Polley, Eric C.

PURPOSE This study assessed the joint association of pathogenic variants (PVs) in breast cancer (BC) predisposition genes and polygenic risk scores (PRS) with BC in the general population. METHODS A total of 26,798 non-Hispanic white BC cases and 26,127 controls from predominately population-based studies in the Cancer Risk Estimates Related to Susceptibility consortium were evaluated for PVs in BRCA1, BRCA2, ATM, CHEK2, PALB2, BARD1, BRIP1, CDH1, and NF1. PRS based on 105 common variants were created using effect estimates from BC genome-wide association studies; the performance of an overall BC PRS and estrogen receptor–specific PRS were evaluated. The odds of BC based on the PVs and PRS were estimated using penalized logistic regression. The results were combined with age-specific incidence rates to estimate 5-year and lifetime absolute risks of BC across percentiles of PRS by PV status and first-degree family history of BC. RESULTS The estimated lifetime risks of BC among general-population noncarriers, based on 10th and 90th percentiles of PRS, were 9.1%-23.9% and 6.7%-18.2% for women with or without first-degree relatives with BC, respectively. Taking PRS into account, more than 95% of BRCA1, BRCA2, and PALB2 carriers had > 20% lifetime risks of BC, whereas, respectively, 52.5% and 69.7% of ATM and CHEK2 carriers without first-degree relatives with BC, and 78.8% and 89.9% of those with a first-degree relative with BC had > 20% risk. CONCLUSION PRS facilitates personalization of BC risk among carriers of PVs in predisposition genes. Incorporating PRS into BC risk estimation may help identify > 30% of CHEK2 and nearly half of ATM carriers below the 20% lifetime risk threshold, suggesting the addition of PRS may prevent overscreening and enable more personalized risk management approaches.

10581 Background: The prevalence of germline pathogenic variants (PVs) in cancer predisposition genes among women with invasive lobular breast cancer (ILC) and the risk of ILC in PV carriers is not well-defined. Methods: The study included 2,999 women with ILC and 32,544 unaffected controls from a population-based cohort; 3,796 women with ILC and 20,323 women with invasive ductal carcinoma (IDC) undergoing clinical multigene panel testing (clinical cohort); and 125,748 exome sequences from unrelated women without a cancer diagnosis in the gnomAD 3.0 dataset. Frequencies of germline PVs in breast cancer predisposition genes ( ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, PALB2, PTEN, RAD51C, RAD51D, and TP53) were compared between women with ILC and unaffected controls in both cohorts and between women with ILC and IDC in the clinical cohort. Results: The frequency of PVs in breast cancer predisposition genes among women with ILC was 6.5% in the clinical cohort and 5.2% in the population-based cohort. In case-control analyses, CDH1 and BRCA2 PVs were associated with high risks of ILC (Odds ratio (OR) > 4), and CHEK2, ATM and PALB2 PVs were associated with moderate (OR = 2-4) risks. BRCA1 PVs and CHEK2 p.Ile157Thr were not associated with clinically relevant risks (OR < 2) of ILC. PV frequencies in these genes in ILC and IDC were similar except for PV frequencies in BRCA1 and CDH1. Conclusions: The study establishes that PVs in ATM, BRCA2, CDH1, CHEK2 and PALB2 are associated with an increased risk of ILC, whereas BRCA1 PVs are not. The similar overall PV frequencies for ILC and IDC suggest that cancer histology should not influence the decision to proceed with genetic testing. While, multigene panel testing may be appropriate for women with ILC, CDH1 should be specifically discussed in the context of low prevalence and attendant gastric cancer risk.

10500 Background: Inherited pathogenic variants in ATM, CHEK2, and PALB2 confer moderate to high risks of breast cancer. The optimal approach to screening in these women has not been established. Methods: We used two simulation models from the Cancer Intervention and Surveillance Modeling Network (CISNET) and data from the Cancer Risk Estimates Related to Susceptibility consortium (CARRIERS) to project lifetime breast cancer incidence and mortality in ATM, CHEK2, and PALB2 carriers. We simulated screening with annual mammography from ages 40-74 alone and with annual magnetic resonance imaging (MRI) starting at ages 40, 35, 30, and 25. Joint and separate mammography and MRI screening performance was based on published literature. Lifetime outcomes per 1,000 women were reported as means and ranges across both models. Results: Estimated risk of breast cancer by age 80 was 22% (21-23%) for ATM, 28% (26-30%) for CHEK2, and 40% (38-42%) for PALB2. Screening with MRI and mammography reduced breast cancer mortality by 52-60% across variants (Table). Compared to no screening, starting MRI at age 30 increased life years (LY)/1000 women by 501 (478-523) in ATM, 620 (587-652) in CHEK2, and 1,025 (998-1,051) in PALB2. Starting MRI at age 25 versus 30 gained 9-12 LY/1000 women with 517-518 additional false positive screens and 197-198 benign biopsies. Conclusions: For women with ATM, CHEK2, and PALB2 pathogenic variants, breast cancer screening with MRI and mammography halves breast cancer mortality. These mortality benefits are similar to those for MRI screening for BRCA1/2 mutation carriers and should inform practice guidelines.[Table: see text]

