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BACKGROUND: Rural U.S. communities are at risk from COVID-19 due to advanced age and limited access to acute care. Recognizing this, the Vashon Medical Reserve Corps (VMRC) in King County, Washington, implemented an all-volunteer, community-based COVID-19 response program. This program integrated public engagement, SARS-CoV-2 testing, contact tracing, vaccination, and material community support, and was associated with the lowest cumulative COVID-19 case rate in King County. This study aimed to investigate the contributions of demographics, geography and public health interventions to Vashons low COVID-19 rates. METHODS: This observational cross-sectional study compares cumulative COVID-19 rates and success of public health interventions from February 2020 through November 2021 for Vashon Island with King County (including metropolitan Seattle) and Whidbey Island, located ~50 km north of Vashon. To evaluate the role of demography, we developed multiple linear regression models of COVID-19 rates using metrics of age, race/ethnicity, wealth and educational attainment across 77 King County zip codes. To investigate the role of remote geography we expanded the regression models to include North, Central and South Whidbey, similarly remote island communities with varying demographic features. To evaluate the effectiveness of VMRCs community-based public health measures, we directly compared Vashons success of vaccination and contact tracing with that of King County and South Whidbey, the Whidbey community most similar to Vashon. RESULTS: Vashons cumulative COVID-19 case rate was 29% that of King County overall (22.2 vs 76.8 cases/K). A multiple linear regression model based on King County demographics found educational attainment to be a major correlate of COVID-19 rates, and Vashons cumulative case rate was just 38% of predicted (p < .05), so demographics alone do not explain Vashons low COVID-19 case rate. Inclusion of Whidbey communities in the model identified a major effect of remote geography (-49 cases/K, p < .001), such that observed COVID-19 rates for all remote communities fell within the models 95% prediction interval. VMRCs vaccination effort was highly effective, reaching a vaccination rate of 1500 doses/K four months before South Whidbey and King County and maintaining a cumulative vaccination rate 200 doses/K higher throughout the latter half of 2021 (p < .001). Including vaccination rates in the model reduced the effect of remote geography to -41 cases/K (p < .001). VMRC case investigation was also highly effective, interviewing 96% of referred cases in an average of 1.7 days compared with 69% in 3.7 days for Washington Department of Health investigating South Whidbey cases and 80% in 3.4 days for Public Health-Seattle & King County (both p

IntroductionOver the past two decades, percutaneous coronary intervention (PCI) capacity has increased while coronary artery disease has decreased, potentially lowering per-hospital PCI volumes, which is associated with less favorable patient outcomes. Trends in the likelihood of receiving PCI in a low-volume center have not been well-documented, and it is unknown whether certain socioeconomic factors are associated with a greater risk of PCI in a low-volume facility. Our study aims to determine the likelihood of being treated in a low-volume PCI center over time and if this likelihood differs by sociodemographic factors.MethodsWe conducted a retrospective cohort study of 374,066 hospitalized patients in California receiving PCI from January 1, 2010, to December 31, 2018. Our primary outcome was the likelihood of PCI discharges at a low-volume hospital (

Artificial Intelligence (AI) has the power to improve our lives through a wide variety of applications, many of which fall into the healthcare space; however, a lack of diversity is contributing to limitations in how broadly AI can help people. The UCSF AI4ALL program was established in 2019 to address this issue by targeting high school students from underrepresented backgrounds in AI, giving them a chance to learn about AI with a focus on biomedicine, and promoting diversity and inclusion. In 2020, the UCSF AI4ALL three-week program was held entirely online due to the COVID-19 pandemic. Thus, students participated virtually to gain experience with AI, interact with diverse role models in AI, and learn about advancing health through AI. Specifically, they attended lectures in coding and AI, received an in-depth research experience through hands-on projects exploring COVID-19, and engaged in mentoring and personal development sessions with faculty, researchers, industry professionals, and undergraduate and graduate students, many of whom were women and from underrepresented racial and ethnic backgrounds. At the conclusion of the program, the students presented the results of their research projects at the final symposium. Comparison of pre- and post-program survey responses from students demonstrated that after the program, significantly more students were familiar with how to work with data and to evaluate and apply machine learning algorithms. There were also nominally significant increases in the students' knowing people in AI from historically underrepresented groups, feeling confident in discussing AI, and being aware of careers in AI. We found that we were able to engage young students in AI via our online training program and nurture greater diversity in AI. This work can guide AI training programs aspiring to engage and educate students entirely online, and motivate people in AI to strive towards increasing diversity and inclusion in this field.

