Racial and ethnic disparities in gallbladder cancer: A two-decade analysis of incidence and mortality rates in the US.

BACKGROUND: Gallbladder cancer (GBC) is an aggressive malignancy that is usually diagnosed at a late stage. Prior data showed increasing incidence of GBC in the US. However, little is known about race/ethnic-specific incidence and mortality trends of GBC per stage at diagnosis. Therefore, we aimed to conduct a time-trend analysis of GBC incidence and mortality rates categorized by race/ethnicity and stage-at-diagnosis. METHODS: Age-adjusted GBC incidence and mortality rates were calculated using SEER*Stat software from the United States Cancer Statistics database (covers ~98% of US population between 2001 and 2020) and NCHS (covers ~100% of the US population between 2000 and 2020) databases, respectively. Race/Ethnic groups were Non-Hispanic-White (NHW), Non-Hispanic-Black (NHB), Hispanic, Non-Hispanic-Asian/Pacific-Islander (NHAPI), and Non-Hispanic-American-Indian/Alaska-Native (NHAIAN). Stage-at-diagnoses were all stages, early, regional, and distant stages. Joinpoint regression was used to generate time-trends [annual percentage change (APC) and average APC (AAPC)] with parametric estimations and a two-sided t-test (p-value cut-off 0.05). RESULTS: 76,873 patients were diagnosed with GBC with decreasing incidence rates in all races/ethnicities except NHB who experienced an increasing trend between 2001 and 2014 (APC = 2.08, p < 0.01) and plateauing afterward (APC = -1.21, p = 0.31); (AAPC = 1.03, p = 0.03). Among early-stage tumors (9927 patients), incidence rates were decreasing only in Hispanic (AAPC = -4.24, p = 0.006) while stable in other races/ethnicities (NHW: AAPC = -2.61, p = 0.39; NHB: AAPC = -1.73, p = 0.36). For regional-stage tumors (29,690 patients), GBC incidence rates were decreasing only in NHW (AAPC = -1.61, p < 0.001) while stable in other races/ethnicities (NHB: AAPC = 0.73, p = 0.34; Hispanic: AAPC = -1.58, p = 0.24; NHAPI: AAPC = -1.22, p = 0.07). For distant-stage tumors (31,735 patients), incidence rates were increasing in NHB (AAPC = 2.72, p < 0.001), decreasing in Hispanic (AAPC = -0.64, p = 0.04), and stable in NHW (AAPC = 0.07, p = 0.84) and NHAPI (AAPC = 0.79, p = 0.13). There were 43,411 deaths attributed to GBC with decreasing mortality rates in all races/ethnicities except NHB who experienced a stable trend (AAPC = 0.25, p = 0.25). CONCLUSION: Nationwide data over the last two decades show that NHB patients experienced increasing GBC incidence between 2001 and 2014 followed by stabilization of the rates. This increase was driven by late-stage tumors and occurred in the first decade. NHB also experienced non-improving GBC mortality, compared to other race and ethnic groups who had decreasing mortality. This can be due to lack of timely-access to healthcare leading to delayed diagnosis and worse outcomes. Future studies are warranted to investigate contributions to the revealed racial and ethnic disparities, especially in NHB, to improve early detection.

Overall, sex-and race/ethnicity-specific prevalence of thyroid dysfunction in US adolescents aged 12-18 years.