Key points Healthy older adults exhibit lower cardiorespiratory fitness () than young in the absence of any age‐related difference in skeletal muscle mitochondrial capacity, suggesting central haemodynamics plays a larger role in age‐related declines in . Total physical activity did not differ by age, but moderate‐to‐vigorous physical activity was lower in older compared to young adults. Moderate‐to‐vigorous physical activity is associated with and muscle oxidative capacity, but physical inactivity cannot entirely explain the age‐related reduction in . AbstractDeclining fitness () is a hallmark of ageing and believed to arise from decreased oxygen delivery and reduced muscle oxidative capacity. Physical activity is a modifiable lifestyle factor that is critical when evaluating the effects of age on parameters of fitness and energy metabolism. The objective was to evaluate the effects of age and sex on , muscle mitochondrial physiology, and physical activity in young and older adults. An additional objective was to assess the contribution of skeletal muscle oxidative capacity to age‐related reductions in and determine if age‐related variation in and muscle oxidative capacity could be explained on the basis of physical activity levels. In 23 young and 52 older men and women measurements were made of , mitochondrial physiology in permeabilized muscle fibres, and free‐living physical activity by accelerometry. Regression analyses were used to evaluate associations between age and , mitochondrial function, and physical activity. Significant age‐related reductions were observed for (P < 0.001), but not muscle mitochondrial capacity. Total daily step counts did not decrease with age, but older adults showed lower moderate‐to‐vigorous physical activity, which was associated with (R2 = 0.323, P < 0.001) and muscle oxidative capacity (R2 = 0.086, P = 0.011). After adjusting for sex and physical activity, age was negatively associated with but not muscle oxidative capacity. Healthy older adults exhibit lower but preserved mitochondrial capacity compared to young. Physical activity, particularly moderate‐to‐vigorous, is a key factor in observed age‐related changes in fitness and muscle oxidative capacity, but cannot entirely explain the age‐related reduction in .

Adipose inflammation is proposed to be at the nexus of the systemic inflammation and metabolic derangements associated with obesity. The present study provides evidence to support adipose inflammation as a central feature of the pathophysiology of obesity. Adipose inflammation is associated with systemic and peripheral metabolic derangements, including increased systemic inflammation, reduced insulin sensitivity and reduced skeletal muscle mitochondrial respiration.

Hospital medicine ward rounds are often conducted away from patients’ bedsides, but it is unknown if more time-at-bedside is associated with improved patient outcomes. Our objective is to measure the association between “time-at-bedside,” patient experience, and patient–clinician care agreement during ward rounds. Research assistants directly observed medicine services to quantify the amount of time spent discussing each patient’s care inside versus outside the patient’s room. “Time-at-bedside” was defined as the proportion of time spent discussing a patient’s care in his or her room. Patient experience and patient–clinician care agreement both were measured immediately after ward rounds. Results demonstrated that the majority of patient and physicians completely agreement on planned tests (66.3%), planned procedures (79.7%), medication changes (50.6%), and discharge location (66.9%), but had no agreement on the patient’s main concern (74.4%) and discharge date (50.6%). Time-at-bedside was not correlated with care agreement or patient experience ( P > .05 for all comparisons). This study demonstrates that spending more time at the bedside during ward rounds, alone, is insufficient to improve patient experience.

PURPOSE Among patients with metastatic breast cancer (mBC), the frequency of germline mutations in cancer susceptibility genes and the clinical relevance of these mutations are unclear. In this study, a prospective cohort of patients with mBC was used to determine mutation rates for breast cancer (BC) predisposition genes, to evaluate the clinical characteristics of patients with mutations, and to assess the influence of mutations on patient outcome. PATIENTS AND METHODS Germline DNA from 2,595 patients with mBC enrolled in the prospective PRAEGNANT registry was evaluated for mutations in cancer predisposition genes. The frequencies of mutations in known BC predisposition genes were compared with results from a prospective registry of patients with nonmetastatic BC sequenced using the same QIAseq method and with public reference controls. Associations between mutation status and tumor characteristics, progression-free survival, and overall survival were assessed. RESULTS Germline mutations in 12 established BC predisposition genes (including BRCA1 and BRCA2) were detected in 271 (10.4%) patients. A mutation in BRCA1 or BRCA2 was seen in 129 patients (5.0%). BRCA1 mutation carriers had a higher proportion of brain metastasis (27.1%) compared with nonmutation carriers (12.8%). Mutations were significantly enriched in PRAEGNANT patients with mBC compared with patients with nonmetastatic BC (10.4% v 6.6%, P < .01). Mutations did not significantly modify progression-free survival or overall survival for patients with mBC. CONCLUSION Multigene panel testing may be considered in all patients with mBC because of the high frequency of germline mutations in BRCA1/2 and other BC predisposition genes. Although the prognosis of mutation carriers and nonmutation carriers with mBC was similar, differences observed in tumor characteristics have implications for treatment and for future studies of targeted therapies.

