The Role of Antidiabetic Drugs in Cutaneous Malignancies: An Evidence-Based Review (++)

The Role of Antidiabetic Drugs in Cutaneous Malignancies: An Evidence-Based Review Seanna Yang, MD; Nickoulet Babaei, MD; Dahyeon Kim, MD; Mireya Cervantes, MD; Minka Gill, MD; Jashin J. Wu, MD https://www.medscape.com/viewarticle/role-antidiabetic-drugs-cutaneous-malignancies-evidence-2026a100106u?ecd=wnl_edit_tpal_etid8756480&uac=148436CN&impID=8756480 Skin cancer is one of the more prevalent malignancies in patients with type 2 diabetes, and shared risk factors may increase susceptibility to both diseases. Antidiabetic medications may have potential roles in reducing the risk for cutaneous malignancies, while emerging evidence suggests possible therapeutic applications that warrant further investigation. We reviewed the association between type 2 diabetes and skin cancer and examined the potential effects of antidiabetic medications on cutaneous malignancies. A nonsystematic literature search was conducted, with supporting articles included for additional context. Current evidence suggests that metformin and thiazolidinediones may have chemopreventive and potential therapeutic effects in skin cancers, whereas the effects of other antidiabetic medications are less well studied. Certain agents also show potential as monotherapy or adjunctive therapy to standard cancer treatments. Further research is needed to determine whether antidiabetic medications can prevent or treat skin cancer in patients with type 2 diabetes. From Convolutional Neural Networks to Foundation Models: A New Era for Artificial Intelligence in Dermatology Rhea Singh, MD; Shari R. Lipner, MD, PhD https://www.medscape.com/viewarticle/convolutional-neural-networks-foundation-models-new-era-2026a100106y?ecd=wnl_edit_tpal_etid8756480&uac=148436CN&impID=8756480 The role that artificial intelligence (AI) should play in dermatology and what it means for dermatologists have transitioned from hypothetical questions to serious clinical issues.[1,2,3,4] Consider a 36-year-old woman with Fitzpatrick skin type IV who presents to her primary care provider with a slowly enlarging pigmented lesion with features that raise the physician’s concern for malignancy. During the clinical evaluation, an AI-based image analysis tool integrated into the electronic medical record analyzes a photograph of the lesion and independently flags it as high risk, supporting the clinician’s concern. The patient then is referred to dermatology, histopathology confirms invasive melanoma, and now the patient has a diagnosis.