As of 2021, non-Hispanic white people in the United States had the highest incidence rates of skin cancer among all races and ethnicities. Skin cancer is one of the most commonly occurring cancers in the world. Furthermore, the United States is among the countries with the highest rates of skin cancer worldwide. Skin cancer in the U.S. There are a few different types of skin cancer and some are more deadly than others. Basal and squamous skin cancers are more common and less dangerous than melanomas. Among U.S. residents, skin cancer has been demonstrated to be more prevalent among men than women. Skin cancer is also more prevalent among older adults. With treatment and early detection, skin cancers have a high survival rate. Fortunately, in recent years the U.S. has seen a reduction in the rate of death from melanoma. Skin cancer prevention Avoiding and protecting exposed skin from the sun (and other sources of UV light) is the primary means of preventing skin cancer. However, a survey of U.S. adults from 2024 found that around a third never used sunscreen.

Between the years 2012 and 2016, there were 372 invasive melanoma cases recorded in the Black population in the U.S. versus 1,725 such cases for Hispanics. The statistic illustrates the number of invasive melanoma cases in the U.S. between 2012 and 2016, by race/ethnicity.

From 2012 to 2016, there were around 237 annual deaths among Hispanics in the U.S. due to invasive melanoma. The statistic illustrates the average annual number of deaths attributed to invasive melanoma in the U.S. between 2012 and 2016, by race/ethnicity.

From 2012 to 2016, around 45,850 cases of invasive melanoma were recorded among males in the U.S. from all races, with around 42,826 cases among White, Non-Hispanic males. The statistic illustrates the number of invasive melanoma cases in U.S. males between 2012 and 2016, by race/ethnicity.

From 2012 to 2016, there were around 140 annual deaths among Hispanic males in the U.S. due to invasive melanoma. The statistic illustrates the average annual number of male deaths attributed to invasive melanoma in the U.S. between 2012 and 2016, by race/ethnicity.

This is historical data. The update frequency has been set to "Static Data" and is here for historic value. Updated 8/14/2024.

Definition of "All Cancer Sites": ICD-O-3 Topography (Site) Codes C00.0 – C80.9 with histology codes including all invasive cancers of all sites except basal and squamous cell skin cancers, and in situ cancer cases of the urinary bladder. Rates are per 100,000 population and are age-adjusted to 2000 U.S. standard population. Rates based on case counts of 1-15 are suppressed per DHMH/MCR Data Use Policy and Procedures.

From 2012 to 2016, around 31,845 cases of invasive melanoma were recorded among females in the U.S. from all races.The statistic illustrates the number of invasive melanoma cases in U.S. females between 2012 and 2016, by race/ethnicity.

The hypothesis was that disparities in time from diagnosis to definitive surgery (TTDS) exist between Asian groups. The National Cancer Database (2004-2020) was used to populate a sample of 1388 Asian patients with melanoma. Adjusting for sociodemographic factors with East Asian patients as the reference group, Southeast and South Asian melanoma patients had around 3 times the odds of a TTDS over 90 days.

Table 1. Categorization of Asian ethnicities into regional groups Table 2. Sample demographics Table 3. Adjusted odds ratios of multivariable analyses of melanoma treatment timeliness and sociodemographic associations

Definition of "All Cancer Sites": ICD-O-3 Topography (Site) Codes C00.0 – C80.9 with histology codes including all invasive cancers of all sites except basal and squamous cell skin cancers, and in situ cancer cases of the urinary bladder. Total includes cases reported as transexual, hermaphrodite, and unknown gender. Some cells are missing data due to suppression of low cell counts.

This dataset contains the summary data visualizations and clinical data of 65 samples from 36 Melanoma patients. Clinical data includes: Cancer Type, Number of Samples Per Patient, Mutation Count, Fraction Genome Altered, Race, Subtype, Mutation Burden, Purity, BRAF Mutation Status, CKIT Mutation Status, NRAS Mutation Status, Gender, Age, Best response, Administered treatment, Breslow Depth (mm). The plaintext components of the dataset can be downloaded as a tar file. The clinical data can be downloaded as a tsv file. The dataset includes copy-number segment data downloadable as .seg files and viewable via the Integrative Genomics Viewer.

In 2022, Australia had the fourth-highest total number of skin cancer cases worldwide and the highest age-standardized rate, with roughly 37 cases of skin cancer per 100,000 population. The graph illustrates the rate of skin cancer in the countries with the highest skin cancer rates worldwide in 2022.