Background: Thyroid dysfunction significantly affects the health and development of adolescents. However, comprehensive studies on its prevalence and characteristics in US adolescents are lacking. Methods: We investigated the prevalence of thyroid dysfunction in US adolescents aged 12-18 years using data from the National Health and Nutrition Examination Survey (NHANES) 2001-2002 and 2007-2012 cycles. Thyroid dysfunction was assessed using serum thyroid-stimulating hormone (TSH) and free thyroxine (fT4) measurements. We analyzed the prevalence across demographic subgroups and identified associated risk factors. Results: The study included 2,182 participants, representing an estimated 12.97 million adolescents. The group had a weighted mean age of 15.1 ± 0.06 years, with males constituting 51.4%. Subclinical hyperthyroidism emerged as the most prevalent thyroid dysfunction, affecting 4.4% of the population. From 2001-2002 to 2011-2012, subclinical hyperthyroidism remained consistent at 4.99% vs. 5.13% in the overall cohort. Subclinical and overt hypothyroidism was found in 0.41 and 1.03% of adolescents respectively, and overt hyperthyroidism was rare (0.04%). The prevalence of thyroid peroxidase antibody (TPOAb) and thyroglobulin antibody (TgAb) positivity in the overall population were 5.8 and 9.8%, respectively. Positivity for TgAb was risk factors for hypothyroidism, while older age, female and Black Americans were risk factors for hyperthyroidism. Female adolescents and adolescents with an older age were more likely to be positive for TPOAb and TgAb, while Black and Mexican Americans had a lower risk of TPOAb and TgAb positivity. Conclusion: Subclinical hyperthyroidism was the most common form of thyroid dysfunction, and its prevalence remained stable from 2001-2002 to 2011-2012. Notable disparities in the prevalence of hyperthyroidism and antibody positivity were observed among different age, sex and racial/ethnic groups.

Reassessing the Use of Race in Clinical Algorithms: An Interactive, Case-Based Session for Medical Students Using eGFR.

Introduction: Medical curricula implicitly teach that race has a biological basis. Clinical rotations reinforce this misconception as race-based algorithms are used to guide clinical decision-making. This module aims to expose the fallacy of race in clinical algorithms, using the estimated glomerular filtration rate (eGFR) equation as an example. Methods: We created a 60-minute module in consultation with nephrologists. The format was an interactive, case-based presentation with a didactic section. A third-year medical student facilitated the workshops to medical students. Evaluation included pre/post surveys using 5-point Likert scales to assess awareness regarding use of race as a biological construct. Higher scores indicated increased awareness. Results: Fifty-five students participated in the module. Pre/post results indicated that students significantly improved in self-perceived knowledge of the history of racism in medicine (2.6 vs. 3.2, p < .001), awareness of race in clinical algorithms (2.7 vs. 3.7, p < .001), impact of race-based eGFR on quality of life/treatment outcomes (4.5 vs. 4.8, p = .01), differences between race and ancestry (3.7 vs. 4.3, p < .001), and implications of not removing race from the eGFR equation (2.7 vs. 4.2, p < .001). Students rated the workshops highly for quality and clarity. Discussion: Our module expands on others' work to expose the fallacy of race-based algorithms and define its impact on health equity. Limitations include a lack of objective assessment of knowledge acquisition. We recommend integrating this module into preclinical and clinical curricula to discuss the use of race in medical literature and clinical practice.

Detecting Early-Stage Pressure Injury in Patients With Dark Skin Tones Using an Enhanced Physical Assessment Technique and Halogen Lighting.

PURPOSE: The purpose of this quality improvement project was to identify stage 1 pressure injuries (PIs) in patients with darker skin tones using an enhanced skin assessment (Skin Assessment for Dark Skin, SADS) and halogen lighting. PARTICIPANTS AND SETTING: This quality improvement project was conducted on 3 units at a large university teaching hospital in Southeast Michigan. The project was originally designed so that participating patients were identified by bedside nurses as having sufficient melanin to obscure blanching on the hand/forearm using regular lighting, but this goal was not met. Data analysis is based on patients who self-identified as African American or Black, Native Hawaiian or Pacific Islander, Asian, American Indian, and Native Alaskan. Bedside nurses participating in this project were also asked to complete a questionnaire describing their knowledge and experiences with this project and assessment of early-stage PI in patients with darker skin tones. APPROACH: The Iowa Model of Evidence-Based Practice was used to guide this quality improvement initiative. Following a trigger event, we reviewed pertinent literature and developed an enhanced technique for assessing patients with darker skin tones that involved use of halogen lighting (SADS) and documentation of findings. We selected units from our facility and taught nurses to apply the SADS approach. Data from the electronic medical record and a survey of participating nurses were used to compare findings before and after project implementation. Comparisons were based on descriptive data analysis. OUTCOMES: Following implementation of the enhanced physical assessment, the participating units experienced a 6% decrease in the total number of facility-acquired PIs during the implementation period. IMPLICATIONS FOR PRACTICE: The enhanced physical assessment, when paired with halogen lighting, enhanced identification of stage 1 PI in persons with dark skin. The assessment method was easy to teach, learn, and can be performed at the bedside as part of a shift assessment which routinely includes inspection of skin.

