Literature DB >> 1814137

Melanocytic naevi, melanoma and sun exposure.

A Augustsson1.   

Abstract

The naevus profile was examined in 379 randomly selected Swedes (30-50 years) and in 121 melanoma patients in the same age-range selected from the Regional Cancer Register. The total body count of common naevi (CN) greater than or equal to 2 mm in the population was high (mean 67, range 1-300). Even so, the melanoma patients had almost twice as many CN as the controls (mean 113, range 13-347). The prevalence of clinical dysplastic naevi (DN) was 18% in the population and 56% in the patients. The corresponding figures for histologically diagnosed DN were 8% and 40% respectively. Subjects with dysplastic naevi had a significantly larger number of CN than those without DN. Subjects with a sun-sensitive skin, greater than or equal to 150 naevi and presence of DN had a 50 times higher melanoma risk than those without these characteristics. For identifying subjects at risk of developing cutaneous malignant melanoma (CMM), clinically diagnosed DN was as good a discriminator as histologically diagnosed DN. The numbers of naevi in different skin areas were tested for their power in predicting the total body naevus count. The strongest correlations were found between total counts and counts on the anterior surface of the thighs and the lateral aspect of the arms. Counts from either of these areas will provide a practical and satisfactory estimate of the total number of naevi. To study the possible link between sun exposure, naevus formation and melanoma development, the distribution of CN, DN and CMM over the body surface was studied in the 121 melanoma patients and in 310 consecutive controls. The number of naevi was four times as high in a sun-exposed area on the lower back compared with in an adjacent sun-protected area on the buttocks, indicating that sunlight plays a role in naevus development. Both CN and CMM were found to have a general distribution pattern over the body surface consistent with the idea that sun exposure is important for their formation. The number of CN and CMM per unit body surface area was significantly higher in intermittently sun-exposed than in rarely or chronically exposed skin. The distribution pattern of DN was quite different from that of CN, with few DN on the sun-exposed upper chest and face and many DN in protected areas such as the buttocks and lower abdomen, indicating that DN may develop independently of sun exposure.(ABSTRACT TRUNCATED AT 400 WORDS)

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Year:  1991        PMID: 1814137

Source DB:  PubMed          Journal:  Acta Derm Venereol Suppl (Stockh)        ISSN: 0365-8341


  5 in total

1.  Sun exposure, pigmentary traits, and risk of cutaneous malignant melanoma: a case-control study in a Mediterranean population.

Authors:  J M Ródenas; M Delgado-Rodríguez; M T Herranz; J Tercedor; S Serrano
Journal:  Cancer Causes Control       Date:  1996-03       Impact factor: 2.506

2.  Using the Prediction Model Risk of Bias Assessment Tool (PROBAST) to Evaluate Melanoma Prediction Studies.

Authors:  Isabelle Kaiser; Sonja Mathes; Annette B Pfahlberg; Wolfgang Uter; Carola Berking; Markus V Heppt; Theresa Steeb; Katharina Diehl; Olaf Gefeller
Journal:  Cancers (Basel)       Date:  2022-06-20       Impact factor: 6.575

3.  Genetic analysis of ultraviolet radiation-induced skin hyperplasia and neoplasia in a laboratory marsupial model (Monodelphis domestica).

Authors:  J L VandeBerg; S Williams-Blangero; G B Hubbard; R D Ley; E S Robinson
Journal:  Arch Dermatol Res       Date:  1994       Impact factor: 3.017

4.  Reporting Quality of Studies Developing and Validating Melanoma Prediction Models: An Assessment Based on the TRIPOD Statement.

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

5.  Risk Prediction Models for Melanoma: A Systematic Review on the Heterogeneity in Model Development and Validation.

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

  5 in total

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