Late-Stage Melanoma in New York State: Associations with Socioeconomic Factors and Healthcare Access at the County Level

Socioeconomic disparity in the natural history of cutaneous melanoma: evidence from two large prospective cohorts

BACKGROUND

Previous studies on the associations between socioeconomic status (SES) and cutaneous malignant melanoma (CMM) failed to distinguish the effects of different SES factors under an individual-data-based prospective study design.

METHODS

Based on UK Biobank (UKB) and China Kadoorie Biobank (CKB), we estimated the effects of four SES factors on transitions from baseline to CMM in situ, subsequently to invasive CMM and further CMM mortality by applying multistate models. We further explored to which extent the associations between SES and CMM incidence could be explained by potential mediators including sun exposure, lifestyle and ageing in UKB.

RESULTS

In multistate analyses, good household income was independently associated with an increased risk of CMM in situ (HR=1.38, 95% CI: 1.21 to 1.58) and invasive CMM (HR=1.34, 95% CI: 1.22 to 1.48) in UKB. These findings were partly validated in CKB. Especially in UKB, we observed an increased risk of CMM in situ and invasive CMM among participants with good type of house; only good education was independently associated with lower risk of evolving to invasive CMM among patients with CMM in situ (HR=0.69, 95% CI: 0.52 to 0.92); only good household income was independently associated with lower risk of CMM mortality among patients with CMM (HR=0.65, 95% CI: 0.45 to 0.95). In mediation analysis, the proportions attributable to the mediating effect were <6% for all selected variables, including self-reported sun exposure-related factors.

CONCLUSION

SES factors have different effects on the incidence and progression of CMM. The association between SES and incident CMM is neither causal nor well explained by selected mediators.

Association of rurality and health professional shortages with the clinicopathologic characteristics of melanoma in North Carolina

PURPOSE

To assess rural-urban and health professional shortage area (HPSA)-related influences on the characteristics of melanoma in North Carolina.

METHODS

We conducted a single-center retrospective cohort study of patients living in North Carolina with an available pathology report for invasive cutaneous melanoma seen in the Duke University Health System from 01/01/2014 to 12/31/2020. Multivariable logistic regression models were employed to compare patient and tumor characteristics between rural versus urban county residence as well between melanoma thicknesses dichotomized into thin (≤1.0 mm) and thicker (>1.0 mm) tumors.

FINDINGS

The cohort included 807 patients, and rural patients accounted for 177 (21.9%) of invasive cutaneous melanomas. Rural patients had significantly higher odds of having thicker tumors than urban patients (odds ratio [OR] = 1.78, 95% confidence interval [CI]: 1.17-2.71; P = .008). Rural patients were significantly more likely to be female (OR = 1.59, 95% CI: 1.10-2.28; P = .013) and located in a population-based (OR = 2.66, 95% CI: 1.84-3.84; P<.001) or geographic-based (OR = 8.21, 95% CI: 3.33-20.22; P<.001) HPSA. Living in a medium- or high-shortage population-based HPSA was associated with higher odds of thicker tumors (OR = 2.65, 95% CI: 1.85-3.80; P<.001).

CONCLUSIONS

Patients living in rural North Carolina counties were more likely than those in urban counties to be diagnosed with melanomas >1.0 mm in thickness, a clinically significant difference with important prognostic implications. Interventions at the county- and state-level to address this disparity may include improving access to skin cancer screening and teledermatology programs, increasing partnerships with primary care providers, and targeting interventions to counties with health professional shortages.

Persistent poverty and incidence-based melanoma mortality in Texas

PURPOSE

Previous studies have shown that individuals living in areas with persistent poverty (PP) experience worse cancer outcomes compared to those living in areas with transient or no persistent poverty (nPP). The association between PP and melanoma outcomes remains unexplored. We hypothesized that melanoma patients living in PP counties (defined as counties with ≥ 20% of residents living at or below the federal poverty level for the past two decennial censuses) would exhibit higher rates of incidence-based melanoma mortality (IMM).