Challenging Misconceptions about Race in Undergraduate Genetics.

Racial biases, which harm marginalized and excluded communities, may be combatted by clarifying misconceptions about race during biology lessons. We developed a human genetics laboratory activity that challenges the misconception that race is biological (biological essentialism). We assessed the relationship between this activity and student outcomes using a survey of students' attitudes about biological essentialism and color-evasive ideology and a concept inventory about phylogeny and human diversity. Students in the human genetics laboratory activity showed a significant decrease in their acceptance of biological essentialism compared with a control group, but did not show changes in color-evasive ideology. Students in both groups exhibited increased knowledge in both areas of the concept inventory, but the gains were larger in the human genetics laboratory. In the second iteration of this activity, we found that only white students' decreases in biological essentialist beliefs were significant and the activity failed to decrease color-evasive ideologies for all students. Concept inventory gains were similar and significant for both white and non-white students in this iteration. Our findings underscore the effectiveness of addressing misconceptions about the biological origins of race and encourage more research on ways to effectively change damaging student attitudes about race in undergraduate genetics education.

Implicit bias and experience influence overall but not relative trustworthiness judgment of other-race faces.

Impressions of trustworthiness are formed quickly from faces. To what extent are these impressions shared among observers of the same or different races? Although high consensus of trustworthiness evaluation has been consistently reported, recent studies suggested substantial individual differences. For instance, negative implicit racial bias and low contact experience towards individuals of the other race have been shown to be related to low trustworthiness judgments for other-race faces. This pre-registered study further examined the effects of implicit social bias and experience on trustworthiness judgments of other-race faces. A relatively large sample of White (N = 338) and Black (N = 299) participants completed three tasks: a trustworthiness rating task of faces, a race implicit association test, and a questionnaire of experience. Each participant rated trustworthiness of 100 White faces and 100 Black faces. We found that the overall trustworthiness ratings for other-race faces were influenced by both implicit bias and experience with individuals of the other-race. Nonetheless, when comparing to the own-race baseline ratings, high correlations were observed for the relative differences in trustworthiness ratings of other-race faces for participants with varied levels of implicit bias and experience. These results suggest differential impact of social concepts (e.g., implicit bias, experience) vs. instinct (e.g., decision of approach-vs-avoid) on trustworthiness impressions, as revealed by overall vs. relative ratings on other-race faces.

Relationship between Plasma P-Tau217 and Amyloid PET in Racial and Ethnic Underrepresented Groups (RE-URG) Compared with Non RE-URG in LEARN and A4.

