Literature DB >> 30190816

Predicting melanoma risk: theory, practice and future challenges.

David Whiteman1.   

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.

Entities:  

Keywords:  cancer control; early detection; melanoma; prevention; risk factors; risk prediction; risk stratification

Year:  2014        PMID: 30190816      PMCID: PMC6094627          DOI: 10.2217/mmt.14.15

Source DB:  PubMed          Journal:  Melanoma Manag        ISSN: 2045-0885


  43 in total

1.  A risk model for prediction of lung cancer.

Authors:  Margaret R Spitz; Waun Ki Hong; Christopher I Amos; Xifeng Wu; Matthew B Schabath; Qiong Dong; Sanjay Shete; Carol J Etzel
Journal:  J Natl Cancer Inst       Date:  2007-05-02       Impact factor: 13.506

2.  Prognosis and prognostic research: what, why, and how?

Authors:  Karel G M Moons; Patrick Royston; Yvonne Vergouwe; Diederick E Grobbee; Douglas G Altman
Journal:  BMJ       Date:  2009-02-23

3.  Increases in invasive melanoma in England, 1979-2006, by anatomical site.

Authors:  S C Wallingford; R D Alston; J M Birch; A C Green
Journal:  Br J Dermatol       Date:  2011-08-04       Impact factor: 9.302

4.  Development of a targeted risk-group model for skin cancer screening based on more than 100,000 total skin examinations.

Authors:  S Guther; K Ramrath; D Dyall-Smith; M Landthaler; W Stolz
Journal:  J Eur Acad Dermatol Venereol       Date:  2011-03-04       Impact factor: 6.166

5.  Identifying Persons at Highest Risk of Melanoma Using Self-Assessed Risk Factors.

Authors:  Lisa H Williams; Andrew R Shors; William E Barlow; Cam Solomon; Emily White
Journal:  J Clin Exp Dermatol Res       Date:  2011

6.  Development of an individual score for melanoma risk.

Authors:  Gaelle Quéreux; Dominique Moyse; Yves Lequeux; Olivier Jumbou; Anabelle Brocard; Daniel Antonioli; Brigitte Dréno; Jean-Michel Nguyen
Journal:  Eur J Cancer Prev       Date:  2011-05       Impact factor: 2.497

7.  Reproducibility of reported measurements of sun exposure in a case-control study.

Authors:  D R English; B K Armstrong; A Kricker
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  1998-10       Impact factor: 4.254

8.  Screening for skin cancer: U.S. Preventive Services Task Force recommendation statement.

Authors: 
Journal:  Ann Intern Med       Date:  2009-02-03       Impact factor: 25.391

9.  Risk factors for developing cutaneous melanoma and criteria for identifying persons at risk: multicenter case-control study of the Central Malignant Melanoma Registry of the German Dermatological Society.

Authors:  C Garbe; P Büttner; J Weiss; H P Soyer; U Stocker; S Krüger; M Roser; J Weckbecker; R Panizzon; F Bahmer
Journal:  J Invest Dermatol       Date:  1994-05       Impact factor: 8.551

10.  Constitutional and environmental risk factors for cutaneous melanoma in an Italian population. A case-control study.

Authors:  Maria Concetta Fargnoli; Domenico Piccolo; Emma Altobelli; Federica Formicone; Sergio Chimenti; Ketty Peris
Journal:  Melanoma Res       Date:  2004-04       Impact factor: 3.599

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