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      Calibration of polygenic risk scores is required prior to clinical implementation: results of three common cancers in UKB

      , , , , , , , , ,
      Journal of Medical Genetics
      BMJ

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          Abstract

          Background

          SNP-based polygenic risk scores have recently been adopted in the clinic for risk assessment of some common diseases. Their validity is supported by a consistent trend between their percentile rank and disease risk in populations. However, for clinical use at the individual level, the reliability of score values is necessary considering they are directly used to calculate remaining lifetime risk.

          Objectives

          We assessed the reliability of polygenic score values to estimate prostate cancer (PCa), breast cancer (BCa) and colorectal cancer (CRC) risk in three incident cohorts from the UK Biobank (n>500 000).

          Methods

          Cancer-specific Genetic Risk Score (GRS), a well-established population-standardised polygenic risk score, was calculated.

          Results

          A systematic bias was found between estimated risks (GRS values) and observed risks; β (95% CI) was 0.67 (0.58–0.76), 0.74 (0.65–0.84) and 0.82 (0.75–0.89), respectively, for PCa, BCa and CRC, all significantly lower than 1.00 (perfect calibration), p<0.001. After applying a correction factor derived from a training data set, the β for corrected GRS values in an independent testing data set were 1.09 (1.05–1.13), 1.00 (0.88–1.12) and 1.08 (0.96–1.21), respectively, for PCa, BCa and CRC.

          Conclusion

          Assessing the calibration of polygenic risk scores is necessary and feasible to ensure their reliability prior to clinical implementation.

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          Author and article information

          Contributors
          Journal
          Journal of Medical Genetics
          J Med Genet
          BMJ
          0022-2593
          1468-6244
          February 18 2022
          March 2022
          March 2022
          December 21 2020
          : 59
          : 3
          : 243-247
          Article
          10.1136/jmedgenet-2020-107286
          33443076
          84b6cfed-a0e3-4b36-b1b8-6a513e7b653b
          © 2020
          History

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