Author Interviews, Cancer Research, Environmental Risks, Melanoma / 19.02.2020
Which States Have Most Ultraviolet-Related Melanomas?
MedicalResearch.com Interview with:
Farhad Islami, MD PhD
Scientific Director, Surveillance Research
American Cancer Society, Inc
MedicalResearch.com: What is the background for this study?
Response: Many cases of cutaneous melanoma (melanoma) in the United States have been attributed to ultraviolet (UV) radiation, but there was little information on the state-by-state burden of melanoma due to UV exposure. We estimated numbers, proportions and age-standardized incidence rates of malignant melanomas attributable to UV radiation in each US state by calculating the difference between observed melanomas during 2011–2015 and expected cases based on rates in a population with theoretically minimum UV exposure.
As there is no population completely unexposed to UV radiation, the reference rates we used were historical melanoma incidence rates in Connecticut during 1942–1954, when the melanoma burden was low. For most adults, melanomas diagnosed in that period likely reflected UV exposure accumulated in the 1930s or earlier, when exposure was minimized by clothing style and limited recreational exposure.
We estimated that 338,701 melanoma cases (91.0% of total, 372,335) in the United States during 2011–2015 were attributable to UV exposure; 94.3% of all these UV-attributable cases (or 319,412 cases) occurred in non-Hispanic whites. UV-attributable melanoma incidence rates and cases were higher among males than females, but attributable rates and cases in ages <45 years were higher among females. (more…)
Dr. Helen Marsden PhD
Skin Analytics Limited
London, United Kingdom
MedicalResearch.com: What is the background for this study?
Response: In this technology age, with the explosion of interest and applications using Artificial Intelligence, it is easy to accept the output of a technology-based test - such as a smartphone app designed to identify skin cancer - without thinking too much about it. In reality, technology is only as good as the way it has been developed, tested and validated. In particular, AI algorithms are prone to a lack of “generalisation” - i.e. their performance drops when presented with data it has not seen before. In the medical field, and particularly in areas where AI is being developed to direct a patient’s diagnosis or care, this is particularly problematic. Inappropriate diagnosis or advice to patients can lead to false reassurance, heightened concern and pressure on NHS services, or worse. It is concerning, therefore, that there are a large number of smartphone apps available that provide an assessment of skin lesions, including some that provide an estimate of the probability of malignancy, that have not been assessed for diagnostic accuracy.
Skin Analytics has developed an AI-based algorithm, named: Deep Ensemble for Recognition of Malignancy (DERM), for use as a decision support tool for healthcare providers. DERM determines the likelihood of skin cancer from dermoscopic images of skin lesions. It was developed using deep learning techniques that identify and assess features of these lesions which are associated with melanoma, using over 7,000 archived dermoscopic images. Using these images, it was shown to identify melanoma with similar accuracy to specialist physicians. However, to prove the algorithm could be used in a real life clinical setting, Skin Analytics set out to conduct a clinical validation study.