BACKGROUND: Individuals from diverse racial and ethnic groups are severely underrepresented in Alzheimer's disease trials in part due to disproportionate biomarker ineligibility. Evidence from recent studies support plasma phosphorylated tau 217 (P-tau217) as an early marker for brain Aß pathology and a reliable marker in predicting elevated brain amyloid PET in cognitively unimpaired adults. OBJECTIVES: To examine whether the relationship between P-tau217 and 18-F florbetapir PET standard uptake value ratios (SUVR) is influenced by race and ethnicity in the Anti-Amyloid treatment in Asymptomatic Alzheimer's disease (A4) preclinical AD studies. DESIGN: We conducted a retrospective analysis of A4 clinical trial and the LEARN natural history companion study data to evaluate the relationship between baseline P-tau217 and PET SUVR concentration levels by race and ethnicity. SETTING: The analysis was conducted on samples from participants enrolled across 65 study sites in the United States and Canada. PARTICIPANTS: Cognitively unimpaired adults aged 65-85 enrolled at North American sites in the A4 preclinical AD trial, pre-dose, (N=1018), and the LEARN (N=480) study. Participants were grouped into 2 categories, racial and ethnic underrepresented group (RE-URG) and non-RE-URG (nRE-URG) based on self-identification. MEASUREMENTS: A mixed-effects regression model was fit to determine differences in the relationship between P-tau217 and PET SUVR by race and ethnicity, adjusting for age, and APOE ε4 carrier status. RESULTS: Results from the linear mixed-effects model support that there was no statistically significant effect of race and ethnicity on the relationship between P-tau217 and PET SUVR. CONCLUSION: These findings suggest that the relationship between plasma P-tau217 and PET SUVR is the same across race and ethnicity. Future analyses should corroborate these findings in a larger sample and examine whether plasma P-tau217 reflects the differential amyloid prevalence previously reported for other biomarkers of amyloid.

Prediction of future visceral adiposity and application to cancer research: The Multiethnic Cohort Study.

BACKGROUND: We previously developed a prediction score for MRI-quantified abdominal visceral adipose tissue (VAT) based on concurrent measurements of height, body mass index (BMI), and nine blood biomarkers, for optimal performance in five racial/ethnic groups. Here we evaluated the VAT score for prediction of future VAT and examined if enhancement with additional biomarkers, lifestyle behavior information, and medical history improves the prediction. METHODS: We examined 500 participants from the Multiethnic Cohort (MEC) with detailed data (age 50-66) collected 10 years prior to their MRI assessment of VAT. We generated three forecasted VAT prediction models: first by applying the original VAT equation to the past data on the predictors ("original"), second by refitting the past data on anthropometry and biomarkers ("refit"), and third by building a new prediction model based on the past data enhanced with lifestyle and medical history ("enhanced"). We compared the forecasted prediction scores to future VAT using the coefficient of determination (R2). In independent nested case-control data in MEC, we applied the concurrent and forecasted VAT models to assess association of the scores with subsequent incident breast cancer (950 pairs) and colorectal cancer (831 pairs). RESULTS: Compared to the VAT prediction by the concurrent VAT score (R2 = 0.70 in men, 0.68 in women), the forecasted original VAT score (R2 = 0.54, 0.48) performed better than past anthropometry alone (R2 = 0.47, 0.40) or two published scores (VAI, METS-VF). The forecasted refit (R2 = 0.61, 0.51) and enhanced (R2 = 0.62, 0.55) VAT scores each showed slight improvements. Similar to the concurrent VAT score, the forecasted VAT scores were associated with breast cancer, but not colorectal cancer. Both the refit score (adjusted OR for tertile 3 vs. 1 = 1.27; 95% CI: 1.00-1.62) and enhanced score (1.27; 0.99-1.62) were associated with breast cancer independently of BMI. CONCLUSIONS: Predicted VAT from midlife data can be used as a surrogate to assess the effect of VAT on incident diseases associated with obesity, as illustrated for postmenopausal breast cancer.

Fairness in Predicting Cancer Mortality Across Racial Subgroups.

