Examining Demographic, Geographic, and Temporal Patterns of Melanoma Incidence in Texas From 2000 to 2018: Retrospective Study

Abstract

Background: Melanoma currently ranks as the fifth leading cancer diagnosis and is projected to become the second most common cancer in the United States by 2040. Melanoma detected at earlier stages may be treated with less-risky and less-costly therapeutic options.

Objective: This study aims to analyze temporal and spatial trends in melanoma incidence by stage at diagnosis (overall, early, and late) in Texas from 2000 to 2018, focusing on demographic and geographic variations to identify high-risk populations and regions for targeted prevention efforts.

Methods: We used melanoma incidence data from all 254 Texas counties from the Texas Cancer Registry (TCR) from 2000 to 2018, aggregated by county and year. Among these, 250 counties reported melanoma cases during the period. Counties with no cases reported in a certain year were treated as having no cases. Melanoma cases were classified by SEER Summary Stage and stratified by the following four key covariates: age, sex, race and ethnicity, and stage at diagnosis. Incidence rates (IRs) were calculated per 100,000 population, and temporal trends were analyzed using joinpoint regression to determine average annual percentage changes (AAPCs) with 95% CIs for the whole time period (2000-2018), the most recent 10-year period (2009-2018), and the most recent 5-year period (2014-2018). Heat map visualizations were developed to assess temporal trends by patient age, year of diagnosis, stage at diagnosis, sex, and race and ethnicity. Spatial cluster analysis was conducted using Getis-Ord Gi* statistics to identify county-level geographic clusters of high and low melanoma incidence by stage at diagnosis.

Results: A total of 82,462 melanoma cases were recorded, of which 74.7% (n=61,588) were early stage, 11.3% (n=9,352) were late stage, and 14% (n=11,522) were of unknown stage. Most cases were identified as males and non-Hispanic White individuals. Melanoma IRs increased from 2000 to 2018, particularly among older adults (60+ years; AAPC range 1.20%-1.84%; all P values were <.001), males (AAPC 1.59%; P<.001), and non-Hispanic White individuals (AAPC of 3.24% for early stage and 2.38% for late stage; P<.001 for early stage and P = .03 for late state). Early-stage diagnoses increased while the rates of late-stage diagnoses remained stable for the overall population. The spatial analysis showed that urban areas had higher early-stage incidence rates (P=.06), whereas rural areas showed higher late-stage incidence rates (P=.05), indicating possible geographic-based differences in access to dermatologic care.

Conclusions: Melanoma incidence in Texas increased over the study time period, with the most-at-risk populations being non-Hispanic White individuals, males, and individuals aged 50 years and older. The stable rates of late-stage melanoma among racial and ethnic minority populations and rural populations highlight potential differences in access to diagnostic care. Future prevention efforts may benefit from increasing access to dermatologic care in areas with higher rates of late-stage melanoma at diagnosis.

Keywords: demographic variation; geographic disparity; geospatial analysis; joinpoint regression; melanoma incidence; melanoma screening; stage at diagnosis; temporal trend analysis.

Figure 1.. Temporal heat maps presenting melanoma incidence rates (per 100,000 population) by columns of overall population, sex, and racial and ethnicity groups. Each row panel shows a different stage at diagnosis: all cases, early stage, late stage, and unknown stage. Numbers in the lower left corner of each panel indicate the total number of melanoma cases in Texas from 2000 to 2018.

Figure 2.. Spatial cluster analysis of melanoma incidence rates (cases per 100,000 population) by melanoma stage at diagnosis (all cases, early stage, and late stage) and selected years from 2000 to 2018 using Gi* statistics. Classifications were defined as follows: very high (Gi*>0 and P<.01), high (Gi*>0 and 0.01 ≤ P<.05), somewhat high (Gi*>0 and 0.05 ≤ P<.10), insignificant (P>.10), and low (Gi*<0 and P<.10). Red-shaded areas represent high-incidence clusters, depicting clusters of counties with significantly higher incidence rates compared with the statewide average incidence rate. Blue-shaded areas highlight clusters of counties with significantly lower incidence rates compared with the state average.

Figure 3.. Spatial clusters of melanoma incidence rates overlaid with (A) rural counties and (B) persistent poverty counties in 2018. Classifications were based on Gi* statistics as follows: very high (Gi*>0 and P<.01), high (Gi*>0and 0.01 ≤ P<.05), somewhat high (Gi*>0 and 0.05 ≤ P<.10), insignificant (P>.10), and low (Gi*<0 and P<.10).