Literature DB >> 27829101

Clinical Features Associated With Individuals at Higher Risk of Melanoma: A Population-Based Study.

Caroline G Watts1, Christine Madronio1, Rachael L Morton2, Chris Goumas3, Bruce K Armstrong1, Austin Curtin4, Scott W Menzies5, Graham J Mann6, John F Thompson3, Anne E Cust7.   

Abstract

Importance: The identification of a subgroup at higher risk of melanoma may assist in early diagnosis. Objective: To characterize melanoma patients and the clinical features associated with their melanomas according to patient risk factors: many nevi, history of previous melanoma, and family history of melanoma, to assist with improving the identification and treatment of a higher-risk subgroup. Design, Setting, and Participants: The Melanoma Patterns of Care study was a population-based observational study of physicians' reported treatment of 2727 patients diagnosed with an in situ or invasive primary melanoma over a 12-month period from October 2006 to 2007 conducted in New South Wales. Our analysis of these data took place from 2015 to 2016. Main Outcomes and Measures: Age at diagnosis and body site of melanoma.
Results: Of the 2727 patients with melanoma included, 1052 (39%) were defined as higher risk owing to a family history of melanoma, multiple primary melanomas, or many nevi. Compared with patients with melanoma who were at lower risk (ie, without any of these risk factors), the higher-risk group had a younger mean age at diagnosis (62 vs 65 years, P < .001), but this differed by risk factor (56 years for patients with a family history, 59 years for those with many nevi, and 69 years for those with a previous melanoma). These age differences were consistent across all body sites. Among higher-risk patients, those with many nevi were more likely to have melanoma on the trunk (41% vs 29%, P < .001), those with a family history of melanoma were more likely to have melanomas on the limbs (57% vs 42%, P < .001), and those with a personal history were more likely to have melanoma on the head and neck (21% vs 15%, P = .003). Conclusions and Relevance: These findings suggest that a person's risk factor status could be used to tailor surveillance programs and education about skin self-examination.

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Year:  2017        PMID: 27829101     DOI: 10.1001/jamadermatol.2016.3327

Source DB:  PubMed          Journal:  JAMA Dermatol        ISSN: 2168-6068            Impact factor:   10.282


  11 in total

1.  Patient-Reported Experiences After Hysterectomy: A Cross-Sectional Study of the Views of Over 2300 Women.

Authors:  Monika Janda; Nigel R Armfield; Gayle Kerr; Suzanne Kurz; Graeme Jackson; Jason Currie; Katie Page; Edward Weaver; Anusch Yazdani; Andreas Obermair
Journal:  J Patient Exp       Date:  2019-04-25

2.  Host Characteristics and Risk of Incident Melanoma by Breslow Thickness.

Authors:  Wen-Qing Li; Eunyoung Cho; Shaowei Wu; Suyun Li; Natalie H Matthews; Abrar A Qureshi
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2018-10-19       Impact factor: 4.254

Review 3.  The World of Melanoma: Epidemiologic, Genetic, and Anatomic Differences of Melanoma Across the Globe.

Authors:  Florentia Dimitriou; Regina Krattinger; Egle Ramelyte; Marjam J Barysch; Sara Micaletto; Reinhard Dummer; Simone M Goldinger
Journal:  Curr Oncol Rep       Date:  2018-09-24       Impact factor: 5.075

4.  Conflicts and contradictions in current skin cancer screening guidelines.

Authors:  K Y Wojcik; L A Escobedo; K A Miller; M Hawkins; O Ahadiat; S Higgins; A Wysong; Myles Cockburn
Journal:  Curr Dermatol Rep       Date:  2017-11-04

5.  Photoaging Mobile Apps as a Novel Opportunity for Melanoma Prevention: Pilot Study.

Authors:  Titus Josef Brinker; Dirk Schadendorf; Joachim Klode; Ioana Cosgarea; Alexander Rösch; Philipp Jansen; Ingo Stoffels; Benjamin Izar
Journal:  JMIR Mhealth Uhealth       Date:  2017-07-26       Impact factor: 4.773

6.  A Nomogram Combining a Four-Gene Biomarker and Clinical Factors for Predicting Survival of Melanoma.

Authors:  Chuan Zhang; Dan Dang; Yuqian Wang; Xianling Cong
Journal:  Front Oncol       Date:  2021-04-01       Impact factor: 6.244

7.  Skin Tumors among Biopsy Samples in Patients Attending Dermatological Out Patient Department in a Tertiary Care Hospital of Nepal: A Descriptive Cross-sectional Study.

Authors:  Shristi Shrestha; Arnija Rana; Deepika Karki; Asim Shrestha
Journal:  JNMA J Nepal Med Assoc       Date:  2021-09-11       Impact factor: 0.556

8.  Photoaging Mobile Apps in School-Based Melanoma Prevention: Pilot Study.

Authors:  Titus Josef Brinker; Christian Martin Brieske; Christoph Matthias Schaefer; Fabian Buslaff; Martina Gatzka; Maximilian Philip Petri; Wiebke Sondermann; Dirk Schadendorf; Ingo Stoffels; Joachim Klode
Journal:  J Med Internet Res       Date:  2017-09-08       Impact factor: 5.428

9.  Predicting the Risk of Melanoma Metastasis Using an Immune Risk Score in the Melanoma Cohort.

Authors:  Yang Sheng; Cheng Yanping; Liu Tong; Liu Ning; Liu Yufeng; Liang Geyu
Journal:  Front Bioeng Biotechnol       Date:  2020-03-31

10.  Pivotal factors associated with the immunosuppressive tumor microenvironment and melanoma metastasis.

Authors:  Chuan Zhang; Dan Dang; Lele Cong; Hongyan Sun; Xianling Cong
Journal:  Cancer Med       Date:  2021-06-22       Impact factor: 4.452

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