Prior skin image datasets have not addressed patient-level information obtained from multiple skin lesions from the same patient.,Though artificial intelligence classification algorithms have achieved expert-level performance in controlled studies examining single images, in practice dermatologists base their judgment holistically from multiple lesions on the same patient.,The 2020 SIIM-ISIC Melanoma Classification challenge dataset described herein was constructed to address this discrepancy between prior challenges and clinical practice, providing for each image in the dataset an identifier allowing lesions from the same patient to be mapped to one another.,This patient-level contextual information is frequently used by clinicians to diagnose melanoma and is especially useful in ruling out false positives in patients with many atypical nevi.,The dataset represents 2,056 patients (20.8% with at least one melanoma, 79.2% with zero melanomas) from three continents with an average of 16 lesions per patient, consisting of 33,126 dermoscopic images and 584 (1.8%) histopathologically confirmed melanomas compared with benign melanoma mimickers.
We trained and validated risk prediction models for the three major types of skin cancer- basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma-on a cross-sectional and longitudinal dataset of 210,000 consented research participants who responded to an online survey covering personal and family history of skin cancer, skin susceptibility, and UV exposure.,We developed a primary disease risk score (DRS) that combined all 32 identified genetic and non-genetic risk factors.,Top percentile DRS was associated with an up to 13-fold increase (odds ratio per standard deviation increase >2.5) in the risk of developing skin cancer relative to the middle DRS percentile.,To derive lifetime risk trajectories for the three skin cancers, we developed a second and age independent disease score, called DRSA.,Using incident cases, we demonstrated that DRSA could be used in early detection programs for identifying high risk asymptotic individuals, and predicting when they are likely to develop skin cancer.,High DRSA scores were not only associated with earlier disease diagnosis (by up to 14 years), but also with more severe and recurrent forms of skin cancer.,Predicting who will develop skin cancer is difficult.,Here, the authors from 23andMe developed a polygenic risk score for skin cancer based on a questionnaire and genetic data from more than 210,000 individuals and suggest that the score could be used in early screening programmes.