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Health equity is the state in which everyone has fair and just opportunities to attain their highest level of health. The field of human genomics has fallen short in increasing health equity, largely because the diversity of the human population has been inadequately reflected among participants of genomics research. This lack of diversity leads to disparities that can have scientific and clinical consequences. Achieving health equity related to genomics will require greater effort in addressing inequities within the field. As part of the commitment of the National Human Genome Research Institute (NHGRI) to advancing health equity, it convened experts in genomics and health equity research to make recommendations and performed a review of current literature to identify the landscape of gaps and opportunities at the interface between human genomics and health equity research. This Perspective describes these findings and examines health equity within the context of human genomics and genomic medicine.

Introduction: Early lung cancer detection programs improve surgical resection rates and survival but may skew toward more indolent cancers. Methods: Hypothesizing that differences in stage-stratified survival indicate differences in biological aggressiveness and possible length-time and overdiagnosis bias, we assessed a cohort who had curative-intent resection, categorized by diagnostic pathways: screening, incidental pulmonary nodule program, and non–program based. Survival was analyzed using Kaplan-Meier plots, log-rank tests, and Cox regression, comparing aggregate and stage-stratified survival across cohorts with Tukey’s method for multiple testing. Results: Of 1588 patients, 111 patients (7%), 357 patients (22.5%), and 1120 patients (70.5%) were diagnosed through screening, pulmonary nodule, and non–program-based pathways; 0% versus 9% versus 6% were older than 80 years (p = 0.0048); 17%, 23%, and 24% had a Charlson Comorbidity score greater than or equal to 2 (p = 0.0143); 7%, 6%, and 9% had lepidic adenocarcinoma; 26%, 31%, and 34% had poorly or undifferentiated tumors (p = 0.1544); and 93%, 87%, and 77% had clinical stage I (p < 0.0001).Aggregate 5-year survival was 87%, 72%, and 65% (p = 0.0009), including 95%, 74%, and 74% for pathologic stage I. Adjusted pairwise comparisons showed similar survival in screening and nodule program cohorts (p = 0.9905). Nevertheless, differences were significant between screening and non–program-based cohorts (p = 0.0007, adjusted hazard ratio 0.33 [95% confidence interval: 0.18–0.6]) and between nodule and nonprogram cohorts (adjusted hazard ratio 0.77 [95% confidence interval: 0.61–0.99]). Stage I comparisons yielded p = 0.2256, 0.1131, and 0.911. In respective pathways, 0%, 2%, and 2% of patients with stage I disease who were older than 80 years had a Charlson score greater than or equal to 2 (p = 0.3849). Conclusions: Neither length-time nor overdiagnosis bias was evident in NSCLC diagnosed through screening or incidental pulmonary nodule programs.

Abstract Tuberculosis (TB) preventive therapy (TPT) is an effective strategy to eliminate TB in low-incidence settings. Shorter TPT regimens incorporating the antimicrobial class of rifamycins are designed to improve adherence and completion rates but carry the risk of modifications to the gut microbiota. We enrolled six subjects diagnosed with latent TB infection (LTBI) who accepted to initiate TPT. We also enrolled six healthy volunteers unexposed to the rifamycins. We profiled the gut microbiota using 16S rRNA amplicon sequencing (V1-V2 region) to document the immediate effect of rifamycin-based TPT on the gut microbiota composition and tracked recovery to baseline two months after TPT. Overall, TPT accounted for 17% of the variance in gut microbial community dissimilarity. This rifamycin-based TPT induced dysbiosis was characterized by a depletion of butyrate-producing taxa (Clostridium-XIVa and Roseburia) and expansion of potentially pathogenic taxa within the Firmicutes and Proteobacteria phyla. Recovery of the gut microbial composition was incomplete two months after TPT. Robust clinical studies are necessary to comprehensively catalogue TPT-induced gut microbiota dysbiosis to inform strategies to mitigate potential long-term sequelae of this important TB control intervention.

