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

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Cancer genetics
Short report
Calibration of polygenic risk scores is required prior to clinical implementation: results of three common cancers in UKB
  1. Jun Wei1,
  2. Zhuqing Shi1,
  3. Rong Na1,
  4. W Kyle Resurreccion1,
  5. Chi-Hsiung Wang1,
  6. David Duggan2,
  7. S Lilly Zheng1,
  8. Peter J Hulick3,
  9. Brian T Helfand1,
  10. Jianfeng Xu1
  1. 1 Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA
  2. 2 Affiliate of City of Hope, Translational Genomics Research Institute, Phoenix, Arizona, USA
  3. 3 Department of Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
  1. Correspondence to Dr Jianfeng Xu, Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL 60201, USA; jxu{at}northshore.org

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.

  • genetic predisposition to disease
  • genetics
  • genetic testing
  • medical oncology
  • clinical decision-making

https://doi.org/10.1136/jmedgenet-2020-107286

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    Footnotes

    • JW and ZS contributed equally.

    • Contributors Concept: JX. Data analysis: JW, ZS, RN and C-HW. Manuscript draft: JW, ZS and JX. Manuscript revision: All authors.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.