participants, and stratified by symptom status at diagnosis.Results: Of the 286 eligible cases, 77% were 60 years or older and mean percent density was 29.5% (SD, 14.6%). Density was not significantly associated with tumor size (P = 0.22), histologic type (P = 0.77), estrogen receptor (P = 0.11) or progesterone receptor (P = 0.37) status, mitotic activity (P = 0.12), or nuclear pleomorphism (P = 0.09; P values for percent density). An inverse association was suggested between tumor grade and percent density (32.0%, 30.3%, 26.7% for grades 1-3; P = 0.06 for trend). The inverse association with tumor grade and its components (nuclear pleomorphism and tubular differentiation) was only evident among the 97 symptomatic women; positive associations of estrogen receptor (P = 0.009) and progesterone receptor (P = 0.04) were also seen with percent density only in this subgroup.Conclusions: The inverse association between tumor grade and percent density in the symptomatic population could inform the biology of the association between mammographic density and breast cancer risk. (Cancer Epidemiol Biomarkers Prev 2008;17(4):872–9)

Abstract Background: Mammographic density is a strong risk factor for breast cancer. However, whether changes in mammographic density are associated with risk remains unclear. Materials and Methods: A study of 372 incident breast cancer cases and 713 matched controls was conducted within the Mayo Clinic mammography screening practice. Controls were matched on age, exam date, residence, menopause, interval between, and number of mammograms. All serial craniocaudal mammograms 10 years before ascertainment were digitized, and quantitative measures of percent density (PD) were estimated using a thresholding method. Data on potential confounders were abstracted from medical records. Logistic regression models with generalized estimating equations were used to evaluate the interactions among PD at earliest mammogram, time from earliest to each serial mammogram, and absolute change in PD between the earliest and subsequent mammograms. Analyses were done separately for PD measures from the ipsilateral and contralateral breast and also by use of hormone therapy (HT). Results: Subjects had an average of five mammograms available, were primarily postmenopausal (83%), and averaged 61 years at the earliest mammogram. Mean PD at earliest mammogram was higher for cases (31%) than controls (27%; ipsilateral side). There was no evidence of an association between change in PD and breast cancer risk by time. Compared with no change, an overall reduction of 10% PD (lowest quartile of change) was associated with an odds ratio of 0.9997 and an increase of 6.5% PD (highest quartile of change) with an odds ratio of 1.002. The same results held within the group of 220 cases and 340 controls never using HT. Among the 124 cases and 337 controls known to use HT during the interval, there was a statistically significant interaction between change in PD and time since the earliest mammogram (P = 0.01). However, in all groups, the risk associated with the earliest PD remained a stronger predictor of risk than change in PD. Conclusion: We observed no association between change in PD with breast cancer risk among all women and those never using HT. However, the interaction between change in PD and time should be evaluated in other populations. (Cancer Epidemiol Biomarkers Prev 2007;16(5):921–8)

Abstract Mammographic breast density is a strong risk factor for breast cancer but whether breast density is a general marker of susceptibility or is specific to the location of the eventual cancer is unknown. A study of 372 incident breast cancer cases and 713 matched controls was conducted within the Mayo Clinic mammography screening practice. Mammograms on average 7 years before breast cancer were digitized, and quantitative measures of percentage density and dense area from each side and view were estimated. A regional density estimate accounting for overall percentage density was calculated from both mammogram views. Location of breast cancer and potential confounders were abstracted from medical records. Conditional logistic regression was used to estimate associations, and C-statistics were used to evaluate the strength of risk prediction. There were increasing trends in breast cancer risk with increasing quartiles of percentage density and dense area, irrespective of the side of the breast with cancer (Ptrends < 0.001). Percentage density from the ipsilateral side [craniocaudal (CC): odds ratios (ORs), 1.0 (ref), 1.7, 3.1, and 3.1; mediolateral oblique (MLO): ORs, 1.0 (ref), 1.5, 2.2, and 2.8] and the contralateral side [CC: ORs, 1.0 (ref), 1.8, 2.2, and 3.7; MLO: ORs, 1.0 (ref), 1.6, 1.9, and 2.5] similarly predicted case-control status (C-statistics, 0.64-65). Accounting for overall percentage density, density in the region where the cancer subsequently developed was not a significant risk factor [CC: 1.0 (ref), 1.3, 1.0, and 1.2; MLO: 1.0 (ref), 1.1, 1.0, and 1.1 for increasing quartiles]. Results did not change when examining mammograms 3 years on average before the cancer. Overall mammographic density seems to represent a general marker of breast cancer risk that is not specific to breast side or location of the eventual cancer. (Cancer Epidemiol Biomarkers Prev 2007;16(1):43–9)

Background— Aortic valve calcification (AVC) is considered degenerative. Recent data suggested links to atherosclerosis or coronary disease (CAD). Methods and Results— AVC and coronary artery calcifications (CAC) were prospectively assessed by Electron-Beam-Computed-Tomography in 262 population-based research participants ≥60 years. AVC was frequent (27%) with aging ( P <0.01) and in men ( P <0.05). AVC was associated with diabetes, hypertension, higher body-mass-index, and serum glucose (all P <0.05). AVC was a marker of higher prevalence ( P <0.01) and severity of CAD (CAC score: 441±802 versus 265±566, P <0.05) independently of age. After follow-up of 3.8±0.9 years, AVC score increased (94±271 versus 54±173, P <0.01, +11±32 U/year), faster with higher baseline AVC score ( P <0.01). Compared with participants remaining free of AVC, de novo acquisition of AVC was associated with higher LDL-cholesterol (141±31 versus 121±27 mg/dL, P <0.05) and faster CAC progression (+78±87 versus +28±47 U/year, P <0.05). In multivariate analysis, LDL-cholesterol independently determined AVC acquisition while higher baseline AVC scores determined faster progression of existing AVC. Conclusion— In the population, AVC is frequent with aging and atherosclerotic risk factors. AVC is a marker of subclinical CAD. AVC is progressive, appearing de novo with progressive atherosclerosis whereas established AVC progresses independently of atherosclerotic risk factors and faster with increasing initial AVC loads.