METHODS

We used Texas Cancer Registry data to identify the patients diagnosed with invasive melanoma or melanoma in situ (stages 0 through 4) between 2000 and 2018 (n = 82,458). Each patient's PP status was determined by their county of residence at the time of diagnosis.

RESULTS

After adjusting for demographic variables, logistic regression analyses revealed that melanoma patients in PP counties had statistically significant higher IMM compared to those in nPP counties (17.4% versus 11.3%) with an adjusted odds ratio of 1.35 (95% CI 1.25-1.47).

CONCLUSION

These findings highlight the relationship between persistent poverty and incidence-based melanoma mortality rates, revealing that melanoma patients residing in counties with persistent poverty have higher melanoma-specific mortality compared to those residing in counties with transient or no poverty. This study further emphasizes the importance of considering area-specific socioeconomic characteristics when implementing place-based interventions to facilitate early melanoma diagnosis and improve melanoma treatment outcomes.

Analyzing County-level Social Vulnerabilities of Head and Neck Melanomas in the United States

OBJECTIVES

Studies addressing social determinants of health (SDH) in head-neck melanomas (HNM) have only assessed incidence with increasing socioeconomic status. None have investigated a wider scope of SDH or their summed influence on affecting HNM prognosis and follow-up care.

METHODS

This retrospective cohort study analyzed 374,138 HNM in adults from 1975 to 2017 from the NCI-Surveillance, Epidemiology, and End Results Program (NCI-SEER) database. Utilizing the NCI-SEER database, Social Vulnerability Index (SVI) scores were matched to county of residence upon diagnosis. Univariate linear regressions were performed on length of care (months of follow-up/surveyed) and prognosis (months survival) across various SDH/SVI scores of socioeconomic status, minority and language status, household composition, housing and transportation, and their total composite.

RESULTS

With increasing overall SVI score, which indicates increasing social vulnerability, months of follow-up showed significant decreases ranging from 0.04% to 27.63% compared with the lowest vulnerability groups, with the highest differences in nodular melanomas and the lowest with malignant melanomas in giant pigmented nevi. Similarly, months survival significant decreases ranged from 0.19% to 39.84% compared with the lowest SVI scores, with the highest difference in epithelioid cell melanomas and the lowest in amelanotic melanoma. Comprising this overall score trend, decreases with socioeconomic status, minority-language status, household composition, and housing-transportation contributed differentially per histology subtype.

CONCLUSIONS

Our data highlight significant negative trends in HNM prognosis and care with higher total social vulnerability while showing which SDH-themes quantifiably contribute more to these differences.

LEVEL OF EVIDENCE

3 Laryngoscope, 134:185-190, 2024.

Melanoma awareness and prevention among latinx and non-latinx white adults in urban and rural California: A qualitative exploration

BACKGROUND

Melanoma mortality rates in the US are highest among older men, individuals of lower socioeconomic status (SES), and people of color. To better understand these inequities, a qualitative exploratory study was conducted in Northern and Southern California to generate knowledge about barriers and facilitators of awareness, prevention, and early detection of melanoma in lower SES Latinx and non-Latinx White (NLW) individuals living in urban and semi-rural areas.

METHODS

Nineteen focus groups were conducted (N = 176 adult participants), stratified by race/ethnicity (Latinx, low-income NLW), geography (semi-rural, urban), and language (English and Spanish). Inductive and deductive thematic analysis was conducted, and the findings were organized using the socioecological model framework: individual, interpersonal, community, and health system/policy levels.

RESULTS

Four socioecological themes describe how key factors affect knowledge, perceived risk, preventive behaviors, and melanoma screening. Individual level findings revealed that many participants were not familiar with melanoma, yet were willing to learn through trusted sources. Having brown or darker skin tone was perceived as being associated with lower risk for skin cancer. Interpersonally, social relationships were important influences for skin cancer prevention practice. However, for several Latinx and semi-rural participants, conversations about melanoma prevention did not occur with family and peers. At the community level, semi-rural participants reported distance or lack of transportation to a clinic as challenges for accessing dermatology care. Healthcare systems barriers included burdens of additional healthcare costs for dermatology visits and obtaining referral.