ObjectiveFollowing the introduction of highly active antiretroviral therapy (HAART) the risk of AIDS-defining cancers decreased but incidence of many non-AIDS-defining cancers has reportedly increased in those with HIV/AIDS. Whether melanoma risk has also changed in HIV/AIDS patients post-HAART is unknown and therefore we evaluated this in comparison with the risk before HAART.DesignSystematic review and meta-analysis.MethodsWe searched Medline, Embase and ISI science citation index databases to April 2013. All cohort studies of patients diagnosed with HIV/AIDS that permitted quantitative assessment of the association with melanoma were eligible. Detailed quality assessment of eligible studies was conducted, focussing particularly on adjustment for ethnicity, a priori considered essential for an unbiased assessment of melanoma risk. Data were pooled using a random effects model.ResultsFrom 288 articles, we identified 21 that met the inclusion criteria, 13 presenting data for the post-HAART era and 8 for the pre-HAART era. Post-HAART the pooled relative risk (pRR) for the association between HIV/AIDS and melanoma was 1.26 (95% CI, 0.97–1.64) and 1.50 (95% CI 1.12–2.01) among studies that accounted for ethnicity, with evidence of significant heterogeneity (P = 0.004, I2 = 55.5). Pre-HAART pRRs were 1.26 (95% CI 1.11–1.43; Phet = 0.82) and 1.28 (95% CI 1.10–1.49) among studies adjusted for ethnicity.ConclusionsPeople with HIV/AIDS remain at a significantly increased risk of developing melanoma in the post-HAART era. White skinned people with HIV/AIDS should be screened regularly and counselled against excessive sun exposure.

BackgroundNon-metastatic breast cancer patients who had a medical history of skin or cervix cancers were presently eligible for clinical trials while few data were available regarding thyroid gland cancer. The study estimated the rate of prior thyroid gland cancer and evaluated its impact on survivals among breast cancer patients.MethodsNon-metastatic invasive breast cancer patients from the SEER database (SEER cohort) between 2010 and 2019 and Ruijin Hospital (Ruijin cohort) during 2009 and 2019 were retrospectively analyzed. Ascian or Pacific Island patients in the SEER cohort (SEER API cohort) were analyzed separately. Chi-square test and multivariate logistic regression analysis were performed to describe the clinical features. Kaplan-Meier analysis and Cox proportional hazards model were used to compare the overall survival (OS) and breast cancer specific survival (BCSS).ResultsA total of 136,441 patients from the SEER cohort, 17,183 from the SEER API cohort, and 8,079 from the Ruijin cohort were enrolled, of whom 0.68%, 0.81%, and 1.06% had a medical history of thyroid gland cancer, respectively. Patients with prior thyroid gland cancers were significantly older (51-60 years: OR 1.84, 95% CI 1.46-2.30, P < 0.001; 61-70 years: OR 2.00, 95% CI 1.61-2.50, P < 0.001; > 70 years: OR 1.51, 95% CI 1.18-1.92, P = 0.001) and more likely to be API (OR 1.23, 95% CI 1.03-1.48, P = 0.026) versus other races. Multivariate analysis demonstrated that patients with a history of thyroid gland cancer had comparable OS (SEER: HR 0.87, 95% CI 0.68-1.11, P = 0.257; SEER API: HR 0.53, 95% CI 0.22-1.28, P = 0.159; Ruijin: HR 1.07, 95% CI 0.26-4.29, P = 0.811) and BCSS (SEER: HR 0.72, 95% CI 0.49-1.08, P = 0.117; SEER API: HR ∞, 95% CI ∞-∞, P = 0.878; Ruijin: HR 0.70, 95% CI 0.10-4.98, P = 0.750) versus those without primary malignancies in the three cohorts.ConclusionThere were of a sizable of non-metastatic breast cancer patients with medical history of thyroid gland cancer, which was related with different races. Prior thyroid gland cancer had no adverse impact on clinical outcomes, indicating possible eligible in further clinical trials.

Supplementary Table I: Tumor and Mohs Micrographic Surgery in Hispanic Individuals Characterized by Fitzpatrick Skin Type

Supplementary Table II:Tumor and Mohs Micrographic Surgery Characteristics in 263 Cases Stratified by Race/Ethnicity Compared to NHW Individuals

Supplemental data accompany the following research letter: Keratinocyte carcinoma resected by Mohs micrographic surgery in individuals with skin of color: an observational study.

Onjona B. Hossain BS, Karolina Mieczkowska MD, Rithu Srikantha MD, Alexandra Rzepecki MD, David H. Ciocon MD, Dean Hosgood PhD, Ramone F. Williams MD, MPhil

Data by medical encounter for the following conditions by age, race/ethnicity, and gender:

Acute Myocardial Infarction (AMI) Asthma Bladder Cancer Brain Cancer Coronary Heart Disease (CHD) Colorectal Cancer Chronic Obstructive Pulmonary Disease (COPD)/Chronic Lower Respiratory Diseases Diabetes Female Breast Cancer Female Reproductive Cancer Heart Failure Hyperlipidemia (High Blood Cholesterol) Kidney Cancer Leukemia Liver Cancer Lung Cancer Lupus and Connective Tissue Disorders Melanoma of the Skin Non-Hodgkin's Lymphoma Non-melanoma Skin Cancer Overall Cancer Overall Heart Disease Overall Hypertensive Diseases Pancreatic Cancer Prostate Cancer Stroke Thyroid Cancer

Rates per 100,000 population. Age-adjusted rates per 100,000 2000 US standard population.
Blank Cells: Rates not calculated for fewer than 11 events. Rates not calculated in cases where zip code is unknown. Geography not reported where there are no cases reported in a given year. SES: Is the median household income by SRA community. Data for SRAs only.

Data sources: California Department of Public Health, Center for Health Statistics, Office of Health Information and Research, Vital Records Business Intelligence System (VRBIS), 2021. California Department of Health Care Access and Information (HCAI), Emergency Department Discharge Database and Patient Discharge Database, 2021. SANDAG Population Estimates, 2021 (vintage: 09/2022). Population estimates were derived using the 2010 Census and data should be considered preliminary. Prepared by: County of San Diego, Health and Human Services Agency, Public Health Services, Community Health Statistics Unit, March 2023.

2021 Community Profile Data Guide and Data Dictionary Dashboard: https://public.tableau.com/app/profile/chsu/viz/2021CommunityProfilesDataGuideandDataDictionaryDashboards_16802003011430/HomePage

Supplementary Table 4: Multivariable Analysis of Specialty Clinics and Association with No-Shows. These separate multivariable regression analyses split the patient appointments into specialty clinics such as alopecia, melanoma, patch testing, high risk skin cancer, etc. When stratified by specialty clinics, most patient characteristics were not significantly associated with no-shows, though being of Black race was significantly associated with no-shows in virtual, high-risk skin cancer (HRSC), injection, and urgent visits (P<.01). Having public insurance was significantly associated with higher odds of no-show in HRSC, patch testing, and urgent visits (P<.02).

aOne or more of the following conditions was reported at study entry: prevalent cancer (except non melanoma skin), heart disease, stroke, respiratory disease (chronic bronchitis, emphysema, asthma), currently sick, or weight loss of ≥10 lbs. in past year.bRate per 100,000 standardized to the age-distribution of the CPS-II women.cCox proportional hazards model, adjusted for age, race, education, physical activity, alcohol use, marital status, aspirin use, fat consumption, vegetable consumption, and postmenopausal estrogen usedNone of the conditions listed in footnote(a) were reported.Relative risks of death from any cause among women according to BMI, smoking, prevalent disease status and race, CPS-II 1982–2010.

BackgroundMelanoma is the fourth leading cause of cancer-related death worldwide. The continuous exploration and reporting of risk factors of melanoma is important for standardizing and reducing the incidence of the disease. Calcium signaling is a promising therapeutic target for melanoma; however, the relationship between total serum calcium levels and melanoma development remains unclear.MethodsIn this study, we included patients with melanoma from the National Health and Nutrition Examination Survey (NHANES) database from 2003 to 2006 and from 2009 to 2016. The baseline clinical characteristics of the participants were analyzed using the chi-square and rank-sum tests. Subsequently, a fitted model was constructed to evaluate the relationship between total serum calcium levels and melanoma development. The performance of total serum calcium levels and covariates in predicting the risk of melanoma was assessed based on ROC curves. Finally, LASSO regression analysis was performed using the “glmnet” R package to identify clinical characteristics associated with melanoma.ResultsA total of 13,432 participants were included in this study. Age, race, household poverty-to-income ratio, response of the skin to sunlight after a certain period of non-exposure, wearing long-sleeved shirts, frequency of sunscreen use, and arthritis were significantly correlated with the development of melanoma. The p-values of total serum calcium levels in three fitted models were 

aOne or more of the following conditions was reported at study entry: prevalent cancer (except non melanoma skin), heart disease, stroke, respiratory disease (chronic bronchitis, emphysema, asthma), currently sick, or weight loss of ≥10 lbs. in past year.bRate per 100,000 standardized to the age-distribution of the CPS-II men.cCox proportional hazards model, adjusted for age, race, education, physical activity, alcohol use, marital status, aspirin use, fat consumption, and vegetable consumptiondNone of the conditions listed in footnote(a) were reported.Rates and relative risks of death from any cause among men according to BMI, smoking, prevalent disease status and race, CPS-II 1982-2010.

Characteristic of 38 and 24 studies included in the meta-analysis of HIF1A 1772 C/T and 1790 G/A polymorphisms, respectively.