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Using clinical and genetic risk factors for risk prediction of 8 cancers in the UK Biobank.

Jiaqi HuYixuan YeGeyu ZhouHongyu Zhao
Published in: JNCI cancer spectrum (2024)
Our models demonstrated the potential to predict cancer risk and identify high-risk individuals with great generalizability to different cancers. Our findings suggested that the polygenic risk score model is more predictive for the cancer risk of early-onset patients than for late-onset patients, while the clinical risk model is more predictive for late-onset patients. Meanwhile, combining polygenic risk scores and clinical risk factors has overall better predictive performance than using polygenic risk scores or clinical risk factors alone.
Keyphrases
  • late onset
  • early onset
  • end stage renal disease
  • risk factors
  • newly diagnosed
  • chronic kidney disease
  • peritoneal dialysis
  • prognostic factors
  • gene expression
  • young adults
  • climate change
  • risk assessment
  • genome wide