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Träfflista för sökning "WFRF:(Schmidt MK) "

Search: WFRF:(Schmidt MK)

  • Result 181-186 of 186
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181.
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182.
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183.
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184.
  • Yang, X, et al. (author)
  • Prospective validation of the BOADICEA multifactorial breast cancer risk prediction model in a large prospective cohort study
  • 2022
  • In: Journal of medical genetics. - : BMJ. - 1468-6244 .- 0022-2593. ; 59:12, s. 1196-1205
  • Journal article (peer-reviewed)abstract
    • The multifactorial Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) breast cancer risk prediction model has been recently extended to consider all established breast cancer risk factors. We assessed the clinical validity of the model in a large independent prospective cohort.MethodsWe validated BOADICEA (V.6) in the Swedish KARolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort including 66 415 women of European ancestry (median age 54 years, IQR 45–63; 816 incident breast cancers) without previous cancer diagnosis. We calculated 5-year risks on the basis of questionnaire-based risk factors, pedigree-structured first-degree family history, mammographic density (BI-RADS), a validated breast cancer polygenic risk score (PRS) based on 313-SNPs, and pathogenic variant status in 8 breast cancer susceptibility genes:BRCA1,BRCA2,PALB2,CHEK2,ATM,RAD51C,RAD51DandBARD1. Calibration was assessed by comparing observed and expected risks in deciles of predicted risk and the calibration slope. The discriminatory ability was assessed using the area under the curve (AUC).ResultsAmong the individual model components, the PRS contributed most to breast cancer risk stratification. BOADICEA was well calibrated in predicting the risks for low-risk and high-risk women when all, or subsets of risk factors are included in the risk prediction. Discrimination was maximised when all risk factors are considered (AUC=0.70, 95% CI: 0.66 to 0.73; expected-to-observed ratio=0.88, 95% CI: 0.75 to 1.04; calibration slope=0.97, 95% CI: 0.95 to 0.99). The full multifactorial model classified 3.6% women as high risk (5-year risk ≥3%) and 11.1% as very low risk (5-year risk <0.33%).ConclusionThe multifactorial BOADICEA model provides valid breast cancer risk predictions and a basis for personalised decision-making on disease prevention and screening.
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185.
  • Zhang, YD, et al. (author)
  • Assessment of polygenic architecture and risk prediction based on common variants across fourteen cancers
  • 2020
  • In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1, s. 3353-
  • Journal article (peer-reviewed)abstract
    • Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence.
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186.
  • 2017
  • swepub:Mat__t
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  • Result 181-186 of 186
Type of publication
journal article (183)
conference paper (1)
Type of content
peer-reviewed (173)
other academic/artistic (11)
Author/Editor
Schmidt, MK (132)
Easton, DF (124)
Hall, P (115)
Chang-Claude, J (115)
Garcia-Closas, M (115)
Czene, K (114)
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Fasching, PA (114)
Mannermaa, A (113)
Dunning, AM (111)
Bojesen, SE (109)
Wang, Q. (107)
Nevanlinna, H (107)
Andrulis, IL (106)
Hamann, U (105)
Brenner, H (104)
Southey, MC (104)
Bolla, MK (102)
Couch, FJ (102)
Pharoah, PDP (102)
Milne, RL (101)
Hopper, JL (99)
Giles, GG (97)
Margolin, S (97)
Chenevix-Trench, G (96)
Cox, A (95)
Devilee, P (95)
Dennis, J (94)
Beckmann, MW (93)
Jakubowska, A (93)
Lambrechts, D (91)
Lindblom, A (89)
Flyger, H (89)
Guenel, P (88)
Dork, T (88)
Benitez, J. (84)
Peterlongo, P (83)
Haiman, CA (83)
Lubinski, J (83)
Anton-Culver, H (82)
Brauch, H (82)
Winqvist, R (82)
Burwinkel, B (81)
Truong, T (81)
Radice, P (79)
Kosma, VM (79)
Blomqvist, C (78)
Michailidou, K (78)
Hooning, MJ (78)
Schmutzler, RK (77)
Arndt, V (76)
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University
Karolinska Institutet (183)
Lund University (61)
Uppsala University (42)
Umeå University (20)
Högskolan Dalarna (12)
University of Gothenburg (10)
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Chalmers University of Technology (6)
University of Skövde (5)
Stockholm University (4)
Linköping University (3)
Royal Institute of Technology (2)
Swedish University of Agricultural Sciences (2)
Stockholm School of Economics (1)
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Language
English (186)
Research subject (UKÄ/SCB)
Medical and Health Sciences (77)
Natural sciences (7)
Social Sciences (1)

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