Scott, Christopher G.

SummaryLow leptin concentration has been shown to be associated with central sleep apnea in heart failure patients. We hypothesized that low leptin concentration predicts central sleep apnea. Consecutive ambulatory New York Heart Association (NYHA) classes I–IV heart failure patients were studied prospectively, including measurement of serum leptin, echocardiography and polysomnography. Sleep apnea was defined by type (central/mixed/obstructive) and by apnea–hypopnea index ≥5 by polysomnography. Subjects were divided into four groups by polysomnography: (1) central sleep apnea, (2) mixed apnea, (3) no apnea and (4) obstructive sleep apnea. Fifty‐six subjects were included. Eighteen subjects were diagnosed with central sleep apnea, 15 with mixed apnea, 12 with obstructive apnea and 11 with no sleep apnea. Leptin concentration was significantly lower in central sleep apnea compared to obstructive apnea (8 ± 10.7 ng mL−1 versus 19.7 ± 14.7 ng mL−1, P ˂ 0.01) or no sleep apnea (8 ± 10.7 ng mL−1 versus 17.1 ± 8.4 ng mL−1, P ˂ 0.01). Logistic regression showed leptin to be associated independently with central sleep apnea [odds ratio (OR): 0.19; 95% confidence interval (CI): 0.06–0.62; area under the curve (AUC): 0.80, P < 0.01]. For the detection of central sleep apnea, a cut‐off value for leptin concentration 5 ng mL−1 yielded a sensitivity of 50% and specificity of 89%. In conclusion, a low leptin concentration may have utility for the screening of heart failure patients for central sleep apnea.

Abstract Aims Chronic kidney disease (CKD) is prevalent and is associated with increased cardiovascular morbidity and mortality. The interaction between diastolic dysfunction (DD) and CKD in subjects with preserved systolic function is not well defined. This study sought to determine the association between renal function and DD in subjects with preserved ejection fraction. Methods and results Through the Rochester Epidemiology Project, subjects who underwent echocardiography over 2 years with EF ≥50% were identified and the clinical data were obtained. Glomerular filtration rate (GFR) was estimated using the modification of diet in renal disease equation. Linear regression was used to test for association of GFR and DD. DD was defined as follows: Grade 2 or pseudonormal pattern (0.75 &lt; E/A ≤ 1.5, E/e′ ≥ 10, DT &gt; 140 ms, ΔE/A ≥ 0.5, and PV S &lt; D) or Grade 3+ or restrictive pattern (E/A &gt; 1.5, E/e′ ≥ 10, DT &lt; 140 ms, and PV S &lt; D). Cox regression was used to assess correlation of GFR and DD with time-to-event outcomes. A total of 2056 patients were identified. There was significant correlation between worsening GFR and degree of DD assessed by echo Doppler E/e′ ratio (P = 0.005), left ventricular mass index (P = 0.004), and right ventricular systolic pressure (P = 0.01). Worsening GFR was associated with increased mortality, development of heart failure, and hospitalization (P &lt; 0.001). Within each GFR group, abnormal DD was associated with a higher risk of the clinical outcomes. No interaction between GFR and DD was noted, suggesting an increased risk of events associated with abnormal DD across ranges of GFR. Conclusions Worsening GFR was associated with a greater degree of diastolic dysfunction and adverse clinical outcomes. Within each GFR group, the presence of DD was associated with increased morbidity and mortality. Further studies are warranted to determine if improving DD in patients with CKD will benefit clinical outcomes.

Background— It is not known whether abnormal blood pressure (BP) responses during dobutamine stress echocardiography (DSE) are associated with abnormal test results, nor if such results indicate obstructive coronary artery disease (CAD). We sought to define the frequency of abnormal BP responses during DSE and their impact on accuracy of test results. Methods and Results— We studied 21 949 patients who underwent DSE at Mayo Clinic, Rochester, MN, grouped by peak systolic BP achieved during the test. We also analyzed a subgroup who underwent coronary angiography within 30 days after positive DSE. The positive predictive value of DSE was calculated for each BP group. Patients with hypertensive response (n=1905; 9%) were more likely to have positive DSE than those with normal (n=19 770; 90%) or hypotensive (n=274; 1%) BP responses (32% versus 21% versus 23%, respectively; P <0.0001). Angiography, performed in 1126 patients, showed obstructive CAD (≥50% stenosis) in 814 patients and severe CAD (≥70% stenosis) in 708 patients. Positive predictive value of DSE was similar for patients who had hypertensive and normal BP responses (69% versus 73%; P =0.3), considering 50% stenosis cut point. The proportion of severe CAD (≥70% stenosis) was lower in patients who had hypertensive response compared with those who had normal BP response (54% versus 65%; P =0.005). Conclusions— Patients with hypertensive response during DSE are more likely to have stress-induced myocardial ischemia compared with those with normal or hypotensive BP responses but are not more likely to have false-positive DSE results. They are, however, less likely to have higher grade or multivessel CAD.