Historically, colorectal cancer (CRC) screening rates have been lower among African Americans. Previous studies that have examined the relationship between community characteristics and adherence to CRC screening have generally focused on a single community parameter, making it challenging to evaluate the overall impact of the social and built environment. In this study, we will estimate the overall effect of social and built environment and identify the most important community factors relevant to CRC screening. Data are from the Multiethnic Prevention and Surveillance Study (COMPASS), a longitudinal study among adults in Chicago, collected between May 2013 to March 2020. A total 2,836 African Americans completed the survey. Participants’ addresses were geocoded and linked to seven community characteristics (i.e., community safety, community crime, household poverty, community unemployment, housing cost burden, housing vacancies, low food access). A structured questionnaire measured adherence to CRC screening. Weighted quantile sum (WQS) regression was used to evaluate the impact of community disadvantages on CRC screening. When analyzing all community characteristics as a mixture, overall community disadvantage was associated with less adherence to CRC screening even after controlling for individual-level factors. In the adjusted WQS model, unemployment was the most important community characteristic (37.6%), followed by community insecurity (26.1%) and severe housing cost burden (16.3%). Results from this study indicate that successful efforts to improve adherence to CRC screening rates should prioritize individuals living in communities with high rates of insecurity and low socioeconomic status.

Key Points: Question: What is the association between social vulnerability and mental health and substance use disorders and related treatment in the US noninstitutionalized population of adults aged 18 years and older? Findings: In this survey study of 4674 participants from US households, large increases in several mental health and substance use disorders and corresponding decreases in treatment were found in the most socially vulnerable communities. Meaning: The findings suggest that routine measurement of social vulnerability might assist in developing more comprehensive care models that integrate medical and social care for mental health and substance use disorders. This survey study evaluates associations of social vulnerability with mental health disorders and substance use disorders in a noninstitutionalized setting. Importance: Community-level social vulnerability (SV) is associated with physical illness and premature mortality. Its association with mental health (MH) and substance use disorders (SUDs) needs further study. Objective: To study associations of SV with clinical diagnoses of MH disorders, SUDs, and related treatments in the US noninstitutionalized population of adults aged 18 years and older. Design, Setting, and Participants: A survey of adults in a national sample of US households between October 2020 and October 2022. Participants drawn from a multistage, clustered, and stratified area probability sample of US households were included, excluding adults older than 65 years because of the difficulty of differentiating mental disorders from symptoms of dementia. The sample also included adults living in prisons, state psychiatric hospitals, and homeless shelters who were excluded from the sample of US households used in these analyses. Each sample household was sent a letter explaining the study and offering the option to complete the household roster online, by phone, or by email. Of the 12 906 adults selected for clinical interviewing in the household sample, 4674 completed clinical interviews. Main Outcomes and Measures: Main outcomes were Structured Clinical Interview for DSM-5 past-year diagnoses of MH disorders and SUDs and responses to survey questions regarding treatment received. The Social Vulnerability Metric (SVM) and the Area Deprivation Index (ADI) were used to determine SV at the residential zip code level. Results: The analysis involved 4674 participants (2904 [62.13%] female and 1770 [37.87%] male; mean [SD] age, 41.51 [13.41] years). Controlling for measured confounders, the SVM was significantly associated with diagnoses of schizophrenia spectrum disorder (SSD; adjusted odds ratio [aOR], 17.22; 95% CI, 3.05-97.29), opioid use disorder (OUD; aOR, 9.47; 95% CI, 2.30-39.02), stimulant use disorder (aOR, 6.60; 95% CI, 2.01-21.67), bipolar I disorder (aOR, 2.39; 95% CI, 1.19-4.80), posttraumatic stress disorder (aOR, 1.63; 95% CI, 1.06-2.50), and any MH disorder (aOR, 1.44; 95% CI, 1.14-1.83), but not major depressive disorder (MDD), generalized anxiety disorder (GAD), or any SUD. Results were similar for the ADI but generally of lower magnitude (SSD aOR, 11.38; 95% CI, 1.61-80.58; OUD aOR, 2.05; 95% CI, 0.30-14.10; stimulant use disorder aOR, 2.18; 95% CI, 0.52-9.18). Among participants with SSDs, SV was associated with reduced MH treatment (aOR, 0.001; 95% CI, 0.00-0.18) and reduced SUD treatment in participants with OUD or stimulant use disorder (aOR, 0.24; 95% CI, 0.02-2.80). Conclusions and Relevance: In contrast to previous studies using nonclinical symptom-based survey data, we found no association between SV and GAD or MDD. By contrast, there were associations of SV with prevalence of SSD, stimulant use disorder, and OUD with corresponding decreases in treatment. These results suggest that the SVM might assist in developing more comprehensive care models that integrate medical and social care for MH disorders and SUDs. [ABSTRACT FROM AUTHOR]

