BACKGROUND: Skin cancer screening aims to detect potentially metastasizing skin cancers at an early and surgically curable stage. This may take the form of mass screening, as currently occurs in Germany, or of targeted screening of those at greatest risk. OBJECTIVE: To develop a model to identify patients at high risk of developing skin cancer who would benefit from regular skin cancer screening. METHODS: This was an open prospective point-prevalence study of consecutive patients presenting to dermatologists for a total skin check. Demographic and skin cancer risk factors were recorded and, for the first time, histology of skin lesions was documented. Results were analysed by univariate and multivariate analyses and, after logistic regression with stepwise forward selection, a risk-group model was developed. RESULTS: The results of 108,281 total skin examinations were available for analysis. 142 definite melanomas, 108 severely dysplastic naevi/cannot-exclude-melanoma, 491 basal cell carcinomas (BCC) and 93 squamous cell carcinomas (SCC) were excised. A risk model was developed for melanoma and SCC based on mathematical e-functions. The model had >92% sensitivity for melanoma and SCC and an overall 67.24% specificity for melanoma, SCC and BCC. This targeted risk model identified one-third of the study population as being at risk for the development of melanoma and SCC. CONCLUSIONS: Using the risk calculator developed from this study, targeted screening of the identified at-risk population reduces the numbers needed to be screened regularly by 50%, yet has better sensitivity for melanoma and similar sensitivity for SCC compared to the current mass screening programme in Germany.
BACKGROUND:Skin cancer screening aims to detect potentially metastasizing skin cancers at an early and surgically curable stage. This may take the form of mass screening, as currently occurs in Germany, or of targeted screening of those at greatest risk. OBJECTIVE: To develop a model to identify patients at high risk of developing skin cancer who would benefit from regular skin cancer screening. METHODS: This was an open prospective point-prevalence study of consecutive patients presenting to dermatologists for a total skin check. Demographic and skin cancer risk factors were recorded and, for the first time, histology of skin lesions was documented. Results were analysed by univariate and multivariate analyses and, after logistic regression with stepwise forward selection, a risk-group model was developed. RESULTS: The results of 108,281 total skin examinations were available for analysis. 142 definite melanomas, 108 severely dysplastic naevi/cannot-exclude-melanoma, 491 basal cell carcinomas (BCC) and 93 squamous cell carcinomas (SCC) were excised. A risk model was developed for melanoma and SCC based on mathematical e-functions. The model had >92% sensitivity for melanoma and SCC and an overall 67.24% specificity for melanoma, SCC and BCC. This targeted risk model identified one-third of the study population as being at risk for the development of melanoma and SCC. CONCLUSIONS: Using the risk calculator developed from this study, targeted screening of the identified at-risk population reduces the numbers needed to be screened regularly by 50%, yet has better sensitivity for melanoma and similar sensitivity for SCC compared to the current mass screening programme in Germany.
Authors: Fangyi Gu; Ting-Huei Chen; Ruth M Pfeiffer; Maria Concetta Fargnoli; Donato Calista; Paola Ghiorzo; Ketty Peris; Susana Puig; Chiara Menin; Arcangela De Nicolo; Monica Rodolfo; Cristina Pellegrini; Lorenza Pastorino; Evangelos Evangelou; Tongwu Zhang; Xing Hua; Curt T DellaValle; D Timothy Bishop; Stuart MacGregor; Mark I Iles; Matthew H Law; Anne Cust; Kevin M Brown; Alexander J Stratigos; Eduardo Nagore; Stephen Chanock; Jianxin Shi; Melanoma Meta-Analysis Consortium; MelaNostrum Consortium; Maria Teresa Landi Journal: Hum Mol Genet Date: 2018-12-01 Impact factor: 6.150
Authors: Catherine M Olsen; Rachel E Neale; Adèle C Green; Penelope M Webb; David C Whiteman Journal: J Invest Dermatol Date: 2014-12-30 Impact factor: 8.551
Authors: Isabelle Kaiser; Katharina Diehl; Markus V Heppt; Sonja Mathes; Annette B Pfahlberg; Theresa Steeb; Wolfgang Uter; Olaf Gefeller Journal: Healthcare (Basel) Date: 2022-01-26
Authors: Anne E Cust; Chris Goumas; Kylie Vuong; John R Davies; Jennifer H Barrett; Elizabeth A Holland; Helen Schmid; Chantelle Agha-Hamilton; Bruce K Armstrong; Richard F Kefford; Joanne F Aitken; Graham G Giles; D Bishop; Julia A Newton-Bishop; John L Hopper; Graham J Mann; Mark A Jenkins Journal: BMC Cancer Date: 2013-09-04 Impact factor: 4.430
Authors: Isabelle Kaiser; Annette B Pfahlberg; Wolfgang Uter; Markus V Heppt; Marit B Veierød; Olaf Gefeller Journal: Int J Environ Res Public Health Date: 2020-10-28 Impact factor: 3.390