Abstract Background: Reductions in breast density with tamoxifen and aromatase inhibitors may be an intermediate marker of treatment response. We compare changes in volumetric breast density among breast cancer cases using tamoxifen or aromatase inhibitors (AI) to untreated women without breast cancer. Methods: Breast cancer cases with a digital mammogram prior to diagnosis and after initiation of tamoxifen (n = 366) or AI (n = 403) and a sample of controls (n = 2170) were identified from the Mayo Clinic Mammography Practice and San Francisco Mammography Registry. Volumetric percent density (VPD) and dense breast volume (DV) were measured using Volpara (Matakina Technology) and Quantra (Hologic) software. Linear regression estimated the effect of treatment on annualized changes in density. Results: Premenopausal women using tamoxifen experienced annualized declines in VPD of 1.17% to 1.70% compared with 0.30% to 0.56% for controls and declines in DV of 7.43 to 15.13 cm3 compared with 0.28 to 0.63 cm3 in controls, for Volpara and Quantra, respectively. The greatest reductions were observed among women with ≥10% baseline density. Postmenopausal AI users had greater declines in VPD than controls (Volpara P = 0.02; Quantra P = 0.03), and reductions were greatest among women with ≥10% baseline density. Declines in VPD among postmenopausal women using tamoxifen were only statistically greater than controls when measured with Quantra. Conclusions: Automated software can detect volumetric breast density changes among women on tamoxifen and AI. Impact: If declines in volumetric density predict breast cancer outcomes, these measures may be used as interim prognostic indicators. Cancer Epidemiol Biomarkers Prev; 26(6); 930–7. ©2017 AACR.

Background: Cardiomyocytes are resistant to radiation. However, cardiac radiation exposure causes coronary microvascular endothelial inflammation, a perturbation implicated in the pathogenesis of heart failure (HF) and particularly HF with preserved ejection fraction (HFpEF). Radiotherapy for breast cancer results in variable cardiac radiation exposure and may increase the risk of HF. Methods: We conducted a population-based case-control study of incident HF in 170 female residents of Olmsted County, Minnesota (59 cases and 111 controls), who underwent contemporary (1998–2013) radiotherapy for breast cancer with computed tomography–assisted radiotherapy planning. Controls were matched to cases for age, tumor side, chemotherapy use, diabetes mellitus, and hypertension. Mean cardiac radiation dose (MCRD) in each patient was calculated from the patient’s computed tomography images and radiotherapy plan. Results: Mean age at radiotherapy was 69±9 years. Of HF cases, 38 (64%) had EF≥50% (HFpEF), 18 (31%) had EF<50% (HF with reduced EF), and 3 (5%) did not have EF measured. The EF was ≥40% in 50 of the 56 HF cases (89%) with an EF measurement. The mean interval from radiotherapy to HF was 5.8±3.4 years. The odds of HF was higher in patients with a history of ischemic heart disease or atrial fibrillation. The MCRD was 2.5 Gy (range, 0.2–13.1 Gy) and higher in cases (3.3±2.7 Gy) than controls (2.1±2.0 Gy; P =0.004). The odds ratio (95% confidence interval) for HF per log MCRD was 9.1 (3.4–24.4) for any HF, 16.9 (3.9–73.7) for HFpEF, and 3.17 (0.8–13.0) for HF with reduced EF. The increased odds of any HF or HFpEF with increasing MCRD remained significant after adjustment for HF risk factors and in sensitivity analyses matching by cancer stage rather than tumor side. Only 18.6% of patients experienced new or recurrent ischemic events between radiotherapy and the onset of HF. Conclusions: The relative risk of HFpEF increases with increasing cardiac radiation exposure during contemporary conformal breast cancer radiotherapy. These data emphasize the importance of radiotherapy techniques that limit MCRD during breast cancer treatment. Moreover, these data provide further support for the importance of coronary microvascular compromise in the pathophysiology of HFpEF.