Abstract Within an institutional pharmacogenomics implementation program, we surveyed 463 outpatients completing preemptive pharmacogenomic testing whose genetic results were available to providers for guiding medication treatment. We compared views and experiences from self-reported White and Black patients, including education level as a covariate across analyses. Black patients were less confident about whether their providers made personalized treatment decisions, and overwhelmingly wanted a greater role for their genetic information in clinical care. Both groups similarly reported that providers asked their opinions regarding medication changes, but White patients were more likely (59% vs. 49%, P = 0.005) to discuss the impact of personal/genetic makeup on medication response with providers, and Black patients reported initiating such discussions much less frequently (4% vs. 15%, P = 0.037). Opportunities exist for enhanced communication with underrepresented patients around personalized care. Tailored communication strategies and development of support tools employed in diverse healthcare settings may facilitate pharmacogenomically guided medication treatment that equitably benefits minority patient populations.

Background Perceived discrimination in health care settings can have adverse consequences on mental health in minority groups. However, the association between perceived discrimination and mental health is prone to unmeasured confounding. The study aims to quantitatively evaluate the influence of unmeasured confounding in this association, using g-estimation. Methods In a predominantly African American cohort, we applied g-estimation to estimate the association between perceived discrimination and mental health, adjusted and unadjusted for measured confounders. Mental health was measured using clinical diagnoses of anxiety, depression and bipolar disorder. Perceived discrimination was measured as the number of patient-reported discrimination events in health care settings. Measured confounders included demographic, socioeconomic, residential and health characteristics. The influence of confounding was denoted as α 1 from g-estimation. We compared α 1 for measured and unmeasured confounding. Results Strong associations between perceived discrimination in health care settings and mental health outcomes were observed. For anxiety, the odds ratio (95% confidence interval) unadjusted and adjusted for measured confounders were 1.30 (1.21, 1.39) and 1.26 (1.17, 1.36), respectively. The α 1 for measured confounding was –0.066. Unmeasured confounding with α 1 = 0.200 ⁠ , which was over three times that of measured confounding, corresponds to an odds ratio of 1.12 (1.01, 1.24). Similar results were observed for other mental health outcomes. Conclusion Compared with measured confounding, unmeasured that was three times measured confounding was not enough to explain away the association between perceived discrimination and mental health, suggesting that this association is robust to unmeasured confounding. This study provides a novel framework to quantitatively evaluate unmeasured confounding. [ABSTRACT FROM AUTHOR]

