Racial and ethnic disparities plague the US health care system despite efforts to eliminate them. To understand what has been achieved amid these efforts, a comprehensive study from the population perspective is needed. To determine trends in rates and racial/ethnic disparities of key access to care measures among adults in the US in the last two decades. Cross-sectional. Data from the National Health Interview Survey, 1999-2018. Individuals >18 years old. Race and ethnicity non-Hispanic Black, non-Hispanic Asian, non-Hispanic White, Hispanic. Rates of lack of insurance coverage, lack of a usual source of care, and foregone/delayed medical care due to cost. We also estimated the gap between non-Hispanic White and the other subgroups for these outcomes. We included 596,355 adults, of which 69.7% identified as White, 11.8% as Black, 4.7% as Asian, and 13.8% as Hispanic. The proportion uninsured and the rates of lacking a usual source of care remained stable across all 4 race/ethnicity subgroum 1999-2018, we found that insurance coverage increased across all 4 major race/ethnicity groups. However, rates of unmet medical needs due to cost increased without reducing the respective racial/ethnic disparities, and little-to-no change occurred in rates of individuals who have no usual source of care.Meaning Despite increased coverage, millions of Americans continued to experience barriers to access to care, which were disproportionately more prevalent among those identifying as Black or Hispanic. Quantifying occupational risk factors for SARS-CoV-2 infection among healthcare workers can inform efforts to improve healthcare worker and patient safety and reduce transmission. This study aimed to quantify demographic, occupational, and community risk factors for SARS-CoV-2 seropositivity among healthcare workers in a large metropolitan healthcare system. We analyzed data from a cross-sectional survey conducted from April through June of 2020 linking risk factors for occupational and community exposure to COVID-19 with SARS-CoV-2 seropositivity. A multivariable logistic regression model was fit to quantify risk factors for infection. Participants were employees and medical staff members who elected to participate in SARS-CoV-2 serology testing offered to all healthcare workers as part of a quality initiative, and who completed a survey on exposure to COVID-19 and use of personal protective equipment. Exposures of interest included known demographic risk factors for COVID-19, residential zip code incidet with a COVID-19 positive individual and residential COVID-19 incidence, are more strongly associated with SARS-CoV-2 seropositivity among healthcare workers than exposure in the workplace.Anti-Müllerian hormone (AMH) is expressed by antral stage ovarian follicles in women. Consequently, circulating AMH levels are detectable until menopause. Variation in age-specific AMH levels has been associated with breast cancer and polycystic ovary syndrome (PCOS), amongst other diseases. Identification of genetic variants underlying variation in AMH levels could provide clues about the physiological mechanisms that explain these AMH-disease associations. To date, only one variant in MCM8 has been identified to be associated with circulating AMH levels in women. We aimed to identify additional variants for AMH through a GWAS meta-analysis including data from 7049 premenopausal women of European ancestry, which more than doubles the sample size of the largest previous GWAS. We identified four loci associated with AMH levels at p less then 5×10 -8 the previously reported MCM8 locus and three novel signals in or near AMH, TEX41 , and CDCA7 . The strongest signal was a missense variant in the AMH gene (rs10417628). Gossypol Most prioritized genes at the other three identified loci were involved in cell cycle regulation. Genetic correlation analyses indicated a strong positive correlation among SNPs for AMH levels and for age at menopause (r g = 0.82, FDR=0.003). Exploratory Mendelian randomization analyses did not support a causal effect of AMH on breast cancer or PCOS risk, but should be interpreted with caution as they may be underpowered and the validity of genetic instruments could not be extensively explored. In conclusion, we identified a variant in the AMH gene and three other loci that may affect circulating AMH levels in women. Radiomic feature analysis has been shown to be effective at modeling cancer outcomes. It has not yet been established how to best combine these radiomic features in patients with multifocal disease. As the number of patients with multifocal metastatic cancer continues to rise, there is a need for improving personalized patient-level prognostication to better inform treatment. We compared six mathematical methods of combining radiomic features of 3596 tumors in 831 patients with multiple brain metastases and evaluated the performance of these aggregation methods using three survival models a standard Cox proportional hazards model, a Cox proportional hazards model with LASSO regression, and a random survival forest. Across all three survival models, the weighted average of the largest three metastases had the highest concordance index (95% confidence interval) of 0.627 (0.595-0.661) for the Cox proportional hazards model, 0.628 (0.591-0.666) for the Cox proportional hazards model with LASSO regression, and 0.652 (0.565-0.727) for the random survival forest model. Radiomic features can be effectively combined to establish patient-level outcomes in patients with multifocal brain metastases. Future studies are needed to confirm that the volume-weighted average of the largest three tumors is an effective method for combining radiomic features across other imaging modalities and disease sites.Radiomic features can be effectively combined to establish patient-level outcomes in patients with multifocal brain metastases. Future studies are needed to confirm that the volume-weighted average of the largest three tumors is an effective method for combining radiomic features across other imaging modalities and disease sites.