BackgroundDischarge delays for non-medical reasons put patients at unnecessary risk for hospital-acquired infections, lead to loss of revenue for hospitals and reduce hospital capacity to treat other patients. The objective of this study was to determine prevalence of, and patient characteristics associated with, delays in discharge at an urban county trauma service.MethodsWe performed a retrospective cohort study with data from Zuckerberg San Francisco General Hospital (ZSFGH), a level-1 trauma center and safety net hospital in San Francisco, California. The study included 1720 patients from the trauma surgery service at ZSFGH. A 'delay in discharge' was defined as days in the hospital, including an initial overnight stay, after all medical needs had been met. We used logistic and zero-inflated negative binomial regression models to test whether the following factors were associated with prolonged, non-medical length of stay: age, gender, race/ethnicity, housing, disposition location, type of insurance, having a primary care provider, primary language and zip code.ResultsOf the 1720 patients, 15% experienced a delay in discharge, for a total of 1147 days (median 1.5 days/patient). The following were statistically significant (p

BackgroundDischarge delays for non-medical reasons put patients at unnecessary risk for hospital-acquired infections, lead to loss of revenue for hospitals and reduce hospital capacity to treat other patients. The objective of this study was to determine prevalence of, and patient characteristics associated with, delays in discharge at an urban county trauma service.MethodsWe performed a retrospective cohort study with data from Zuckerberg San Francisco General Hospital (ZSFGH), a level-1 trauma center and safety net hospital in San Francisco, California. The study included 1720 patients from the trauma surgery service at ZSFGH. A 'delay in discharge' was defined as days in the hospital, including an initial overnight stay, after all medical needs had been met. We used logistic and zero-inflated negative binomial regression models to test whether the following factors were associated with prolonged, non-medical length of stay: age, gender, race/ethnicity, housing, disposition location, type of insurance, having a primary care provider, primary language and zip code.ResultsOf the 1720 patients, 15% experienced a delay in discharge, for a total of 1147 days (median 1.5 days/patient). The following were statistically significant (p

BACKGROUND: Socioeconomic status (SES) is associated with diagnostic and treatment delays and survival in multiple cancers, but less data exist for anal squamous cell carcinoma (ASCC). This study investigated the association between SES and outcomes for patients undergoing definitive chemoradiation therapy for ASCC. METHODS: One hundred and eleven patients diagnosed with nonmetastatic ASCC between 2005 and 2018 were retrospectively reviewed. Socioeconomic predictor variables included primary payer, race, income, employment, and partnership status. Outcomes included the tumor-node (TN) stage at diagnosis, the duration from diagnosis to treatment initiation, relapse-free survival (RFS), and overall survival (OS). Age, gender, TN stage, and HIV status were analyzed as covariates in survival analysis. RESULTS: SES was not associated with the TN stage at diagnosis. SES factors associated with treatment initiation delays were Medicaid payer (P = .016) and single partnership status (P = .016). Compared to privately insured patients, Medicaid patients had lower 2-year RFS (64.4% vs 93.8%, P = .021) and OS (82.9% vs 93.5%, P = .038). Similarly, relative to patients in the racial majority, racial minority patients had lower 2-year RFS (53.3% vs 93.5%, P = .001) and OS (73.7% vs 92.6%, P = .008). Race was an independent predictor for both RFS (P = .027) and OS (P = .047). CONCLUSIONS: These results highlight the impact of social contextual factors on health. Interventions targeted at socioeconomically vulnerable populations are needed to reduce disparities in ASCC outcomes.

BackgroundWhile programmed death 1 (PD-1) and programmed death-ligand 1 (PD-L1) checkpoint inhibitors have activity in a proportion of patients with advanced bladder cancer, strongly predictive and prognostic biomarkers are still lacking. In this study, we evaluated PD-L1 protein expression on circulating tumor cells (CTCs) isolated from patients with muscle invasive (MIBC) and metastatic (mBCa) bladder cancer and explore the prognostic value of CTC PD-L1 expression on clinical outcomes.MethodsBlood samples from 25 patients with MIBC or mBCa were collected at UCSF and shipped to Epic Sciences. All nucleated cells were subjected to immunofluorescent (IF) staining and CTC identification by fluorescent scanners using algorithmic analysis. Cytokeratin expressing (CK)+ and (CK)-CTCs (CD45-, intact nuclei, morphologically distinct from WBCs) were enumerated. A subset of patient samples underwent genetic characterization by fluorescence in situ hybridization (FISH) and copy number variation (CNV) analysis.ResultsCTCs were detected in 20/25 (80 %) patients, inclusive of CK+ CTCs (13/25, 52 %), CK-CTCs (14/25, 56 %), CK+ CTC Clusters (6/25, 24 %), and apoptotic CTCs (13/25, 52 %). Seven of 25 (28 %) patients had PD-L1+ CTCs; 4 of these patients had exclusively CK-/CD45-/PD-L1+ CTCs. A subset of CTCs were secondarily confirmed as bladder cancer via FISH and CNV analysis, which revealed marked genomic instability. Although this study was not powered to evaluate survival, exploratory analyses demonstrated that patients with high PD-L1+/CD45-CTC burden and low burden of apoptotic CTCs had worse overall survival.ConclusionsCTCs are detectable in both MIBC and mBCa patients. PD-L1 expression is demonstrated in both CK+ and CK-CTCs in patients with mBCa, and genomic analysis of these cells supports their tumor origin. Here we demonstrate the ability to identify CTCs in patients with advanced bladder cancer through a minimally invasive process. This may have the potential to guide checkpoint inhibitor immune therapies that have been established to have activity, often with durable responses, in a proportion of these patients.