Background: Biomarker-directed therapy requires biomarker testing. We assessed the patterns of epidermal growth factor receptor (EGFR) and programmed death ligand 1 (PDL1) testing in a non-small cell lung cancer (NSCLC) resection cohort. We hypothesized that testing would increase but be unevenly distributed across patient-, provider- and institution-level demographics. Methods: We examined the population-based Mid-South Quality of Surgical Resection (MS-QSR) cohort of NSCLC resections. We evaluated the proportions receiving EGFR and PDL1 testing before and after approval of biomarker-directed adjuvant therapy (2018-2020 vs. 2021-2022). We used association tests and logistic regression to compare factors. Results: From 2018 to 2022, 1,687 patients had NSCLC resection across 12 MS-QSR institutions: 1,045 (62%) from 2018 to 2020 and 642 (38%) from 2021 to 2022. From 2018 to 2020, 11% had EGFR testing versus 38% in 2021 to 2022 (56% in those meeting ADAURA trial inclusion criteria, P < 0.0001). From 2018 to 2020, 8% had PDL1 testing versus 20% in 2021 to 2022 (P < 0.0001). EGFR testing did not significantly differ by age (P = 0.07), sex (P = 0.99), race (P = 0.33), or smoking history (P = 0.28); PDL1 testing did not differ significantly by age (P = 0.47), sex (P = 0.41), race (P = 0.51), or health insurance (P = 0.07). Testing was significantly less likely in nonteaching and non-Commission on Cancer-accredited hospitals and after resection by cardiothoracic or general surgeons (vs. general thoracic surgeons; all P < 0.05). Conclusions: EGFR and PDL1 testing increased after approval of biomarker-directed adjuvant therapies. However, testing rates were still suboptimal and differed by institutional- and provider-level factors. [ABSTRACT FROM AUTHOR]

The article presents the discussion on pivotal role of Medicaid as the primary safety net for vulnerable populations in the US since its inception in 1965. Topics include Medicaid's coverage of diverse populations, variations in state administration, and the significant increase in Medicaid-managed care enrollment, urging for public awareness of its implications on healthcare access, spending, and equity.

Rising cancer care costs impose financial burdens on health systems. Applying artificial intelligence to diagnostic algorithms may reduce testing costs and avoid wasteful therapy-related expenditures. To evaluate the financial and clinical impact of incorporating artificial intelligence-based determination of mismatch repair/microsatellite instability status into the first-line metastatic colorectal carcinoma setting, we developed a deterministic model to compare eight testing strategies: A) next-generation sequencing alone, B) high-sensitivity polymerase chain reaction or immunohistochemistry panel alone, C) high-specificity panel alone, D) high-specificity artificial intelligence alone, E) high-sensitivity artificial intelligence followed by next generation sequencing, F) high-specificity artificial intelligence followed by next-generation sequencing, G) high-sensitivity artificial intelligence and high-sensitivity panel, and H) high-sensitivity artificial intelligence and high-specificity panel. We used a hypothetical, nationally representative, population-based sample of individuals receiving first-line treatment for de novo metastatic colorectal cancer (N = 32,549) in the United States. Model inputs were derived from secondary research (peer-reviewed literature and Medicare data). We estimated the population-level diagnostic costs and clinical implications for each testing strategy. The testing strategy that resulted in the greatest project cost savings (including testing and first-line drug cost) compared to next-generation sequencing alone in newly-diagnosed metastatic colorectal cancer was using high-sensitivity artificial intelligence followed by confirmatory high-specificity polymerase chain reaction or immunohistochemistry panel for patients testing negative by artificial intelligence ($400 million, 12.9%). The high-specificity artificial intelligence-only strategy resulted in the most favorable clinical impact, with 97% diagnostic accuracy in guiding genotype-directed treatment and average time to treatment initiation of less than one day. Artificial intelligence has the potential to reduce both time to treatment initiation and costs in the metastatic colorectal cancer setting without meaningfully sacrificing diagnostic accuracy. We expect the artificial intelligence value proposition to improve in coming years, with increasing diagnostic accuracy and decreasing costs of processing power. To extract maximal value from the technology, health systems should evaluate integrating diagnostic histopathologic artificial intelligence into institutional protocols, perhaps in place of other genotyping methodologies.

