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Validation of a genetic-enhanced risk prediction model for colorectal cancer in a large community-based cohort.
Pubmed ID
36622766 (View this publication on the PubMed website)
Digital Object Identifier
Cancer Epidemiol Biomarkers Prev. 2023 Jan 9
Su YR , Sakoda LC , Jeon J , Thomas M , Lin Y , Schneider JL , Udaltsova N , Lee JK , Lansdorp-Vogelaar I , Peterse EFP , Zauber AG , Zheng J , Zheng Y , Hauser E , Baron JA , Barry EL , Bishop DT , Brenner H , Buchanan DD , Burnett-Hartman A , more Campbell PT , Casey G , Castellví-Bel S , Chan AT , Chang-Claude J , Figueiredo JC , Gallinger SJ , Giles GG , Gruber SB , Gsur A , Gunter MJ , Hampe J , Hampel H , Harrison TA , Hoffmeister M , Hua X , Huyghe JR , Jenkins MA , Keku TO , Le Marchand L , Li L , Lindblom A , Moreno V , Newcomb PA , Pharoah PDP , Platz EA , Potter JD , Qu C , Rennert G , Schoen RE , Slattery ML , Song M , van Duijnhoven FJB , Van Guelpen B , Vodicka P , Wolk A , Woods MO , Wu AH , Hayes RB , Peters U , Corley DA , Hsu L
  • Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States.
  • Kaiser Permanente Northern California, Oakland, CA, United States.
  • University of Michigan-Ann Arbor, Ann Arbor, Michigan, United States.
  • Fred Hutchinson Cancer Research Center, Seattle, United States.
  • Fred Hutchinson Cancer Research Center, Seattle, WA, United States.
  • Kaiser Permanante Northern California, oakland, CA, United States.
  • Kaiser Permanente Northern California, Oakland, California, United States.
  • Erasmus MC, Rotterdam, Netherlands.
  • Memorial Sloan Kettering Cancer Center, New York, NY, United States.
  • Fred Hutchinson Cancer Research Center, United States. more
  • VA Cooperative Studies Program Epidemiology Center, Durham Veterans Affairs Health Care System, Durham, NC, United States.
  • University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
  • Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.
  • University of Leeds, Leeds, West Yorkshire, United Kingdom.
  • German Cancer Research Center, Heidelberg, Germany.
  • University of Melbourne, Parkville, Victoria, Australia.
  • Kaiser Permanente Colorado, Aurora, CO, United States.
  • Albert Einstein College of Medicine, Bronx, NY, United States.
  • University of Virginia, Charlottesville, United States.
  • IDIBAPS, Barcelona, Spain.
  • Massachusetts General Hospital, Boston, MA, United States.
  • Cedars-Sinai Medical Center Samuel Oschin Comprehensive Cancer Institute, Los Angeles, CA, United States.
  • University Health Network, Canada.
  • Cancer Council Victoria, Melbourne, VIC, Australia.
  • City of Hope National Medical Center Center for Precision Medicine, Duarte, CA, United States.
  • Medical University of Vienna, Vienna, Austria.
  • International Agency For Research On Cancer, Lyon Cedex 08, France.
  • University Hospital Dresden, Dresden, Germany.
  • The Ohio State University, Columbus, Ohio, United States.
  • Fred Hutchinson Cancer Center, Seattle, United States.
  • University of Melbourne, Victoria, Victoria, Australia.
  • University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States.
  • University of Hawaii Cancer Center, Honolulu, Hawaii, United States.
  • Case Western Reserve University, Cleveland, United States.
  • Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
  • Catalan Institute of Oncology, Hopitalet de Llobregat, Barcelona, Spain.
  • Cedars-Sinai Medical Center, West Hollywood, CA, United States.
  • Johns Hopkins Bloomberg School of Public Health, Baltimore, United States.
  • Massey University, Wellington, New Zealand.
  • Carmel Medical Center and Faculty of Medicine, Technion, Haifa, Israel.
  • University of Pittsburgh Medical Center, Pittsburgh, PA, United States.
  • University of Utah Health Sciences Center, Salt Lake City, Utah, United States.
  • Harvard T.H. Chan School of Public Health, Boston, MA, United States.
  • Wageningen University & Research, Wageningen, Netherlands.
  • Umeå University, Umeå, Sweden.
  • Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czech Republic.
  • Karolinska Institute, Stockholm, Sweden.
  • Memorial University of Newfoundland, St. John's, NL, Canada.
  • University of Southern California, Los Angeles, California, United States.
  • New York University School of Medicine, New York, NY, United States.
  • Kaiser Permanente Southern California, Oakland, CA, United States.

BACKGROUND: 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.

METHODS: 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).

RESULTS: 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.

CONCLUSIONS: The proposed PRS-enhanced model provides a well-calibrated 5-year CRC risk prediction and improves discriminatory accuracy in the external cohort.

IMPACT: The proposed model has potential utility in risk-stratified CRC prevention.

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