Importance: Machine learning has potential to transform cancer care by helping clinicians prioritize patients for serious illness conversations. However, models need to be evaluated for unequal performance across racial groups (ie, racial bias) so that existing racial disparities are not exacerbated. Objective: To evaluate whether racial bias exists in a predictive machine learning model that identifies 180-day cancer mortality risk among patients with solid malignant tumors. Design, Setting, and Participants: In this cohort study, a machine learning model to predict cancer mortality for patients aged 21 years or older diagnosed with cancer between January 2016 and December 2021 was developed with a random forest algorithm using retrospective data from the Mount Sinai Health System cancer registry, Social Security Death Index, and electronic health records up to the date when databases were accessed for cohort extraction (February 2022). Exposure: Race category. Main Outcomes and Measures: The primary outcomes were model discriminatory performance (area under the receiver operating characteristic curve [AUROC], F1 score) among each race category (Asian, Black, Native American, White, and other or unknown) and fairness metrics (equal opportunity, equalized odds, and disparate impact) among each pairwise comparison of race categories. True-positive rate ratios represented equal opportunity; both true-positive and false-positive rate ratios, equalized odds; and the percentage of predictive positive rate ratios, disparate impact. All metrics were estimated as a proportion or ratio, with variability captured through 95% CIs. The prespecified criterion for the model's clinical use was a threshold of at least 80% for fairness metrics across different racial groups to ensure the model's prediction would not be biased against any specific race. Results: The test validation dataset included 43 274 patients with balanced demographics. Mean (SD) age was 64.09 (14.26) years, with 49.6% older than 65 years. A total of 53.3% were female; 9.5%, Asian; 18.9%, Black; 0.1%, Native American; 52.2%, White; and 19.2%, other or unknown race; 0.1% had missing race data. A total of 88.9% of patients were alive, and 11.1% were dead. The AUROCs, F1 scores, and fairness metrics maintained reasonable concordance among the racial subgroups: the AUROCs ranged from 0.75 (95% CI, 0.72-0.78) for Asian patients and 0.75 (95% CI, 0.73-0.77) for Black patients to 0.77 (95% CI, 0.75-0.79) for patients with other or unknown race; F1 scores, from 0.32 (95% CI, 0.32-0.33) for White patients to 0.40 (95% CI, 0.39-0.42) for Black patients; equal opportunity ratios, from 0.96 (95% CI, 0.95-0.98) for Black patients compared with White patients to 1.02 (95% CI, 1.00-1.04) for Black patients compared with patients with other or unknown race; equalized odds ratios, from 0.87 (95% CI, 0.85-0.92) for Black patients compared with White patients to 1.16 (1.10-1.21) for Black patients compared with patients with other or unknown race; and disparate impact ratios, from 0.86 (95% CI, 0.82-0.89) for Black patients compared with White patients to 1.17 (95% CI, 1.12-1.22) for Black patients compared with patients with other or unknown race. Conclusions and Relevance: In this cohort study, the lack of significant variation in performance or fairness metrics indicated an absence of racial bias, suggesting that the model fairly identified cancer mortality risk across racial groups. It remains essential to consistently review the model's application in clinical settings to ensure equitable patient care.

Racial and social inequities in medication use: A review of articles responding to the Journal of Managed Care + Specialty Pharmacy's Call to Action.

This article provides a summary of Viewpoint and Research articles responding to the 2020 Journal of Managed Care + Specialty Pharmacy Call to Action to address racial and social inequities in medication use. We find great heterogeneity in terms of topic, clinical condition examined, and health disparity addressed. Common recommendations across Viewpoint articles include the need to increase racial and ethnic diversity in clinical trial participants, the need to address drug affordability and health insurance literacy, and the need to incentivize providers and plans to participate in diversity initiatives, such as the better capture of information on social determinants of health (SDOH) in claims data to be able to address SDOH needs. Across research articles, we also find a large range of approaches and study designs, spanning from randomized controlled trials to surveys to observational studies. These articles identify disparities in which minoritized beneficiaries are shown to be less likely to receive medications and vaccines, as well as less likely to be adherent to medications, across a variety of conditions. Finally, we discuss Healthy People 2030 as a potential framework for future health disparity researchers.

How people are exposed to neighborhoods racially different from their own.

