Projects per year
Abstract
Background: Previous studies suggest that polygenic risk scores (PRSs) may improve melanoma risk stratification. However, there has been limited independent validation of PRS-based risk prediction, particularly assessment of calibration (comparing predicted to observed risks). Objectives: To evaluate PRS-based melanoma risk prediction in prospective UK and Australian cohorts with European ancestry. Methods: We analysed invasive melanoma incidence in the UK Biobank (UKB; n = 395 647, 1651 cases) and a case-cohort nested within the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4765, 303 cases). Three PRSs were evaluated: 68 single-nucleotide polymorphisms (SNPs) at 54 loci from a 2020 meta-analysis (PRS68), 50 SNPs significant in the 2020 meta-analysis excluding UKB (PRS50) and 45 SNPs at 21 loci known in 2018 (PRS45). Ten-year melanoma risks were calculated from population-level cancer registry data by age group and sex, with and without PRS adjustment. Results: Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in the UKB [ratio of expected/observed cases: E/O = 0·65, 95% confidence interval (CI) 0·62–0·68] and MCCS (E/O = 0·63, 95% CI 0·56–0·72). For UKB, calibration was improved by PRS adjustment, with PRS50-adjusted risks E/O = 0·91, 95% CI 0·87–0·95. The discriminative ability for PRS68- and PRS50-adjusted absolute risks was higher than for risks based on age and sex alone (Δ area under the curve 0·07–0·10, P < 0·0001), and higher than for PRS45-adjusted risks (Δ area under the curve 0·02–0·04, P < 0·001). Conclusions: A PRS derived from a larger, more diverse meta-analysis improves risk prediction compared with an earlier PRS, and might help tailor melanoma prevention and early detection strategies to different risk levels. Recalibration of absolute risks may be necessary for application to specific populations.
Original language | English |
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Pages (from-to) | 823-834 |
Number of pages | 12 |
Journal | British Journal of Dermatology |
Volume | 186 |
Issue number | 5 |
DOIs | |
Publication status | Published - May 2022 |
Projects
- 3 Finished
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Selecting the best cancer risk prediction models
MacInnis, R. J., Winship, I. M., Terry, M. B., Milne, R. & Nguyen, T.
National Health and Medical Research Council (NHMRC) (Australia)
1/01/17 → 31/12/19
Project: Research
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Precision Public Health for major cancers - novel approaches to building the genetic, epigenetic and lifestyle knowledge base for assessing risk and prognosis
Giles, G. G., Southey, M., Jenkins, M. A. & Hopper, J. L.
National Health and Medical Research Council (NHMRC) (Australia)
1/01/15 → 31/12/19
Project: Research
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The Epidemiology of Chronic Disease, Health Interventions and DNA studies (ECHIDNAs)
Tonkin, A.
National Health and Medical Research Council (NHMRC) (Australia)
1/01/02 → 31/12/06
Project: Research