An epidemiologic analysis of cutaneous melanomas during 2018-2022: Results from a multicenter health maintenance organization in Northern California

Summary: Abstract Body: We aimed to characterize the effects of delayed diagnostics on melanoma stage within distinct demographic groups based on age, sex, and race/ethnicity; by comparing tumor (pT) stage and metastases before, during, and after lockdown periods of the COVID-19 pandemic. This retrospective study analyzed data from the Kaiser Permanente Northern California Regional Cancer Registry to assess cutaneous melanoma incidence trends from 2018 to 2022. For 20 distinct age-sex-race groups, and within each calendar year, we quantified the number and relative proportions of cutaneous melanomas by primary tumor stage (pT0, pT1a, etc.) and pathological stage (0, I, II, III, IV)- defined by regional and distant metastases. There were 14,139 melanomas diagnosed during the study period. Our preliminary analysis reveal no statistically significant differences in the age-adjusted invasive melanoma incidence rates for 2021 (42.7; 95% CI: 40.5–44.8) compared to 2018 (42.8; 95% CI: 40.6–44.9) and 2019 (42.5; 95% CI: 40.3–44.7), as evidenced by the overlapping 95% confidence intervals. In contrast, the age-adjusted incidence in 2022 was significantly higher at 47.6 (95% CI: 45.3–49.9). Within our age group subanalysis, those 75+ had an age-adjusted incidence of 17.3 (95% CI: 15.9-18.9) in 2022 compared to 14.2 (95% CI: 12.9-15.7) and 15.4 (95% CI: 14.1-16.9) in 2018 and 2019, respectively with distinct CIs. No other age groups demonstrated a significant difference in invasive melanoma incidence pre- and post-COVID19. Based on our preliminary results, there was an increase in invasive melanoma incidence in 2022 compared with the preceding four years, which may be driven by the 75+ group. This age group may have been disproportionately affected by disruptions in timely dermatological care during the pandemic. To further evaluate changes in melanoma incidence trends, we plan to estimate the annual percent change (APC) using a joinpoint regression model. Sanah Basrai¹, Peter Young³, Byron VanDyke² 1. aiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, United States. 2. Dermatology, Kaiser Permanente, Roseville, CA, United States. 3. Dermatology, Kaiser Permanente, Sacramento, CA, United States. Clinical Research: Epidemiology and Observational Research