Identifying people at higher risk of melanoma across the UK: a primary care-based electronic survey

Talk Code: 
2E.6
Presenter: 
Fiona Walter
Co-authors: 
Juliet Usher-Smith, Angelos Kassianos, Gary Abel, Howie Teoh, Susan Hall, Richard Neal, Peter Murchie, Jon Emery
Author institutions: 
University of Cambridge, University College London, Bangor University, University of Aberdeen, University of Melbourne, Australia

Problem

Melanoma incidence is rising rapidly worldwide among Caucasian populations. Defining higher-risk populations using risk prediction models may help targeted screening and early detection approaches. Can people at higher risk of melanoma be identified via primary care in the UK?

Approach

We recruited participants from the waiting rooms of 22 general practices covering a total population of >240,000 in three UK regions: Eastern England, Northeast Scotland, North Wales. Participants completed an electronic questionnaire incorporating the William's melanoma risk model using tablet computers.

Findings

7,742/9,004 approached people completed the electronic questionnaire (86%). The mean melanoma risk score for the 7,566 eligible participants was 17.15 (SD 8.51), with small regional differences (lower in England compared with Scotland (p = 0.001) and Wales (p < 0.0005)), mainly due to greater freckling and childhood sunburn among Scottish and Welsh participants. After weighting to the age and gender distribution, different potential cut-offs would allow between 4% and 20% of the population to be identified as higher risk, and those groups would contain 30% and 60% respectively of those likely to develop melanoma.

Consequences

Our findings suggest that collecting data on the melanoma risk profile of the general population in UK primary care is both feasible and acceptable. This provides opportunities for new methods of real-time risk assessment and risk stratified cancer interventions.

Submitted by: 
Fiona Walter
Funding acknowledgement: 
This report is independent research arising from Fiona Walter’s Clinician Scientist award supported by the NIHR (RG 68235).