Importance: The International Association for the Study of Lung Cancer (IASLC) has proposed a revision of the residual disease (R-factor) classification, to R0, ‘R-uncertain’, R1 and R2. We previously demonstrated longer survival after surgical resection with a lymph node specimen collection kit, and now evaluate R-factor redistribution as the mechanism of its survival benefit. Objective: We retrospectively evaluated surgical resections for lung cancer in the population-based observational ‘Mid-South Quality of Surgical Resection’ cohort from 2009-2019, including a full-cohort and propensity-score matched analysis. Results: Of 3,505 resections, 34% were R0, 60% R-uncertain, and 6% R1 or R2. The R0 percentage increased from 9% in 2009 to 56% in 2019 (p < 0.0001). Kit cases were 66% R0 and 29% R-uncertain, compared to 14% R0 and 79% R-uncertain in non-kit cases (p < 0.0001). Compared with non-kit resections, kit resections had 12.3 times the adjusted odds of R0 versus R-uncertainty.Of 2,100 R-uncertain resections, kit cases had lower percentages of non-examination of lymph nodes, 1% vs. 14% (p < 0.0001) and non-examination of mediastinal lymph nodes, 8% vs. 35% (p < 0.0001). With the kit, more R-uncertain cases had examination of stations 7 (43% vs. 22%, p < 0.0001) and 10 (67% vs. 45%, p < 0.0001).The adjusted hazard ratio (aHR) for kit cases versus non-kit cases was 0.75 (confidence interval [CI]: 0.66–0.85, p < 0.0001). In 2,100 subjects with R-uncertain resections, kit cases had an aHR of 0.79 versus non-kit cases ([CI: 0.64–0.99], p=0.0384); however, in the 1,199 R0 resections the survival difference was not significant (aHR: 0.85[0.68–1.07], p = 0.17). Conclusions and Relevance: A lymph node kit increased overall survival by increasing R0, reducing the probability of R-uncertain resections, and diminishing extreme R-uncertainty.

BackgroundAdvancements in treatment have contributed to increased survivorship among children with sickle cell disease (SCD). Increased transition readiness, encompassing disease knowledge and self-management skills before transfer to adult care, is necessary to ensure optimal health outcomes. The Sickle Cell Transition E-Learning Program (STEP) is a public, Web-based, 6-module tool designed to increase transition readiness for youth with SCD. ObjectiveThe objective of our study was to investigate the participation rate of youth with SCD in STEP and its association with transition readiness. MethodsThis was a single-center, Institution Review Board–approved, retrospective cohort review. A total of 183 youths with SCD, aged between 12 and 15 years, were offered STEP as an adjunct to in-clinic disease education sessions. Participation rate (number of patients who used at least one STEP module divided by those approached) was calculated. The association among the number of STEP modules completed, disease knowledge, and self-management was explored. ResultsOverall, 53 of the 183 approached adolescents completed at least one STEP module, yielding a participation rate in STEP of 29.0%. Of the 53 participants, 37 and 39 adolescents had disease knowledge and self-management confidence rating available, respectively. A positive correlation (r=0.47) was found between the number of STEP modules completed and disease knowledge scores (P=.003). No association was found between the number of modules completed and self-management confidence ratings. Disease knowledge scores were significantly higher among participants who completed ≥3 STEP modules compared with those who completed

This study assessed the extent to which high fat diet (HFD)-induced β-amyloid accumulation and cognitive decline in APP/PSEN1 mice are reversible through control of fat intake. Ten months of HFD (60% calories from fat) led to significant deficits in a 2-trial Y maze task, and nest building assay, and decreased voluntary locomotor activity. The HFD induced an inflammatory response, indicated by increased expression of several inflammatory markers. Substituting a low fat diet led to pronounced weight loss and correction of glucose intolerance, decreases in the inflammatory response, and improved performance on behavioral tasks in both wild-type and APP/PSEN1 transgenic mice. Insoluble β-amyloid levels, and extent of tau phosphorylation were also lower following dietary reversal in APP/PSEN1 mice compared to high fat-fed animals, indicating that the inflammatory response may have contributed to key pathogenic pathways in the Alzheimer's disease model. The data suggest that weight loss can be a vital strategy for cognitive protection, but also highlight potential mechanisms for intervention when sustained weight loss is not possible.