BackgroundWhile programmed death 1 (PD-1) and programmed death-ligand 1 (PD-L1) checkpoint inhibitors have activity in a proportion of patients with advanced bladder cancer, strongly predictive and prognostic biomarkers are still lacking. In this study, we evaluated PD-L1 protein expression on circulating tumor cells (CTCs) isolated from patients with muscle invasive (MIBC) and metastatic (mBCa) bladder cancer and explore the prognostic value of CTC PD-L1 expression on clinical outcomes.MethodsBlood samples from 25 patients with MIBC or mBCa were collected at UCSF and shipped to Epic Sciences. All nucleated cells were subjected to immunofluorescent (IF) staining and CTC identification by fluorescent scanners using algorithmic analysis. Cytokeratin expressing (CK)+ and (CK)-CTCs (CD45-, intact nuclei, morphologically distinct from WBCs) were enumerated. A subset of patient samples underwent genetic characterization by fluorescence in situ hybridization (FISH) and copy number variation (CNV) analysis.ResultsCTCs were detected in 20/25 (80 %) patients, inclusive of CK+ CTCs (13/25, 52 %), CK-CTCs (14/25, 56 %), CK+ CTC Clusters (6/25, 24 %), and apoptotic CTCs (13/25, 52 %). Seven of 25 (28 %) patients had PD-L1+ CTCs; 4 of these patients had exclusively CK-/CD45-/PD-L1+ CTCs. A subset of CTCs were secondarily confirmed as bladder cancer via FISH and CNV analysis, which revealed marked genomic instability. Although this study was not powered to evaluate survival, exploratory analyses demonstrated that patients with high PD-L1+/CD45-CTC burden and low burden of apoptotic CTCs had worse overall survival.ConclusionsCTCs are detectable in both MIBC and mBCa patients. PD-L1 expression is demonstrated in both CK+ and CK-CTCs in patients with mBCa, and genomic analysis of these cells supports their tumor origin. Here we demonstrate the ability to identify CTCs in patients with advanced bladder cancer through a minimally invasive process. This may have the potential to guide checkpoint inhibitor immune therapies that have been established to have activity, often with durable responses, in a proportion of these patients.

BackgroundWhile programmed death 1 (PD-1) and programmed death-ligand 1 (PD-L1) checkpoint inhibitors have activity in a proportion of patients with advanced bladder cancer, strongly predictive and prognostic biomarkers are still lacking. In this study, we evaluated PD-L1 protein expression on circulating tumor cells (CTCs) isolated from patients with muscle invasive (MIBC) and metastatic (mBCa) bladder cancer and explore the prognostic value of CTC PD-L1 expression on clinical outcomes.MethodsBlood samples from 25 patients with MIBC or mBCa were collected at UCSF and shipped to Epic Sciences. All nucleated cells were subjected to immunofluorescent (IF) staining and CTC identification by fluorescent scanners using algorithmic analysis. Cytokeratin expressing (CK)+ and (CK)-CTCs (CD45-, intact nuclei, morphologically distinct from WBCs) were enumerated. A subset of patient samples underwent genetic characterization by fluorescence in situ hybridization (FISH) and copy number variation (CNV) analysis.ResultsCTCs were detected in 20/25 (80 %) patients, inclusive of CK+ CTCs (13/25, 52 %), CK-CTCs (14/25, 56 %), CK+ CTC Clusters (6/25, 24 %), and apoptotic CTCs (13/25, 52 %). Seven of 25 (28 %) patients had PD-L1+ CTCs; 4 of these patients had exclusively CK-/CD45-/PD-L1+ CTCs. A subset of CTCs were secondarily confirmed as bladder cancer via FISH and CNV analysis, which revealed marked genomic instability. Although this study was not powered to evaluate survival, exploratory analyses demonstrated that patients with high PD-L1+/CD45-CTC burden and low burden of apoptotic CTCs had worse overall survival.ConclusionsCTCs are detectable in both MIBC and mBCa patients. PD-L1 expression is demonstrated in both CK+ and CK-CTCs in patients with mBCa, and genomic analysis of these cells supports their tumor origin. Here we demonstrate the ability to identify CTCs in patients with advanced bladder cancer through a minimally invasive process. This may have the potential to guide checkpoint inhibitor immune therapies that have been established to have activity, often with durable responses, in a proportion of these patients.

