title: Individual risk of cutaneous melanoma in New Zealand: developing a clinical prediction aid.
abstract: BACKGROUND
  New Zealand and Australia have the highest melanoma incidence rates worldwide. In New Zealand, both the incidence and thickness have been increasing. Clinical decisions require accurate risk prediction but a simple list of genetic, phenotypic and behavioural risk factors is inadequate to estimate individual risk as the risk factors for melanoma have complex interactions. In order to offer tailored clinical management strategies, we developed a New Zealand prediction model to estimate individual 5-year absolute risk of melanoma.
  
  
  METHODS
  A population-based case-control study (368 cases and 270 controls) of melanoma risk factors provided estimates of relative risks for fair-skinned New Zealanders aged 20-79 years. Model selection techniques and multivariate logistic regression were used to determine the important predictors. The relative risks for predictors were combined with baseline melanoma incidence rates and non-melanoma mortality rates to calculate individual probabilities of developing melanoma within 5 years.
  
  
  RESULTS
  For women, the best model included skin colour, number of moles > =5 mm on the right arm, having a 1st degree relative with large moles, and a personal history of non-melanoma skin cancer (NMSC). The model correctly classified 68% of participants; the C-statistic was 0.74. For men, the best model included age, place of occupation up to age 18 years, number of moles > =5 mm on the right arm, birthplace, and a history of NMSC. The model correctly classified 67% of cases; the C-statistic was 0.71.
  
  
  CONCLUSIONS
  We have developed the first New Zealand risk prediction model that calculates individual absolute 5-year risk of melanoma. This model will aid physicians to identify individuals at high risk, allowing them to individually target surveillance and other management strategies, and thereby reduce the high melanoma burden in New Zealand.
authors.affiliation: Hugh Adam Cancer Epidemiology Unit, Department of Preventive and Social Medicine, Dunedin School of Medicine, University of Otago, P,O, Box 56, Dunedin 9054, New Zealand. mary-jane.sneyd@otago.ac.nz.
authors.forename: Mary Jane
authors.initials: MJ
authors.lastname: Sneyd
authors.forename: Claire
authors.initials: C
authors.lastname: Cameron
authors.forename: Brian
authors.initials: B
authors.lastname: Cox
mesh_terms: D000328:Adult; D000368:Aged; D016022:Case-Control Studies; D016009:Chi-Square Distribution; D003661:Decision Support Techniques; D005260:Female; D020022:Genetic Predisposition to Disease; D006801:Humans; D015994:Incidence; D016015:Logistic Models; D008297:Male; D008545:Melanoma / Q000175:diagnosis / Q000453:epidemiology* / Q000235:genetics; D008875:Middle Aged; D015999:Multivariate Analysis; D009506:Nevus / Q000175:diagnosis / Q000453:epidemiology* / Q000235:genetics; D009520:New Zealand / Q000453:epidemiology; D011237:Predictive Value of Tests; D012111:Residence Characteristics; D018570:Risk Assessment; D012307:Risk Factors; D012737:Sex Factors; D012878:Skin Neoplasms / Q000175:diagnosis / Q000453:epidemiology* / Q000235:genetics; D012880:Skin Pigmentation; D013997:Time Factors; D017132:Workplace; D055815:Young Adult