PurposeTo develop a two‐stage three‐dimensional (3D) convolutional neural networks (CNNs) for fully automated volumetric segmentation of pancreas on computed tomography (CT) and to further evaluate its performance in the context of intra‐reader and inter‐reader reliability at full dose and reduced radiation dose CTs on a public dataset.MethodsA dataset of 1994 abdomen CT scans (portal venous phase, slice thickness ≤ 3.75‐mm, multiple CT vendors) was curated by two radiologists (R1 and R2) to exclude cases with pancreatic pathology, suboptimal image quality, and image artifacts (n = 77). Remaining 1917 CTs were equally allocated between R1 and R2 for volumetric pancreas segmentation [ground truth (GT)]. This internal dataset was randomly divided into training (n = 1380), validation (n = 248), and test (n = 289) sets for the development of a two‐stage 3D CNN model based on a modified U‐net architecture for automated volumetric pancreas segmentation. Model’s performance for pancreas segmentation and the differences in model‐predicted pancreatic volumes vs GT volumes were compared on the test set. Subsequently, an external dataset from The Cancer Imaging Archive (TCIA) that had CT scans acquired at standard radiation dose and same scans reconstructed at a simulated 25% radiation dose was curated (n = 41). Volumetric pancreas segmentation was done on this TCIA dataset by R1 and R2 independently on the full dose and then at the reduced radiation dose CT images. Intra‐reader and inter‐reader reliability, model’s segmentation performance, and reliability between model‐predicted pancreatic volumes at full vs reduced dose were measured. Finally, model’s performance was tested on the benchmarking National Institute of Health (NIH)‐Pancreas CT (PCT) dataset.ResultsThree‐dimensional CNN had mean (SD) Dice similarity coefficient (DSC): 0.91 (0.03) and average Hausdorff distance of 0.15 (0.09) mm on the test set. Model’s performance was equivalent between males and females (P = 0.08) and across different CT slice thicknesses (P > 0.05) based on noninferiority statistical testing. There was no difference in model‐predicted and GT pancreatic volumes [mean predicted volume 99 cc (31cc); GT volume 101 cc (33 cc), P = 0.33]. Mean pancreatic volume difference was −2.7 cc (percent difference: −2.4% of GT volume) with excellent correlation between model‐predicted and GT volumes [concordance correlation coefficient (CCC)=0.97]. In the external TCIA dataset, the model had higher reliability than R1 and R2 on full vs reduced dose CT scans [model mean (SD) DSC: 0.96 (0.02), CCC = 0.995 vs R1 DSC: 0.83 (0.07), CCC = 0.89, and R2 DSC:0.87 (0.04), CCC = 0.97]. The DSC and volume concordance correlations for R1 vs R2 (inter‐reader reliability) were 0.85 (0.07), CCC = 0.90 at full dose and 0.83 (0.07), CCC = 0.96 at reduced dose datasets. There was good reliability between model and R1 at both full and reduced dose CT [full dose: DSC: 0.81 (0.07), CCC = 0.83 and reduced dose DSC:0.81 (0.08), CCC = 0.87]. Likewise, there was good reliability between model and R2 at both full and reduced dose CT [full dose: DSC: 0.84 (0.05), CCC = 0.89 and reduced dose DSC:0.83(0.06), CCC = 0.89]. There was no difference in model‐predicted and GT pancreatic volume in TCIA dataset (mean predicted volume 96 cc (33); GT pancreatic volume 89 cc (30), p = 0.31). Model had mean (SD) DSC: 0.89 (0.04) (minimum–maximum DSC: 0.79 −0.96) on the NIH‐PCT dataset.ConclusionA 3D CNN developed on the largest dataset of CTs is accurate for fully automated volumetric pancreas segmentation and is generalizable across a wide range of CT slice thicknesses, radiation dose, and patient gender. This 3D CNN offers a scalable tool to leverage biomarkers from pancreas morphometrics and radiomics for pancreatic diseases including for early pancreatic cancer detection.