Abstract
In this work, we present a quantitative analysis of cutaneous melanoma based on 615 patients attended in Cruces University Hospital between 1988 and 2012. First, we studied which characteristics are more associated with the metastasis of this kind of cancer. We observed that people with light eyes, light hair, an ulcerated nevus, or exposed to the sun during working hours, had more risk to suffer from metastasis. Besides, a big diameter or a thick nevus (measured by Breslow’s depth) were also associated with this condition. Next, we evaluated the metastasis detection capability of the tests performed in this hospital, which indicated that X-rays and CT scan were the best techniques for metastasis detection, since they identified this condition successfully in 80% and 93.5% of the cases, respectively. Moreover, we concluded that the blood test was very inaccurate, since it recognized the presence of metastasis in only 40% of the cases and failed in the rest. Consequently, we suggest the replacement of this test in order to save money, time, and avoid the misdiagnosis of cutaneous melanoma metastasis. Finally, we built a predictive model to forecast the time that takes for metastasis to happen, based on Breslow’s depth. This tool could be used not only for improving the programming appointment management of the dermatology section, but also for detecting metastasis sooner.
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Work by the first and second authors was supported by the Basque Government grant IT974-16.
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Malaina, I. et al. (2018). Metastasis of Cutaneous Melanoma: Risk Factors, Detection and Forecasting. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2018. Lecture Notes in Computer Science(), vol 10813. Springer, Cham. https://doi.org/10.1007/978-3-319-78723-7_44
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DOI: https://doi.org/10.1007/978-3-319-78723-7_44
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