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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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