1. Validation of self-reported sun exposure against electronic ultraviolet radiation dosimeters.
- Author
-
Zhang, Ran, Smit, Amelia K, Espinoza, David, Allen, Martin, Reyes-Marcelino, Gillian, Kimlin, Michael G, Lo, Serigne N, Sharman, Ashleigh R, Law, Matthew H, Kanetsky, Peter A, Mann, Graham J, and Cust, Anne E
- Subjects
- *
SUNSHINE , *DOSIMETERS , *BLAND-Altman plot , *ULTRAVIOLET radiation , *ULTRAVIOLET radiation measurement , *SOLAR ultraviolet radiation - Abstract
From the dosimeter data we derived: (i) time spent outdoors exposed to UV, defined as any 8-s measurements with UV values of >0; and (ii) total standard erythemal doses (SEDs) as a measure of UV dose. Table 1 Spearman rank correlations between weekend and weekday ultraviolet radiation (UV) exposure measured as standard erythemal doses (SEDs) using electronic UV dosimeters HT
. Validation, exposure measurement, ultraviolet radiation, dosimetry, questionnaire, skin cancer Keywords: Validation; exposure measurement; ultraviolet radiation; dosimetry; questionnaire; skin cancer EN Validation exposure measurement ultraviolet radiation dosimetry questionnaire skin cancer 324 328 5 02/16/23 20230201 NES 230201 Ultraviolet radiation (UV) exposure is the main risk factor for skin cancer[1] and skin cancer prevention research and health promotion programme evaluation relies on the accurate measurement of sun exposure using questionnaires. [Extracted from the article] - Published
- 2023
- Full Text
- View/download PDF
2. Independent evaluation of melanoma polygenic risk scores in UK and Australian prospective cohorts*.
- Author
-
Steinberg, Julia, Iles, Mark M., Lee, Jin Yee, Wang, Xiaochuan, Law, Matthew H., Smit, Amelia K., Nguyen‐Dumont, Tu, Giles, Graham G., Southey, Melissa C., Milne, Roger L., Mann, Graham J., Bishop, D. Timothy, MacInnis, Robert J., and Cust, Anne E.
- Subjects
DISEASE risk factors ,MONOGENIC & polygenic inheritance (Genetics) ,MELANOMA ,SINGLE nucleotide polymorphisms ,AGE groups ,CONFIDENCE intervals - Abstract
Summary: 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. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
3. 1036Independent evaluation of melanoma polygenic risk scores in UK and Australian prospective cohorts.
- Author
-
Steinberg, Julia, Lee, Jin Yee, Wang, Harry, Law, Matthew, Smit, Amelia, Nguyen-Dumont, Tu, Giles, Graham, Southey, Melissa, Milne, Roger, Mann, Graham, MacInnis, Robert, and Cust, Anne
- Subjects
MELANOMA ,GENETIC variation ,AGE groups ,META-analysis ,CONFIDENCE intervals - Abstract
Background To improve melanoma early detection, tools to predict personal risk based on genetic information (polygenic risk scores, PRS) have been developed, but require external validation. Methods We analysed invasive melanoma incidence in UK Biobank (UKB; n = 395,647; 1,651 cases) and the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4,765; 303 cases). Three PRS were evaluated: 68 genetic variants (SNPs) at 54 loci from a 2020 meta-analysis (PRS68); 50 SNPs significant in the 2020 meta-analysis excluding UKB (PRS50); 45 SNPs at 21 loci known pre-2020 (PRS45). 10-year melanoma risks were calculated from population-level cancer registry data by age group and sex, with and without PRS adjustment. Results All PRS were strongly associated with melanoma incidence, including after adjustment for age, sex, ethnicity, and ease of tanning. Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in UKB (ratio expected/observed cases E/O=0.65, 95% confidence interval 0.62-0.68) and MCCS (E/O=0.65, 0.57-0.73). For UKB, this was reduced by PRS-adjustment, e.g. PRS50-adjusted risks E/O=0.91 (0.87-0.95). Discriminative ability for PRS68- and PRS50-adjusted absolute risks was higher than for risks based on age and sex alone (deltaAUC 0.07-0.1, p < 0.0001), and higher than for PRS45-adjusted risks (deltaAUC 0.02-0.04, p < 0.001). Conclusions A PRS derived from a larger, more diverse meta-analysis improves melanoma risk prediction compared to an earlier PRS. Re-calibration of absolute risks may be necessary for application to specific populations. Key messages A genetic score can improve prediction of melanoma risk and might help tailor melanoma prevention and early detection strategies to different risk levels. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
Catalog
Books, media, physical & digital resourcesDiscovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.