Abstract
Introduction Merkel cell carcinoma is an aggressive neuroendocrine tumor that is related to immunosuppression and the Merkel cell polyomavirus. It is more common on the head and neck and has been associated with other skin malignancies such as basal cell carcinoma, squamous cell carcinoma, and melanoma. However, there has never been a nationwide investigation that quantifies Merkel cell carcinoma's connection with these subgroups. Methods Utilizing the National Institutes of Health's All of Us open-access database, a retrospective study was conducted by filtering for Merkel cell carcinoma through the International Classification of Diseases, 9th and 10th Clinical Modification codes 209.* and C4A.*, respectively. This led to the inclusion of 41 patients in the study, with each instance compared to four control patients without merkel cell carcinoma, matched by age, race, and gender. The data's demographics and skin cancer co-morbidities were collected and evaluated with odds ratios and 95% confidence intervals using Wald's method. Results In patients with merkel cell carcinoma, a statistically significant gradient of increasing risk for developing basal cell carcinoma (Odds Ratio, 11.63; 95% Confidence Interval, 4.30-31.45; P < 0.0001), squamous cell carcinoma (Odds Ratio, 15.09; 95% Confidence Interval, 3.87-58.84; P = 0.0001), and melanoma (Odds Ratio, 27.94; 95% Confidence Interval, 3.26-239.48; P = 0.0024) was observed. The race/ethnicity demographics showed that 85.4% of the patients were white, and they were at the highest risk of developing merkel cell carcinoma. However, the study has limitations, such as the inability to identify the stage of merkel cell carcinoma among patients and the lack of consideration for other confounding variables. Conclusion The study examines the link between merkel cell carcinoma and other skin malignancies, underscoring the need for more national research to better understand the underlying causes that contribute to this link. The findings also indicate the possibility of sample bias in the All of Us database, emphasizing the need to assess the patient population's representativeness in such investigations.