Abstract Aims Guided by predictive characteristics of cardiovascular biomarkers, we explored the clinical implications of a simulated biomarker-guided heart failure (HF) and major adverse cardiovascular events (MACE) prevention strategy in the community. Methods and results In a community cohort (n = 1824), the predictive characteristics for HF and MACE of galectin-3 (Gal-3), ST2, high-sensitivity cardiac troponin I (hscTnI), high-sensitivity C-reactive protein (hsCRP), N-terminal pro-brain natriuretic peptide (NT-proBNP) and B-type natriuretic peptide (BNP) were established. We performed number needed to screen (NNS) and treat (NNT) with the intervention analyses according to biomarker screening strategy and intervention efficacy in persons with at least one cardiovascular risk factor. In the entire cohort, for both HF and MACE, the predictive characteristics of NT-proBNP and hscTnI were superior to other biomarkers; alone, in a multimarker model, and adjusting for clinical risk factors. An NT-proBNP-guided preventative intervention with an intervention effect size (4-year hazard ratio for intervention in biomarker positive cohort) of ≤0.7 would reduce the global burden of HF by ≥20% and MACE by ≥15%. From this simulation, the NNS to prevent one HF event or MACE in 4 years would be ≤100 with a NNT to prevent one HF event of ≤20 and one MACE of ≤10. Conclusions The predictive characteristics of NT-proBNP and hscTnI for HF or MACE in the community are superior to other biomarkers. Biomarker-guided preventative interventions with reasonable efficacy would compare favourably to established preventative interventions. This data provides a framework for biomarker selection which may inform design of biomarker-guided preventative intervention trials.

Abstract Breast density represents the stromal and epithelial tissue in the breast and is a strong risk factor for breast cancer. Reductions in breast density attributable to tamoxifen (TAM) and aromatase inhibitors (AI) may be associated with reduced risk of first primary and subsequent breast cancer. Studies assessing breast density changes have principally used two-dimensional measures. We assess changes in breast density following initiation of TAM and AI using two automated volumetric density measures that have shown strong associations to breast cancer risk. Breast cancer cases with a full field digital mammogram (FFDM) prior to diagnosis (index mammogram) and after initiation of TAM (n = 379) or AI (n = 425) were identified from the Mayo Clinic Mammography Practice and the San Francisco Mammography Registry. Volumetric percent density (VPD) and dense volume (DV) were measured on 4-view FFDM using VolparaTM (Matakina Technology) and QuantraTM (Hologic) automated software. We used linear regression to assess the effect of treatment on mean annualized change in VPD and DV (change from index to last mammogram divided by time interval) for each software type, adjusting for age, body mass index (BMI) and density at index mammogram. The median time between index mammogram and cancer diagnosis was 0.6 months (IQR: 0.2, 2.2) and median time between index and last mammogram was 3 years (IQR: 2.0, 3.9). Women on TAM were younger, had lower BMI and higher baseline VPD and DV relative to women on AI (Table). An annual decrease in VPD and DV was observed with both TAM and AI. Both Volpara and Quantra estimated a similar magnitude of change in VPD in women on TAM and AI, and a greater change in DV with TAM. Our findings suggest that both Volpara and Quantra can assess volumetric changes in breast density among women on hormone therapy. If declines in volumetric density correlate with a reduction in breast cancer risk, these automated measures could be used in clinical practice to assess response to therapy. Annualized changes in volumetric breast density estimated by linear regression.Tamoxifen (n = 379)Aromatase Inhibitors (n = 425)Baseline Median (IQR)Annualized Change (95% CI)*Baseline Median (IQR)Annualized Change (95% CI)*Age at Diagnosis50.0 (45.0, 60.0)–63.0 (58.0, 71.0)–Body Mass Index (BMI)23.6 (21.5, 26.8)–25.7 (22.7, 29.9)–Time Interval¥3.0 (2.1, 3.9)–3.0 (2.1, 3.9)–VolparaPercent Density (VPD,%)11.6 (6.8, 18.8)-0.17 (-0.27, -0.10)7.2 (5.0, 11.0)-0.19 (-0.29, -0.12)Dense Volume (DV, cm3)64.7 (45.4, 90.9)-0.90 (-1.45, -0.48)51.9 (38.9, 69.9)-0.52 (-0.93, -0.23)QuantraPercent Density (VPD,%)14.5 (9.2, 20.2)-0.42 (-0.59, -0.28)9.9 (7.1, 14.5)-0.38 (-0.54, -0.25)Dense Volume (DV, cm3)94.0 (58.0, 144.0)-2.20 (-3.52, -1.19)80.0 (49.0, 128.0)-0.95 (-1.85, -0.35)IQR = Interquartile range ¥ Median number of years between index mammogram and last mammogram post-initiation of therapy. *Annualized change estimated as change from index to last mammogram divided by time interval and adjusted for study site, age at diagnosis, BMI and density at index mammogram. Citation Format: Natalie J. Engmann, Celine M. Vachon, Christopher G. Scott, Matthew R. Jensen, Lin Ma, Kathleen R. Brandt, Amir P. Mahmoudzadeh, Serghei Malkov, Dana H. Whaley, Carrie B. Hruska, Fang F. Wu, Stacey J. Winham, Diana L. Miglioretti, Aaron D. Norman, John J. Heine, John Shepherd, V Shane Pankratz, Karla Kerlikowske. Longitudinal changes in volumetric breast density with adjuvant endocrine therapy among women with breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3424.