CONCLUSIONS

Varying factors influence the awareness levels, beliefs, and behaviors associated with knowledge, prevention, and early detection of melanoma among low-income Latinx and NLW individuals and in semi-rural areas. Results have implications for health education interventions. Navigation strategies that target individuals, families, and health care settings can promote improved prevention and early detection of melanoma in these communities.

Geospatial analysis of patients' social determinants of health for health systems science and disparity research

Social context matters for health, healthcare processes/quality and patient outcomes. The social status and circumstances we are born into, grow up in and live under, are called social determinants of health; they drive our health, and how we access and experience care; they are the fundamental causes of disease outcomes. Such circumstances are influenced heavily by our location through neighborhood context, which relates to support networks. Geography can influence proximity to resources and is an important dimension of social determinants of health, which also encompass race/ethnicity, language, health literacy, gender identity, social capital, wealth and income. Beginning with an explanation of social determinants, we explore the use of Geospatial Analysis methods and geocoding, including the importance of collaborating with geography experts, the pitfalls of geocoding, and how geographic analysis can help us to understand patient populations within the context of Social Determinants of Health. We then explain mechanisms and methods of geospatial analysis with two examples: (1) Bayesian hierarchical regression with crossed random effects and (2) discontinuity regression i.e., change point analysis. We leveraged the local University of Utah and Yale cohorts of the Multicenter Perioperative Outcomes Group (MPOG.org ), a perioperative electronic health registry; we enriched the Utah cohort with US-census tract level social determinants of health after geocoding patient addresses and extracting social determinants of health from the National Neighborhood Database (NaNDA). We explain how to investigate the impact of US-census tract level community deprivation indices and racial/ethnic composition on (1) individual clinicians’ administration of risk-adjusted perioperative antiemetic prophylaxis, (2) patients’ decisions to defer cataract surgery at the cusp of Medicare eligibility and finally (3) methods to further characterize patient populations at risk through publicly available datasets in the context of public transit access. Our examples are not rigorous analyses, and our preliminary inferences should not be taken at face value, but rather seen as illustration of geospatial analysis processes and methods. Our worked examples show the potential utility of geospatial analysis, and in particular the power of geocoding patient addresses to extract US-census level social determinants of health from publicly available databases to enrich electronic health registries for healthcare disparity research and targeted health system level countermeasures.

Racial Differences in Perceived Risk and Sunscreen Usage

Background Although White individuals have higher incidence of melanoma, clinical outcomes are worse among patients with skin of color. This disparity arises from delayed diagnoses and treatment that are largely due to clinical and sociodemographic factors. Investigating this discrepancy is crucial to decrease melanoma-related mortality rates in minority communities. A survey was used to investigate the presence of racial disparities in perceived sun exposure risks and behaviors. Methods A survey consisting of 16 questions was deployed via social media to assess skin health knowledge. Over 350 responses were recorded, and the extracted data were analyzed using statistical software. Results Of the respondents, White patients were significantly more likely to have higher perceived risk of developing skin cancer, highest levels of sunscreen usage, and higher reported frequency of skin checks performed by primary care providers (PCPs). There was no difference between racial groups in the amount of education provided by PCPs related to sun exposure risks. Conclusion The survey findings suggest inadequate dermatologic health literacy as a result of other factors such as public health and sunscreen product marketing rather than as a consequence of inadequate dermatologic education provided in healthcare settings. Factors such as racial stereotypes in communities, implicit biases in marketing companies, and public health campaigns should be considered. Further studies should be conducted to determine these biases and improve education in communities of color.

Shedding Light on Disparities in Melanoma Care

The article by Shah et al. (2021) published in the Journal of Investigative Dermatology adds to the growing body of literature on disparities in melanoma care. The authors report that whereas melanoma is more common in the New York state's counties with higher socioeconomic status (SES) and increased health-system access (HSA), counties with lower SES and decreased HSA have a relatively increased proportion of late-stage melanoma diagnoses. Increased understanding of the individual- and community-level factors contributing to adverse melanoma outcomes in certain populations is necessary to strategize targeted solutions.