Literature DB >> 28692584

Association between risk factors and detection of cutaneous melanoma in the setting of a population-based skin cancer screening.

Joachim Hübner1, Annika Waldmann1, Nora Eisemann1, Maria Noftz1, Alan C Geller2, Martin A Weinstock3,4,5, Beate Volkmer6, Rüdiger Greinert6, Eckhard W Breitbart7, Alexander Katalinic1,8.   

Abstract

Early detection is considered to improve the prognosis of cutaneous melanoma. The value of population-based screening for melanoma, however, is still controversial. The aim of this study was to evaluate the predictive power of established risk factors in the setting of a population-based screening and to provide empirical evidence for potential risk stratifications. We reanalyzed data (including age, sex, risk factors, and screening results) of 354 635 participants in the Skin Cancer Research to provide Evidence for Effectiveness of Screening in Northern Germany (SCREEN)project conducted in the German state of Schleswig-Holstein (2003-2004). In multivariable analysis, atypical nevi [odds ratio (OR): 17.4; 95% confidence interval (CI): 14.4-20.1], personal history of melanoma (OR: 5.3; 95% CI: 3.6-7.6), and multiple (≥40) common nevi (OR: 1.3; 95% CI: 1.1-1.6) were associated with an increased risk of melanoma detection. Family history and congenital nevi were not significantly associated with melanoma detection in the SCREEN. The effects of several risk-adapted screening strategies were evaluated. Hypothesizing a screening of individuals aged more than or equal to 35 years, irrespective of risk factors (age approach), the number needed to screen is 559 (95% CI: 514-612), whereas a screening of adults (aged ≥20) with at least one risk factor (risk approach) leads to a number needed to screen of 178 (95% CI: 163-196). Converted into one screen-detected melanoma, the number of missed melanomas is 0.15 (95% CI: 0.12-0.18) with the age approach and 0.22 (95% CI: 0.19-0.26) with the risk approach. The results indicate that focusing on individuals at high risk for melanoma may improve the cost-effectiveness and the benefit-to-harm balance of melanoma screening programs.

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Year:  2018        PMID: 28692584     DOI: 10.1097/CEJ.0000000000000392

Source DB:  PubMed          Journal:  Eur J Cancer Prev        ISSN: 0959-8278            Impact factor:   2.497


  6 in total

1.  Risk Factors of Subsequent Primary Melanomas in Austria.

Authors:  Christoph Müller; Judith Wendt; Sabine Rauscher; Raute Sunder-Plassmann; Erika Richtig; Ingrid Fae; Gottfried Fischer; Ichiro Okamoto
Journal:  JAMA Dermatol       Date:  2019-02-01       Impact factor: 10.282

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.  Mechanisms of JAK-STAT signaling pathway mediated by CXCL8 gene silencing on epithelial-mesenchymal transition of human cutaneous melanoma cells.

Authors:  Xiaorui Hu; Lili Yuan; Teng Ma
Journal:  Oncol Lett       Date:  2020-06-09       Impact factor: 2.967

4.  Targeted Melanoma Screening: Risk Self-Assessment and Skin Self-Examination Education Delivered During Mammography of Women.

Authors:  June K Robinson; Megan Perez; Dalya Abou-El-Seoud; Kathryn Kim; Zoe Brown; Elona Liko-Hazizi; Sarah M Friedewald; Mary Kwasny; Bonnie Spring
Journal:  JNCI Cancer Spectr       Date:  2019-06-28

5.  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

6.  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

  6 in total

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