The Future of Precision Prevention for Advanced Melanoma

Abstract

Precision prevention of advanced melanoma is fast becoming a realistic prospect, with personalized, holistic risk stratification allowing patients to be directed to an appropriate level of surveillance, ranging from skin self-examinations to regular total body photography with sequential digital dermoscopic imaging. This approach aims to address both underdiagnosis (a missed or delayed melanoma diagnosis) and overdiagnosis (the diagnosis and treatment of indolent lesions that would not have caused a problem). Holistic risk stratification considers several types of melanoma risk factors: clinical phenotype, comprehensive imaging-based phenotype, familial and polygenic risks. Artificial intelligence computer-aided diagnostics combines these risk factors to produce a personalized risk score, and can also assist in assessing the digital and molecular markers of individual lesions. However, to ensure uptake and efficient use of AI systems, researchers will need to carefully consider how best to incorporate privacy and standardization requirements, and above all address consumer trust concerns.

Artificial Intelligence in Dermatology: Challenges and Perspectives

“…This approach can potentially lead to trust issues from patients, particularly since the model gives a diagnostic output while being unable to explain the results. Physician interpretation is necessary to explain why a diagnosis or treatment should be chosen [ 50 , 51 ].…”

“…As ML has the capability of unlimited storage, the above data can be stored and analyzed in ML algorithms to provide a holistic predictive result. Lee et al gave a remarkable approach to precision prediction of MM [ 51 ]. They proposed a holistic risk stratification that can be produced from AI computer-aided diagnostics in order to provide the appropriate level of surveillance to patients depending on their risk factors.…”

“…Genotype, digital, and molecular markers from lesion assessment can all be combined to produce a personalized skin score. This approach aims to conserve early melanoma detection and improve surveillance for high-risk patients, while minimizing overdiagnosis [ 51 , 86 ].…”

In Vivo Melanoma Cell Morphology and Tumor Aggressiveness: The Promise of Reflectance Confocal Microscopy in Reducing Unnecessary Excisions

“…A decrease in indiscriminate screening, and the introduction of targeted, risk-adjusted screening for people at the highest risk of melanoma, is likely to be the most effective method of reducing overdiagnosis and unnecessary excisions (Lee et al, 2022;Welch et al, 2021). However, RCM screening for the melanoma types defined by Marconi et al (2022) may help to further reduce excisions in people who do require screening owing to elevated melanoma risk.…”

Communicating Personal Melanoma Polygenic Risk Information: Participants’ Experiences of Genetic Counseling in a Community-Based Study

“…There is a need to improve melanoma prevention and early detection, particularly through the better targeting of high-risk groups in the population [ 2 , 3 ]. Precision prevention strategies, including the use of multiple common genomic variants (combined as a polygenic risk score) to improve individual risk assessment and inform risk-specific prevention and early detection, are fast becoming realistic approaches to addressing this need [ 4 ].…”