Disparities in melanoma outcomes in urban versus rural settings: An analysis from the Nebraska cancer registry 2001-2016.
Journal of the American Academy of Dermatology(2023)
摘要
To the Editor: Melanoma accounts for 1% of skin cancers, however, it causes about 75% of skin cancer deaths. Geographical location may have a major impact on access to care, education, and prognosis.1Zafar F.S. Abid R. Ginader T. Powers J.G. Rural health disparities in melanoma staging and prognostic outcomes in Iowa.J Am Acad Dermatol. 2021; 84: 1727-1730https://doi.org/10.1016/j.jaad.2020.08.092Abstract Full Text Full Text PDF PubMed Scopus (5) Google Scholar In rural areas of the United States such as Nebraska, incidence of melanoma and characteristics of the disease should be addressed. In Nebraska, melanoma cases have increased from 15.2 cases per 100,000 in 2001 to 25.6 cases per 100,000 in 2015.2C CD. U.S. Cancer Statistics Data Visualizations Tool, based on 2020 submission data (1999-2018): U.S. Department of Health and Human Services. Institute C for DC and P and NC, ed, 2018. Accessed October 16, 2021. https://gis.cdc.gov/Cancer/USCS/#/AtAGlance/Google Scholar With about one-third of Nebraska living in rural areas, this can have a major impact on access to care and early diagnosis.3Rural Helath Information Hub, 2019. Accessed September 13, 2021. https://www.ruralhealthinfo.org/states/nebraskaGoogle Scholar The purpose of this study is to determine how rural versus urban areas in Nebraska are affected by melanoma. All cases for melanoma were obtained from the Nebraska Cancer Registry for the years 2001-2016. Data obtained included the patient's address, race, gender, date of diagnosis, primary site of the cancer, stage of disease at diagnosis, and histological subtype. For mortality data, the patient's information was gathered from death certificates that are on file with the Department of Health and Human Services. The difference of distribution between rural and urban groups was evaluated using the Chi-square test for categorical variables and t test for continuous variables. Univariate and multivariate logistic regression models were developed to determine the odds ratio of death for each of these risk factors. We excluded 7 observations with missing rural/urban information. The distribution of gender, site (ie, trunk/limb, head/neck, unspecified), stage, vital status mean, and standard deviation of age were calculated for rural and urban groups separately. We received data from 9688 individuals living in Nebraska and diagnosed with melanoma. Of those, 62% lived in urban areas and 38% lived in rural areas. The most affected site was trunk and limb followed by head/neck for both urban and rural areas (Table I). When adjusting for gender, age, race, stage of disease, and site, the odds ratio of death comparing those living in rural versus urban area was estimated to be 1.48 (95% CI 1.35-1.63, P = .0001) (Table II). Males living in rural areas had a significantly higher odds of death from melanoma compared to those living in urban areas, with an odds ratio of 2.13 (95% CI 1.93-2.36, P ≤ .0001) (Table II). The comparison of death rates between males and females living in rural versus urban areas can be seen in Supplementary Fig 1, available via Mendeley at https://doi.org/10.17632/gr4d72hj2j.1.Table IDistribution of participant characteristics stratified by living areas (rural vs urban in Nebraska)CharacteristicsUrban (N = 6005, 62.0)Rural (N = 3683, 38.0%)P valueN (%)N (%)Variable Gender.03Female2779 (46.3)1619 (44)Male3226 (53.7)2064 (56) Race.01Black10 (0.2)1 (0)Other20 (0.3)6 (0.2)Unknown648 (10.8)348 (9.4)White5327 (88.7)3328 (90.4) Status<.0001Alive4772 (79.5)2664 (72.3)Dead1233 (20.5)1019 (27.7) Stage.03Distant147 (2.4)116 (3.1)Local2062 (34.3)1177 (32)Regional2870 (47.8)1812 (49.2)Unknown/unstaged926 (15.4)578 (15.7) Site<.0001Head/neck1627 (27.1)1231 (33.4)Not specified173 (2.9)150 (4.1)Trunk/limb4205 (70)2302 (62.5)MeanSDMeanSDAge59.216.863.116.7<.0001 Age among male63.115.165.814.8<.0001 Age among female54.617.559.818.2<.0001 Open table in a new tab Table IIUnadjusted (univariate) and adjusted (multivariate) odds ratio of death among participant characteristics in NebraskaVariableUnadjustedAdjustedOR (95% CI)P valueOR (95% CI)P valueRural1.17 (1.05-1.31).0061.48 (1.35-1.63).0005Male1.55 (1.37-1.74).00052.13 (1.93-2.36).0005Age1.08 (1.07-1.08).00051.07 (1.07-1.08).0005Race WhiteRef Black2.82 (0.70-11.30).141.68 (0.49-5.73).41 Other1.68 (0.60-4.71).32441.08 (0.45-2.57).8615 Unknown0.19 (0.14-0.27).0050.12 (0.09-0.17).005Stage LocalRef Distant11.79 (7.99-17.40).000518.21 (13.34-24.85).0005 Regional2.17 (1.91-2.47).00051.69 (1.51-1.89).0005 Unknown/unstaged0.82 (0.68-0.99).0431.05 (0.89-1.23).560Site Trunk/limbRef Head/neck1.18 (1.04-1.33)8.62E-031.94 (1.75-2.15).0005 Not specified8.47 (6.03-11.89).000514.48 (11.13-18.83).0005CI, Confidence interval; OR, odds ratio. Open table in a new tab CI, Confidence interval; OR, odds ratio. Efforts to increase dermatology in rural areas have continued to rise but there are still ways to improve. In Nebraska, only 5 out of the 93 counties had dermatologists in 2016 and only 43 dermatologists were available in the entire state.3Rural Helath Information Hub, 2019. Accessed September 13, 2021. https://www.ruralhealthinfo.org/states/nebraskaGoogle Scholar With the limited access to a dermatologist, many individuals rely on their primary care physicians to make an appropriate diagnosis. Expanding the utilization of teledermatology in rural settings can increase early diagnosis, improve patient outcomes, and limit costs.4Chuchu N. Dinnes J. Takwoingi Y. et al.Teledermatology for diagnosing skin cancer in adults.Cochrane Database Syst Rev. 2018; 2018https://doi.org/10.1002/14651858.cd013193Crossref Google Scholar Although teledermatology is promising, increasing dermatologists in these rural areas will continue to limit health disparities and improve patient outcomes. Ashely Wysong is the recipient of the Institutional Research Grant for Castle Biosciences. Elizabeth M. Mata, Natalia Trinidad, Elliot Blue, Marissa Lobl, Dillon Clarey, and Cheng Zheng have no conflicts of interest to declare.
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