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@ARTICLE{Su:186696,
      author       = {Y.-R. Su and L. C. Sakoda and J. Jeon and M. Thomas and Y.
                      Lin and J. L. Schneider and N. Udaltsova and J. K. Lee and
                      I. Lansdorp-Vogelaar and E. F. P. Peterse and A. G. Zauber
                      and J. Zheng and Y. Zheng and E. Hauser and J. A. Baron and
                      E. L. Barry and D. T. Bishop and H. Brenner$^*$ and D. D.
                      Buchanan and A. Burnett-Hartman and P. T. Campbell and G.
                      Casey and S. Castellví-Bel and A. T. Chan and J.
                      Chang-Claude$^*$ and J. C. Figueiredo and S. J. Gallinger
                      and G. G. Giles and S. B. Gruber and A. Gsur and M. J.
                      Gunter and J. Hampe and H. Hampel and T. A. Harrison and M.
                      Hoffmeister$^*$ and X. Hua and J. R. Huyghe and M. A.
                      Jenkins and T. O. Keku and L. Le Marchand and L. Li and A.
                      Lindblom and V. Moreno and P. A. Newcomb and P. D. P.
                      Pharoah and E. A. Platz and J. D. Potter and C. Qu and G.
                      Rennert and R. E. Schoen and M. L. Slattery and M. Song and
                      F. J. B. van Duijnhoven and B. Van Guelpen and P. Vodicka
                      and A. Wolk and M. O. Woods and A. H. Wu and R. B. Hayes and
                      U. Peters and D. A. Corley and L. Hsu},
      title        = {{V}alidation of a genetic-enhanced risk prediction model
                      for colorectal cancer in a large community-based cohort.},
      journal      = {Cancer epidemiology, biomarkers $\&$ prevention},
      volume       = {32},
      number       = {3},
      issn         = {1055-9965},
      address      = {Philadelphia, Pa.},
      publisher    = {AACR},
      reportid     = {DKFZ-2023-00065},
      pages        = {353–362},
      year         = {2023},
      abstract     = {Polygenic risk scores (PRS) which summarize individuals'
                      genetic risk profile may enhance targeted colorectal cancer
                      (CRC) screening. A critical step towards clinical
                      implementation is rigorous external validations in large
                      community-based cohorts. This study externally validated a
                      PRS-enhanced CRC risk model comprising 140 known CRC loci to
                      provide a comprehensive assessment on prediction
                      performance.The model was developed using 20,338 individuals
                      and externally validated in a community-based cohort
                      (n=85,221). We validated predicted 5-year absolute CRC risk,
                      including calibration using expected-to-observed case ratios
                      (E/O) and calibration plots, and discriminatory accuracy
                      using time-dependent AUC. The PRS-related improvement in
                      AUC, sensitivity and specificity were assessed in
                      individuals of age 45-74 years (screening-eligible age
                      group) and 40-49 years with no endoscopy history
                      (younger-age group).In European-ancestral individuals, the
                      predicted 5-year risk calibrated well (E/O=1.01 $(95\%CI$
                      0.91-1.13)) and had high discriminatory accuracy (AUC=0.73
                      $(95\%CI$ 0.71-0.76)). Adding the PRS to a model with age,
                      sex, family and endoscopy history improved the 5-year AUC by
                      0.06 (p-value<0.001) and 0.14 (p-value=0.05) in the
                      screening-eligible age and younger-age groups, respectively.
                      Using a risk-threshold of 5-year SEER CRC-incidence rate at
                      age 50 years, adding the PRS had a similar sensitivity but
                      improved the specificity by $11\%$ (p-value<0.001) in the
                      screening-eligible age group. In the younger-age group it
                      improved the sensitivity by $27\%$ (p-value=0.04) with
                      similar specificity.The proposed PRS-enhanced model provides
                      a well-calibrated 5-year CRC risk prediction and improves
                      discriminatory accuracy in the external cohort.The proposed
                      model has potential utility in risk-stratified CRC
                      prevention.},
      cin          = {C070 / C020},
      ddc          = {610},
      cid          = {I:(DE-He78)C070-20160331 / I:(DE-He78)C020-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:36622766},
      doi          = {10.1158/1055-9965.EPI-22-0817},
      url          = {https://inrepo02.dkfz.de/record/186696},
}