Skip to main content
Top
Published in: BMC Cancer 1/2014

Open Access 01-12-2014 | Research article

Individual risk of cutaneous melanoma in New Zealand: developing a clinical prediction aid

Authors: Mary Jane Sneyd, Claire Cameron, Brian Cox

Published in: BMC Cancer | Issue 1/2014

Login to get access

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.
Appendix
Available only for authorised users
Literature
1.
go back to reference Ministry of Health: Cancer: New Registrations and Deaths, 2009. 2012, Wellington, New Zealand: Ministry of Health Ministry of Health: Cancer: New Registrations and Deaths, 2009. 2012, Wellington, New Zealand: Ministry of Health
2.
go back to reference Richardson A, Fletcher L, Sneyd M, Cox B, Reeder AI: The incidence and thickness of cutaneous malignant melanoma in New Zealand 1994–2004. N Z Med J. 2008, 121 (1279): 18-26.PubMed Richardson A, Fletcher L, Sneyd M, Cox B, Reeder AI: The incidence and thickness of cutaneous malignant melanoma in New Zealand 1994–2004. N Z Med J. 2008, 121 (1279): 18-26.PubMed
3.
go back to reference Sneyd M, Cox B: Clinical and histologic factors associated with melanoma thickness in New Zealand Europeans, Maori, and Pacific peoples. Cancer. 2011, 117 (11): 2489-2498. 10.1002/cncr.25795.CrossRefPubMed Sneyd M, Cox B: Clinical and histologic factors associated with melanoma thickness in New Zealand Europeans, Maori, and Pacific peoples. Cancer. 2011, 117 (11): 2489-2498. 10.1002/cncr.25795.CrossRefPubMed
4.
go back to reference Sneyd M, Cox B: The control of melanoma in New Zealand. N Z Med J. 2006, 119 (1242): 1-11. Sneyd M, Cox B: The control of melanoma in New Zealand. N Z Med J. 2006, 119 (1242): 1-11.
5.
go back to reference Williams L, Shors A, Barlow W, Solomon C, White E: Identifying persons at highest risk of melanoma using self-assessed risk factors. Clin Exp Dermatol Res. 2011, 2: 6- Williams L, Shors A, Barlow W, Solomon C, White E: Identifying persons at highest risk of melanoma using self-assessed risk factors. Clin Exp Dermatol Res. 2011, 2: 6-
6.
go back to reference Sneyd MJ: Malignant Melanoma: Early Diagnosis and Screening. PhD Thesis. 1999, Dunedin: University of Otago Sneyd MJ: Malignant Melanoma: Early Diagnosis and Screening. PhD Thesis. 1999, Dunedin: University of Otago
7.
go back to reference Hosmer D, Lemeshow S: Applied Logistic Regression. 1989, New York: J Wiley & Sons Hosmer D, Lemeshow S: Applied Logistic Regression. 1989, New York: J Wiley & Sons
8.
go back to reference StataCorp: Stata: Stata: Release 11. 2009, College Station, TX: StataCorp LP: Statistical Software StataCorp: Stata: Stata: Release 11. 2009, College Station, TX: StataCorp LP: Statistical Software
9.
go back to reference Fears T, Guerry D, Pfeiffer R, Sagebiel R, Elder D, Halpern A, Holly E, Hartge P, Tucker M: Identifying individuals at high risk of melanoma: a practical predictor of absolute risk. J Clin Oncol. 2006, 24 (22): 3590-3596. 10.1200/JCO.2005.04.1277.CrossRefPubMed Fears T, Guerry D, Pfeiffer R, Sagebiel R, Elder D, Halpern A, Holly E, Hartge P, Tucker M: Identifying individuals at high risk of melanoma: a practical predictor of absolute risk. J Clin Oncol. 2006, 24 (22): 3590-3596. 10.1200/JCO.2005.04.1277.CrossRefPubMed
10.
go back to reference Bruzzi P, Green S, Byar D, Brinton L, Schairer C: Estimating the population attributable risk for multiple risk factors using case–control data. Am J Epidemiol. 1985, 122 (5): 904-914.PubMed Bruzzi P, Green S, Byar D, Brinton L, Schairer C: Estimating the population attributable risk for multiple risk factors using case–control data. Am J Epidemiol. 1985, 122 (5): 904-914.PubMed
11.
go back to reference Gail M, Brinton L, Byar D, Corle D, Green S, Schairer C, Mulvihill J: Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst. 1989, 81: 1879-1886. 10.1093/jnci/81.24.1879.CrossRefPubMed Gail M, Brinton L, Byar D, Corle D, Green S, Schairer C, Mulvihill J: Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst. 1989, 81: 1879-1886. 10.1093/jnci/81.24.1879.CrossRefPubMed
12.
go back to reference Steyerberg E: Clinical Prediction Models: A practical approach to development, validation and updating. 2009, New York: SpringerCrossRef Steyerberg E: Clinical Prediction Models: A practical approach to development, validation and updating. 2009, New York: SpringerCrossRef