Abstract Percent mammographic density (PMD) is a risk factor for estrogen receptor (ER)-positive and ER-negative invasive breast cancer (BC). Gene expression profiling has identified molecular signatures that classify invasive BC into distinct subtypes that vary in their clinical behavior, response to treatment and likely, etiology. Immunohistochemical (IHC) staining of tumor sections using antibody panels can be used to classify these ‘intrinsic’ molecular subtypes. We evaluated whether density measures [PMD, absolute dense area (DA) and non-dense area (NDA)], are associated equally with all ‘intrinsic’ molecular subtypes. Pooled analysis of six cohort or case-control studies included 3492 women with invasive BC and 10,148 without, who underwent screening mammography a median 4 years prior to diagnosis (for cases). PMD, DA, and NDA were assessed from digitized film-screen mammograms using a computer-assisted thresholding technique, and categorized as 0-10%, 11-25%, 26-50% and 51%+ (PMD) or into quartiles (DA and NDA). Receptor status was abstracted from pathology records and supplemented by IHC staining. We classified tumors as Luminal A (ER+ and/or PR+ and HER2- and grade 1 or 2), Luminal B (ER+ and/or PR+ and HER2+ or Luminal A and grade 3), HER2 expressing (HER2+/ER-/PR-) and triple negative (TN) (ER-/PR-/HER2-). For TN, we also differentiated basal-like tumors (positive for EGFR and/or CK 5/6) from unclassified (negative on both markers). We used polytomous logistic regression to calculate the odds ratio (OR) of each ‘intrinsic’ subtype of BC by categories of PMD, DA or NDA, adjusting for age, body mass index and study. We tested for statistical heterogeneity of associations by subtype. Of 3492 invasive BC cases, 2217 (63%) were classified as Luminal A, 747 (21%) as Luminal B, 159 (5%) as HER2 expressing, and 369 (11%) as TN. Of TN, 203 were evaluated for CK 5/6 and EGFR, with 167 (82%) classified as basal-like and 36 (18%) unclassified. PMD was associated with BC risk across all subtypes. For Luminal A, compared to women with 11-25% PMD (reference), women with 0-10% had a reduced risk of BC (OR = 0.63 [95% confidence interval: 0.55, 0.74]) while women with 26-50% had an OR = 1.5 [1.3, 1.7] and women with 51%+ had the highest risk, OR = 2.3 [2.0, 2.7]. Similar BC associations were seen across PMD categories when comparing the five subtypes (P-heterogeneity = 0.63). Similar trends were seen for DA and BC across the five subtypes (P-het = 0.25). NDA was inversely associated with BC across subtypes, and there was suggestion of a stronger inverse trend among HER2-expressing BC compared to other subtypes (P-het = 0.09). Our results suggest mammographic density measures are associated with all ‘intrinsic’ molecular subtypes. However, NDA may be more strongly inversely associated with HER2-expressing than other subtypes. Understanding the importance of density measures for BC subtypes has significance for subtype-specific risk models. Citation Format: Aaron D. Norman, Rulla M. Tamimi, Christopher G. Scott, Kimberly A. Bertrand, Matthew R. Jensen, Daniel W. Visscher, Fergus J. Couch, John Shepherd, Bo Fan, Yunn-Yi Chen, Lin Ma, Andrew Beck, Vernon S. Pankratz, Karla Kerlikowske, Celine M. Vachon. Association of mammographic density measures and breast cancer ‘intrinsic’ molecular subtypes. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2593.

Abstract Gene expression profiling has identified molecular subtypes that classify invasive breast cancers into distinct categories that vary in their clinical behavior and response to treatment. These subtypes highlight the many possible biologically and clinically distinct types of breast cancer. Immunohistochemical (IHC) staining of tumor sections using antibody panels has been used as a surrogate for the molecular subtypes identified through gene expression profiling, resulting in a set of intrinsic molecular subtypes. Given the heterogeneity within breast cancer, one might expect that different risk factors influence specific subtypes of breast cancer through various etiologic pathways. We evaluated whether percent mammographic density (MD), the proportion of fibroglandular or white tissue on a mammogram and one of the strongest and most consistent risk factors for breast cancer, is associated equally with all intrinsic molecular subtypes. Data were pooled from six cohort or case-control studies including 3389 women with invasive breast cancer and 9860 without, who underwent screening mammography. Percent MD was assessed from digitized film-screen mammograms (for cases, at a median 4 years prior to diagnosis) using a computer-assisted threshold technique, and categorized as 0-10%, 11-25%, 26-50% and 51%+. Receptor status was abstracted from clinical pathology records and supplemented by IHC staining of tumor sections or microarrays. With estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (HER2) information, we classified tumors into the intrinsic molecular subtypes: Luminal A ( ER+ and/or PR+ and HER2- and grade 1 or 2), Luminal B (ER+ and/or PR+ and HER2+ or Luminal A and grade 3), HER2 expressing (HER2+/ER-/PR-) and triple negative (ER-/PR-/HER2-). For cancers found to be triple negative (TN), we also stained for epidermal growth factor receptor (EGFR) and cytokeratins (CK) 5/6 to differentiate basal-like tumors (positive for EGFR and/or CK 5/6) from the unclassifieds (negative on both EGFR and CK 5/6). We used polytomous logistic regression to calculate the odds (OR) of each of the intrinsic subtypes of breast cancer by categories of percent MD, adjusting for age, BMI and study. Contrasts were constructed and tested within the polytomous model framework to investigate differences in the strength of association of percent MD across subtypes. On average, cases were slightly older (56.4 years [SD=11.3]) than controls (55.8 [10.9]). Of the 3389 invasive breast cancer cases, 2146 (63%) were classified as Luminal A, 709 (21%) as Luminal B, 169 (5%) as HER-2 expressing, and 365(11%) as triple negative (TN). Of the TN tumors, 203 had tumor tissue available and were evaluated for CK 5/6 and EGFR, with 167 (82%) classified as basal-like and 36 (18%) as unclassified. Percent (%) MD was associated with breast cancer risk across all intrinsic subtypes. For Luminal A, compared to women with 11-25% MD (reference), women with 0-10% MD had a reduced risk of breast cancer (OR=0.64 [95% confidence interval (CI): 0.55, 0.74]) while women with 26-50% MD had an OR=1.5 (1.3,1.7) and women with 51%+ MD had the highest risk, OR=2.4 (2.0, 2.8). Similar associations were seen for Luminal B, HER2 expressing, and TN across percent MD categories. The small differences among the percent MD-breast cancer associations observed for the different subtypes were not statistically significant, either when comparing the four (Luminal A, Luminal B, HER-2 expressing and TN; p=0.61) or five categories of subtypes (Luminal A, Luminal B, HER-2 expressing, basal-like, unclassified; p=0.66). Our results suggest percent MD is a risk factor for all intrinsic molecular subtypes. Additional study is needed to examine whether these results hold for younger and older aged women. Understanding the importance of mammographic density measures for subtypes of breast cancer has significance for development of subtype-specific risk models. Citation Format: Celine Vachon, Rulla Tamimi, Yunn-Yi Chen, Christopher Scott, Kimberly Bertrand, Matthew Jensen, Daniel Visscher, Aaron Norman, Fergus Couch, John Shepherd, Bo Fan, Fang-Fang Wu, Lin Ma, Andrew Beck, Steve Cummings, V. Shane Pankratz, Karla Kerlikowske. Mammographic density: A risk factor for all breast cancers or only specific subtypes? [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr IA22.