Predicting melanoma risk: theory, practice and future challenges
- PMID: 30190816
- PMCID: PMC6094627
- DOI: 10.2217/mmt.14.15
Predicting melanoma risk: theory, practice and future challenges
Abstract
The incidence of melanoma continues to rise in most fair-skinned populations. Strategies to curb the toll from melanoma include targeting the patients who are at highest risk with the aim of either preventing the onset of cancer or intervening early in order to improve survival. The challenge has been to synthesize the available information on risk factors into prediction tools with clinical utility, such that 'high-risk' patients can be identified with accuracy. While a number of risk prediction tools for melanoma have been developed, few have undergone rigorous evaluation of their performance in order to assess calibration or discrimination, and even fewer have been validated in independent populations. Future research should assess the validity of existing tools and seek to integrate the increasing volumes of data being generated by genomic studies.
Keywords: cancer control; early detection; melanoma; prevention; risk factors; risk prediction; risk stratification.
Conflict of interest statement
Financial & competing interests disclosure D Whiteman is supported by a Research Fellowship (APP1058522) from the National Health and Medical Research Council of Australia. The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.
Similar articles
-
Optimal surveillance strategies for patients with stage 1 cutaneous melanoma post primary tumour excision: three systematic reviews and an economic model.Health Technol Assess. 2021 Nov;25(64):1-178. doi: 10.3310/hta25640. Health Technol Assess. 2021. PMID: 34792018
-
[The Rise of Artificial Intelligence - High Prediction Accuracy in Early Detection of Pigmented Melanoma].Laryngorhinootologie. 2023 Jul;102(7):496-503. doi: 10.1055/a-1949-3639. Epub 2022 Dec 29. Laryngorhinootologie. 2023. PMID: 36580975 German.
-
Strategies for early recognition of cutaneous melanoma-present and future.Dermatol Pract Concept. 2012 Jul 31;2(3):203a06. doi: 10.5826/dpc.0203a06. Print 2012 Jul. Dermatol Pract Concept. 2012. PMID: 23785608 Free PMC article.
-
Predicting the future risk of lung cancer: development, and internal and external validation of the CanPredict (lung) model in 19·67 million people and evaluation of model performance against seven other risk prediction models.Lancet Respir Med. 2023 Aug;11(8):685-697. doi: 10.1016/S2213-2600(23)00050-4. Epub 2023 Apr 5. Lancet Respir Med. 2023. PMID: 37030308
-
Screening for skin cancer.Am J Prev Med. 2001 Apr;20(3 Suppl):47-58. doi: 10.1016/s0749-3797(01)00258-6. Am J Prev Med. 2001. PMID: 11306232 Review.
References
-
- Australian Institute of Health and Welfare. Australian Cancer Incidence and Mortality Books. Australian Institute of Health and Welfare; Australia: 2012.
-
- Howlader N, Noone AM, Krapcho M, et al., editors. SEER Cancer Statistics Review, 1975–2014. National Cancer Institute; MD, USA: 2013. (Eds)
-
- Erdmann F, Lortet-Tieulent J, Schüz J, et al. International trends in the incidence of malignant melanoma 1953–2008 – are recent generations at higher or lower risk? Int. J. Cancer. 2013;132(2):385–400. - PubMed
-
- Moons KG, Royston P, Vergouwe Y, Grobbee DE, Altman DG. Prognosis and prognostic research: what, why, and how? BMJ. 2009;338:b375. - PubMed
-
• One of a series of papers in the British Medical Journal that describe the theory and practice of risk prediction. This paper is recommended for clinicians with an interest in the practical aspects of risk prediction.
Publication types
LinkOut - more resources
Full Text Sources
Other Literature Sources