In US cities, neighborhoods have long been racially segregated. However, people do not spend all their time in their neighborhoods, and the consequences of residential segregation may be tempered by the contact people have with other racial groups as they traverse the city daily. We examine the extent to which people's regular travel throughout the city is to places "beyond their comfort zone" (BCZ), i.e., to neighborhoods of racial composition different from their own-and why. Based on travel patterns observed in more than 7.2 million devices in the 100 largest US cities, we find that the average trip is to a neighborhood less than half as racially different from the home neighborhood as it could have been given the city. Travel to grocery stores is least likely to be BCZ; travel to gyms and parks, most likely; however, differences are greatest across cities. For the first ~10 km people travel from home, neighborhoods become increasingly more BCZ for every km traveled; beyond that point, whether neighborhoods do so depends strongly on the city. Patterns are substantively similar before and after COVID-19. Our findings suggest that policies encouraging more 15-min travel-that is, to amenities closer to the home-may inadvertently discourage BCZ movement. In addition, promoting use of certain "third places" such as restaurants, bars, and gyms, may help temper the effects of residential segregation, though how much it might do so depends on city-specific conditions.

Improvements in data completeness in health information systems reveal racial inequalities: longitudinal national data from hospital admissions in Brazil 2010-2022.

BACKGROUND: Race and ethnicity are important drivers of health inequalities worldwide. However, the recording of race/ethnicity in data systems is frequently insufficient, particularly in low- and middle-income countries. The aim of this study is to descriptively analyse trends in data completeness in race/color records in hospital admissions and the rates of hospitalizations by various causes for Blacks and Whites individuals. METHODS: We conducted a longitudinal analysis, examining hospital admission data from Brazil's Hospital Information System (SIH) between 2010 and 2022, and analysed trends in reporting completeness and racial inequalities. These hospitalization records were examined based on year, quarter, cause of admission (using International Classification of Diseases (ICD-10) codes), and race/color (categorized as Black, White, or missing). We examined the patterns in hospitalization rates and the prevalence of missing data over a period of time. RESULTS: Over the study period, there was a notable improvement in data completeness regarding race/color in hospital admissions in Brazil. The proportion of missing values on race decreased from 34.7% in 2010 to 21.2% in 2020. As data completeness improved, racial inequalities in hospitalization rates became more evident - across several causes, including assaults, tuberculosis, hypertensive diseases, at-risk hospitalizations during pregnancy and motorcycle accidents. CONCLUSIONS: The study highlights the critical role of data quality in identifying and addressing racial health inequalities. Improved data completeness has revealed previously hidden inequalities in health records, emphasizing the need for comprehensive data collection to inform equitable health policies and interventions. Policymakers working in areas where socioeconomic data reporting (including on race and ethnicity) is suboptimal, should address data completeness to fully understand the scale of health inequalities.

Racial and Ethnic Diversity in Vitiligo Clinical Trials: A Retrospective Cross-Sectional Study Assessing Demographic Reporting of Participants.

BACKGROUND: While the prevalence of vitiligo is similar across racial and ethnic groups, the effects of vitiligo vary by demographic group, culture, and skin color, with darker-skinned individuals facing greater stigma due to increased visibility of the disease.1,2 The recruitment of diverse participants that are representative of the United States (US) population is crucial to ensuring the generalizability of findings and understanding the impacts of vitiligo across diverse patient groups.   Objectives: This study aimed to determine demographic reporting trends in US vitiligo clinical trials and to determine whether participants are representative of the US population. METHODS: A search for US vitiligo clinical trials was conducted on clinicaltrials.gov. Trials conducted between 2006 to September 5, 2023, were included if they intended to treat vitiligo, were conducted in the US, and were completed or terminated.  Results: Of the 15 trials meeting inclusion criteria, only 60% (n=9) reported participant race/ethnicity. These 9 studies included 1,510 participants, of which only 25.43% (n=384) were non-White and 20.40% were Hispanic. There was disproportionately low representation of racial minorities, particularly Black, Native American, and Native Hawaiian groups.   Limitations: Limitations of our study include small sample size, variations in demographic reporting between trials, and undercounting of minority groups by the US Census.  Conclusions: Racial and ethnic minority groups remain underrepresented in US vitiligo clinical trials. Given that the impact of vitiligo can vary by the affected individual’s demographic group and skin color, investigators must be intentional about including a more diverse and representative population in vitiligo clinical trials.  J Drugs Dermatol. 2024;23(7):e164-e166. doi:10.36849/JDD.8117e.