Prostate cancer is the most frequently diagnosed and second most fatal nonskin cancer among men in the United States. African American men are two times more likely to develop and die of prostate cancer compared with men of other ancestries. Previous whole genome or exome tumor-sequencing studies of prostate cancer have primarily focused on men of European ancestry. In this study, we sequenced and characterized somatic mutations in aggressive (Gleason ≥7, stage ≥T2b) prostate tumors from 24 African American patients. We describe the locations and prevalence of small somatic mutations (up to 50 bases in length), copy number aberrations, and structural rearrangements in the tumor genomes compared with patient-matched normal genomes. We observed several mutation patterns consistent with previous studies, such as large copy number aberrations in chromosome 8 and complex rearrangement chains. However, TMPRSS2-ERG gene fusions and PTEN losses occurred in only 21% and 8% of the African American patients, respectively, far less common than in patients of European ancestry. We also identified mutations that appeared specific to or more common in African American patients, including a novel CDC27-OAT gene fusion occurring in 17% of patients. The genomic aberrations reported in this study warrant further investigation of their biologic significant role in the incidence and clinical outcomes of prostate cancer in African Americans. Cancer Res; 76(7); 1860-8. ©2016 AACR.

Evaluation of prostate cancer prognosis after surgery is increasingly relying upon genomic analyses of tumor DNA. We assessed the ability of the biomarker panel Genomic Evaluators of Metastatic Prostate Cancer (GEMCaP) to predict biochemical recurrence in 33 European American and 28 African American prostate cancer cases using genome-wide copy number data from a previous study. "Biomarker positive" was defined as ≥20% of the 38 constituent copy number gain/loss GEMCaP loci affected in a given tumor; based on this threshold, the frequency of a positive biomarker was significantly lower in African Americans (n = 2; 7%) than European Americans (n = 11; 33%; P = 0.013). GEMCaP positivity was associated with risk of recurrence [hazard ratio (HR), 5.92; 95% confidence interval (CI), 2.32-15.11; P = 3 × 10(-4)] in the full sample and among European Americans (HR, 3.45; 95% CI, 1.13-10.51; P = 0.032) but was not estimable in African Americans due to the low rate of GEMCaP positivity. Overall, the GEMCaP recurrence positive predictive value (PPV) was 85%; in African Americans, PPV was 100%. When we expanded the definition of loss to include copy-neutral loss of heterozygosity (i.e., loss of one allele with concomitant duplication of the other), recurrence PPV was 83% for European American subjects. Under this definition, 5 African American subjects had a positive GEMCaP test value; 4 went on to develop biochemical recurrence (PPV = 80%). Our results suggest that the GEMCaP biomarker set could be an effective predictor for both European American and African American men diagnosed with localized prostate cancer who may benefit from immediate aggressive therapy after radical prostatectomy.

Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) associated with complex traits. However, the genetic heritability of most of these traits remains unexplained. To help guide future studies, we address the crucial question of whether future GWAS can detect new SNP associations and explain additional heritability given the new availability of larger GWAS SNP arrays, imputation, and reduced genotyping costs. We first describe the pairwise and imputation coverage of all SNPs in the human genome by commercially available GWAS SNP arrays, using the 1000 Genomes Project as a reference. Next, we describe the findings from 6 years of GWAS of 172 chronic diseases, calculating the power to detect each of them while taking array coverage and sample size into account. We then calculate the power to detect these SNP associations under different conditions using improved coverage and/or sample sizes. Finally, we estimate the percentages of SNP associations and heritability previously detected and detectable by future GWAS under each condition. Overall, we estimated that previous GWAS have detected less than one-fifth of all GWAS-detectable SNPs underlying chronic disease. Furthermore, increasing sample size has a much larger impact than increasing coverage on the potential of future GWAS to detect additional SNP-disease associations and heritability.