Background— In the elderly, mitral regurgitation (MR) is frequent, but surgery risks are considered high. Benefits and indications of MR surgery are uncertain in the elderly. Methods and Results— Baseline characteristics, outcome, and trends for surgical results improvement were analyzed in elderly patients (≥75 years of age; n=284) operated on for MR in 1980 to 1995 compared with younger patients (65 to 74 years of age, n=504; and <65 years of age, n=556). Preoperatively, class III to IV symptoms, atrial fibrillation, coronary disease, creatinine, and comorbidity index were more severe in elderly patients (all P <0.002). In the long term after surgery, observed survival stratified by age (≥75, 65 to 74, <65 years) was lower in elderly than in younger patients (at 5 years, 57±3%, 73±2%, and 85±2%, respectively; P <0.001), but ratios of observed to expected survival were similar (83%, 85%, and 88%, respectively). In multivariate analysis adjusted to expected survival, elderly patients showed no difference in life expectancy restoration compared with younger patients (adjusted hazard ratio, 0.89; 95% confidence interval, 0.73 to 1.30; P =0.54). Temporal trends showed that risk of operative mortality, although higher in elderly patients ( P <0.001), declined markedly for all ages (27% to 5% in those ≥75 years of age, P <0.01; 21% to 4% in those 65 to 74 years of age, P <0.01; and 7% to 2% in those <65 years of age, P =0.06), with a parallel decline in low cardiac output and length of hospital stay. Over time, valve repair feasibility increased in all age groups (30% to 84% overall and 31% to 93% in degenerative MR; P <0.0001). Conclusions— Elderly patients undergoing MR surgery display more severe preoperative characteristics and incur higher operative risks than younger patients. However, restoration of life expectancy after surgery is similar in elderly and younger patients, and outstanding recent surgical improvements particularly benefited elderly patients. Thus, elderly patients with MR can now carefully be considered for surgery before refractory heart failure is present.

Background— This study assessed the long-term outcome of a large, asymptomatic population with hemodynamically significant aortic stenosis (AS). Methods and Results— We identified 622 patients with isolated, asymptomatic AS and peak systolic velocity ≥4 m/s by Doppler echocardiography who did not undergo surgery at the initial evaluation and obtained follow-up (5.4±4.0 years) in all. Mean age (±SD) was 72±11 years; there were 384 (62%) men. The probability of remaining free of cardiac symptoms while unoperated was 82%, 67%, and 33% at 1, 2, and 5 years, respectively. Aortic valve area and left ventricular hypertrophy predicted symptom development. During follow-up, 352 (57%) patients were referred for aortic valve surgery and 265 (43%) patients died, including cardiac death in 117 (19%). The 1-, 2-, and 5-year probabilities of remaining free of surgery or cardiac death were 80%, 63%, and 25%, respectively. Multivariate predictors of all-cause mortality were age (hazard ratio [HR], 1.05; P <0.0001), chronic renal failure (HR, 2.41; P =0.004), inactivity (HR, 2.00; P =0.001), and aortic valve velocity (HR, 1.46; P =0.03). Sudden death without preceding symptoms occurred in 11 (4.1%) of 270 unoperated patients. Patients with peak velocity ≥4.5 m/s had a higher likelihood of developing symptoms (relative risk, 1.34) or having surgery or cardiac death (relative risk, 1.48). Conclusions— Most patients with asymptomatic, hemodynamically significant AS will develop symptoms within 5 years. Sudden death occurs in ≈1%/y. Age, chronic renal failure, inactivity, and aortic valve velocity are independently predictive of all-cause mortality.

Background— B-type natriuretic peptide (BNP) activation observed in cardiac diseases is a predictor of poor outcome; however, in organic mitral regurgitation (MR), BNP determinants and prognostic value are unknown. Methods and Results— We prospectively enrolled 124 patients with chronic organic MR (aged 63±15 years, 60% males) in whom we measured BNP level and simultaneously quantified MR degree, left ventricular (LV) remodeling, and left atrial (LA) volumes and analyzed long-term outcome. Baseline BNP level (54±67 pg/mL, median 31 pg/mL) was associated univariately with multiple clinical and echocardiographic characteristics, but in multivariate analysis, independent determinants of BNP, beyond age and sex (both P ≤0.01), were LV end-systolic volume index, LA volume, atrial fibrillation, and symptoms (all P <0.02). Conversely, MR degree was not independently associated with BNP. During follow-up, patients with high versus low BNP (≥31 versus <31 pg/mL) displayed lower survival rates (at 5 years, 72±10% versus 95±5%, P =0.03) and higher rates of the combined end point of death and heart failure (at 5 years, 42±10% versus 16±7%, P =0.03). In multivariate analysis, with adjustment for age, sex, functional class, MR severity, and ejection fraction, BNP was independently predictive of mortality (hazard ratio per 10 pg/mL, 1.23 [95% CI 1.07 to 1.48], P =0.004) and of death or heart failure (hazard ratio per 10 pg/mL, 1.09 [95% CI 1.001 to 1.19], P =0.04). Conclusions— BNP activation in organic MR reflects primarily ventricular and atrial consequences rather than degree of MR. Higher BNP level in patients with organic MR independently predicts adverse events under conservative management. Therefore, BNP activation in organic MR is an emerging biomarker of severity of MR consequences and of poor clinical outcome, and its assessment should be considered in the clinical evaluation and risk stratification of patients with MR.