Racial Disparities in Colorectal Cancer Care for Black Patients: Barriers and Solutions

Racial and Ethnic Disparities in Hepatocellular Carcinoma Treatment Receipt in the United States: A Systematic Review and Meta-Analysis

BACKGROUND

Racial and ethnic disparities in hepatocellular carcinoma (HCC) prognosis exist, partly related to differential failures along the cancer care continuum. We characterized racial and ethnic disparities in treatment receipt among patients with HCC in the United States.

METHODS

We searched Medline, Embase, and CINAHL databases to identify studies published between January 2012 and March 2022 reporting HCC treatment receipt among adult patients with HCC, stratified by race or ethnicity. We calculated pooled odds ratios for HCC treatment using random effects models.

RESULTS

We identified 15 studies with 320,686 patients (65.8% White, 13.9% Black, 10.4% Asian, and 8.5% Hispanic). Overall, 33.2% of HCC patients underwent any treatment, and 22.7% underwent curative treatment. Compared with White patients, Black patients had lower odds of any treatment (OR 0.67, 95% CI 0.55-0.81) and curative treatment (OR 0.74, 95% CI 0.71-0.78). Similarly, Hispanic patients had lower pooled odds of curative treatment (OR 0.79, 95% CI 0.73-0.84).

CONCLUSIONS

There were significant racial and ethnic disparities in HCC treatment receipt, with Black patients having lower odds of receiving any and curative treatment while Hispanic patients having lower odds of curative treatment.

IMPACT

Racial and ethnic differences in treatment receipt serve as an intervention target to reduce disparities in HCC prognosis.

A Scoping Review of Possible Solutions for Decreasing Socioeconomic Inequalities in Type 2 Diabetes Mellitus

Background

As socioeconomic inequalities are key factors in access and utilization of type 2 diabetes (T2D) services, the purpose of this scoping review was to identify solutions for decreasing socioeconomic inequalities in T2D.

Methods

A scoping review of scientific articles from 2000 and later was conducted using PubMed, Web of Science (WOS), Scopus, Embase, and ProQuest databases. Using the Arksey and O'Malley framework for scoping review, articles were extracted, meticulously read, and thematically analyzed.

Results

A total of 7204 articles were identified from the reviewed databases. After removing duplicate and nonrelevant articles, 117 articles were finally included and analyzed. A number of solutions and passways were extracted from the final articles. Solutions for decreasing socioeconomic inequalities in T2D were categorized into 12 main solutions and 63 passways.

Conclusions

Applying identified solutions in diabetes policies and interventions would be recommended for decreasing socioeconomic inequalities in T2D. Also, the passways could be addressed as entry points to help better implementation of diabetic policies.

Machine Learning as a Tool for Early Detection: A Focus on Late-Stage Colorectal Cancer across Socioeconomic Spectrums

PURPOSE

To assess the efficacy of various machine learning (ML) algorithms in predicting late-stage colorectal cancer (CRC) diagnoses against the backdrop of socio-economic and regional healthcare disparities.

METHODS

An innovative theoretical framework was developed to integrate individual- and census tract-level social determinants of health (SDOH) with sociodemographic factors. A comparative analysis of the ML models was conducted using key performance metrics such as AUC-ROC to evaluate their predictive accuracy. Spatio-temporal analysis was used to identify disparities in late-stage CRC diagnosis probabilities.

RESULTS

Gradient boosting emerged as the superior model, with the top predictors for late-stage CRC diagnosis being anatomic site, year of diagnosis, age, proximity to superfund sites, and primary payer. Spatio-temporal clusters highlighted geographic areas with a statistically significant high probability of late-stage diagnoses, emphasizing the need for targeted healthcare interventions.

CONCLUSIONS

This research underlines the potential of ML in enhancing the prognostic predictions in oncology, particularly in CRC. The gradient boosting model, with its robust performance, holds promise for deployment in healthcare systems to aid early detection and formulate localized cancer prevention strategies. The study's methodology demonstrates a significant step toward utilizing AI in public health to mitigate disparities and improve cancer care outcomes.

Disparities in Late-Stage Breast and Colorectal Cancer Diagnosis Among Hispanic, Non-Hispanic White, and Non-Hispanic Black Patients: a Retrospective Cohort Study of Texas Medicare Beneficiaries

BACKGROUND

Disparities in late-stage breast or colorectal cancer diagnosis in younger populations are associated with social determinants of health (SDOH; education, poverty, housing, employment). We hypothesized that, in older Medicare beneficiaries, disparities in late-stage cancer diagnosis between Hispanic, non-Hispanic Black (NHB), and non-Hispanic White (NHW) patients would be associated with SDOH, comorbidities, and primary care physician (PCP) access.

METHODS

We analyzed 2005-2017 Texas Cancer Registry data linked with Medicare data for patients aged ≥ 66 (n = 86,501). Variables included age at diagnosis, sex, comorbidities, poverty level, education, PCP, and relevant cancer screening within 1 year.

RESULTS

For breast cancer in women (Hispanic, n = 6380; NHW, n = 39,225; NHB, n = 4055), a fully adjusted model showed significantly higher odds of late-stage cancer diagnosis only in NHB patients (odds ratio [OR] 1.11, 95% confidence interval [CI] 1.01-1.22) compared with NHW; adjustment for comorbidities and SDOH partially decreased the odds of late-stage diagnosis relative to NHWs. Interaction terms between race-ethnicity and poverty were not significant. For colorectal cancer, a fully adjusted multivariate model showed significantly higher odds of late-stage diagnosis only among NHBs (n = 3318, OR 1.29, 95% CI 1.19-1.40) relative to NHWs (n = 27,470); adjustment for SDOH partially decreased the odds of late-stage diagnosis in NHB patients. Interaction terms between race-ethnicity and poverty were not significant.

CONCLUSION

Racial disparities in late-stage breast and colorectal cancer diagnoses remain after adjustment for SDOH and clinically relevant factors, underscoring the need to optimize access to screening and timely cancer treatment in racial/ethnic minorities.