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Context: Racial/ethnic minorities suffer disproportionate morbidity and mortality from chronic diseases.
Objective: Our objective was to assess racial and socioeconomic status (SES) disparities in well-differentiated thyroid cancer (WDTC) patients.
Design And Participants: We conducted a retrospective cohort study on 25 945 patients with WDTC (1999-2008) from the California Cancer Registry (57% white, 4% black, 24% Hispanic, and 15% Asian-Pacific Islander [API]).
Main Outcomes: We evaluated effect of race and SES variables on stage of cancer presentation and overall/disease-specific survival.
Results: Significant differences in stage of presentation between all racial groups were found (P<.001), with minority groups presenting with a higher percentage of metastatic disease as compared with white patients (black, odds ratio [OR]=1.36 with confidence interval [CI] 1.01-1.84; Hispanic, OR=1.89 [CI, 1.62-2.21], API, OR=1.82 [CI, 1.54-2.15]). Hispanic (OR=1.59, [CI, 1.48-1.72]) and API (OR=1.32 [1.22-1.44]) patients also presented with higher odds of regional disease. Patients with the lowest SES presented with metastatic disease more often than those with the highest SES (OR=1.45 [CI, 1.16-1.82]). Those that were poor/uninsured and/or with Medicaid insurance had higher odds of presenting with metastatic disease as compared with those with private insurance (OR=2.41, [CI, 2.10-2.77]). Unadjusted overall survival rates were higher among API and Hispanic patients and lower among black patients (P<.001 vs white patients). Adjusted overall survival also showed a survival disadvantage for black patients (hazard ratio=1.4, [CI, 1.10-1.73]) and survival advantage for API patients (hazard ratio=0.83, [CI, 0.71-0.97]). In disease-specific survival analyses, when only those patients with metastatic disease were analyzed separately, black patients again had the lowest survival rates, and Hispanic/API patients had the highest survival rates (P<.04).
Conclusion: Black patients and those with low SES have worse outcomes for thyroid cancer. API and Hispanic patients may have a protective effect on survival despite presenting with more advanced disease.
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http://dx.doi.org/10.1210/jc.2013-2781 | DOI Listing |
Inj Prev
September 2025
Division of Injury Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Background: Previous research suggests that some racial/ethnic groups are at increased risk for poor health outcomes following a traumatic brain injury (TBI). Less is known about the extent to which TBI prevalence and incidence vary by race/ethnicity. This paper presents results of a systematic search and review of TBI prevalence and incidence among US racial and ethnic groups.
View Article and Find Full Text PDFLaryngoscope
September 2025
Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California, USA.
Objective: To evaluate and quantify the mediation effects of neighborhood socioeconomic status (SES), insurance status, and quality of care on racial disparities in HNC survival.
Methods: Retrospective cohort study of data from the California Cancer Registry dataset linked with discharge records and hospital characteristics from the California Department of Health Care Access and Information. The study cohort included adult patients with HNC diagnosed between January 1, 2010, and December 31, 2019.
Older adults often show improved emotional regulation with age, a phenomenon known as the aging paradox. This age-related increase in emotional regulation capacity is attributed to enhanced prefrontal cortex control over amygdala reactivity. However, because racial discrimination and economic disadvantage cause chronic stress, typical age-related neural associations may be altered in marginalized groups.
View Article and Find Full Text PDFJ Med Internet Res
September 2025
Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, United States, 1 2122416500.
Background: The growing adoption of diagnostic and prognostic algorithms in health care has led to concerns about the perpetuation of algorithmic bias against disadvantaged groups of individuals. Deep learning methods to detect and mitigate bias have revolved around modifying models, optimization strategies, and threshold calibration with varying levels of success and tradeoffs. However, there have been limited substantive efforts to address bias at the level of the data used to generate algorithms in health care datasets.
View Article and Find Full Text PDFTher Adv Neurol Disord
September 2025
Baylor Scott & White Health, Temple, TX, USA.
Background: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with limited treatment options and significant variability in care. Racial and ethnic disparities in ALS management and outcomes have been reported, but findings remain inconsistent.
Objectives: This study aimed to evaluate racial and ethnic disparities in ALS care, specifically differences in healthcare utilization, treatment patterns, and survival, within a large healthcare system.