13.
go back to reference Austin P, Tu J: Bootstrap methods for developing predictive models. Am Stat. 2004, 58 (2): 131-137. 10.1198/0003130043277.CrossRef Austin P, Tu J: Bootstrap methods for developing predictive models. Am Stat. 2004, 58 (2): 131-137. 10.1198/0003130043277.CrossRef
14.
go back to reference Royston P, Moons K, Altman D, Vergouwe Y: Prognosis and prognostic research: developing a prognostic model. BMJ. 2009, 338: 1373-1377. 10.1136/bmj.b1373.CrossRef Royston P, Moons K, Altman D, Vergouwe Y: Prognosis and prognostic research: developing a prognostic model. BMJ. 2009, 338: 1373-1377. 10.1136/bmj.b1373.CrossRef
15.
go back to reference Harrell FE, Lee KL, Mark DB: Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996, 15 (4): 361-387. 10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4.CrossRefPubMed Harrell FE, Lee KL, Mark DB: Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996, 15 (4): 361-387. 10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4.CrossRefPubMed
18.
go back to reference Cho E, Rosner B, Feskanich D, Colditz G: Risk factors and individual probabilities of melanoma for whites. J Clin Oncol. 2005, 23: 2669-2675.CrossRefPubMed Cho E, Rosner B, Feskanich D, Colditz G: Risk factors and individual probabilities of melanoma for whites. J Clin Oncol. 2005, 23: 2669-2675.CrossRefPubMed
19.
go back to reference Fortes C, Mastroeni S, Bakos L, Antonelli G, Alessandroni L, Pilla M, Alotto M, Zappalà A, Manoorannparampill T, Bonamigo R, Pasquini P, Melchi F: Identifying individuals at high risk of melanoma: a simple tool. Eur J Cancer Prev. 2010, 19 (5): 393-400. 10.1097/CEJ.0b013e32833b492f.CrossRefPubMed Fortes C, Mastroeni S, Bakos L, Antonelli G, Alessandroni L, Pilla M, Alotto M, Zappalà A, Manoorannparampill T, Bonamigo R, Pasquini P, Melchi F: Identifying individuals at high risk of melanoma: a simple tool. Eur J Cancer Prev. 2010, 19 (5): 393-400. 10.1097/CEJ.0b013e32833b492f.CrossRefPubMed
20.
go back to reference Harbauer A, Binder M, Pehamberger H, Wolff K, Kittler H: Validity of an unsupervised self-administered questionnaire for self-assessment of melanoma risk. Melanoma Res. 2003, 13 (5): 537-542. 10.1097/00008390-200310000-00013.CrossRefPubMed Harbauer A, Binder M, Pehamberger H, Wolff K, Kittler H: Validity of an unsupervised self-administered questionnaire for self-assessment of melanoma risk. Melanoma Res. 2003, 13 (5): 537-542. 10.1097/00008390-200310000-00013.CrossRefPubMed
21.
go back to reference MacKie R, Freudenberger T, Aitchison T: Personal risk-factor chart for cutaneous melanoma. Lancet. 1989, 2: 487-490.CrossRefPubMed MacKie R, Freudenberger T, Aitchison T: Personal risk-factor chart for cutaneous melanoma. Lancet. 1989, 2: 487-490.CrossRefPubMed
22.
go back to reference Moons K, Royston P, Vergouwe Y, Grobbee D, Altman D: Prognosis and prognostic research: what, why, and how?. BMJ. 2009, 338: 1317-1320. 10.1136/bmj.b1317.CrossRef Moons K, Royston P, Vergouwe Y, Grobbee D, Altman D: Prognosis and prognostic research: what, why, and how?. BMJ. 2009, 338: 1317-1320. 10.1136/bmj.b1317.CrossRef
23.
go back to reference Sneyd M, Cox B: Melanoma in Maori, Asian and Pacific peoples in New Zealand. Cancer Epidemiol Biomarkers Prev. 2009, 18 (6): 1706-1713. 10.1158/1055-9965.EPI-08-0682.CrossRefPubMed Sneyd M, Cox B: Melanoma in Maori, Asian and Pacific peoples in New Zealand. Cancer Epidemiol Biomarkers Prev. 2009, 18 (6): 1706-1713. 10.1158/1055-9965.EPI-08-0682.CrossRefPubMed
24.
go back to reference Mar V, Wolfe R, Kelly JW: Predicting melanoma risk for the Australian population. Australas J Dermatol. 2011, 52 (2): 109-116. 10.1111/j.1440-0960.2010.00727.x.CrossRefPubMed Mar V, Wolfe R, Kelly JW: Predicting melanoma risk for the Australian population. Australas J Dermatol. 2011, 52 (2): 109-116. 10.1111/j.1440-0960.2010.00727.x.CrossRefPubMed
Metadata
Title
Individual risk of cutaneous melanoma in New Zealand: developing a clinical prediction aid
Authors
Mary Jane Sneyd
Claire Cameron
Brian Cox
Publication date
01-12-2014
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2014
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/1471-2407-14-359

Other articles of this Issue 1/2014

BMC Cancer 1/2014 Go to the issue
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine