001     186696
005     20240229154902.0
024 7 _ |a 10.1158/1055-9965.EPI-22-0817
|2 doi
024 7 _ |a pmid:36622766
|2 pmid
024 7 _ |a 1055-9965
|2 ISSN
024 7 _ |a 1538-7755
|2 ISSN
024 7 _ |a altmetric:141101199
|2 altmetric
037 _ _ |a DKFZ-2023-00065
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Su, Yu-Ru
|0 0000-0001-6150-960X
|b 0
245 _ _ |a Validation of a genetic-enhanced risk prediction model for colorectal cancer in a large community-based cohort.
260 _ _ |a Philadelphia, Pa.
|c 2023
|b AACR
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1679472413_6245
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a 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.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).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.The proposed PRS-enhanced model provides a well-calibrated 5-year CRC risk prediction and improves discriminatory accuracy in the external cohort.The proposed model has potential utility in risk-stratified CRC prevention.
536 _ _ |a 313 - Krebsrisikofaktoren und Prävention (POF4-313)
|0 G:(DE-HGF)POF4-313
|c POF4-313
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
700 1 _ |a Sakoda, Lori C
|0 0000-0002-0900-5735
|b 1
700 1 _ |a Jeon, Jihyoun
|0 0000-0001-7003-3412
|b 2
700 1 _ |a Thomas, Minta
|0 0000-0001-9337-7015
|b 3
700 1 _ |a Lin, Yi
|0 0000-0001-8644-614X
|b 4
700 1 _ |a Schneider, Jennifer L
|0 0000-0002-6095-7942
|b 5
700 1 _ |a Udaltsova, Natalia
|0 0000-0002-0679-4310
|b 6
700 1 _ |a Lee, Jeffrey K
|0 0000-0001-7404-4274
|b 7
700 1 _ |a Lansdorp-Vogelaar, Iris
|0 0000-0002-9438-2753
|b 8
700 1 _ |a Peterse, Elisabeth F P
|0 0000-0002-4249-6169
|b 9
700 1 _ |a Zauber, Ann G
|0 0000-0002-1764-5994
|b 10
700 1 _ |a Zheng, Jiayin
|0 0000-0002-5559-6847
|b 11
700 1 _ |a Zheng, Yingye
|0 0000-0002-3078-4200
|b 12
700 1 _ |a Hauser, Elizabeth
|0 0000-0003-0367-9189
|b 13
700 1 _ |a Baron, John A
|0 0000-0003-3461-1056
|b 14
700 1 _ |a Barry, Elizabeth L
|0 0000-0001-9637-3036
|b 15
700 1 _ |a Bishop, D Timothy
|0 0000-0002-8752-8785
|b 16
700 1 _ |a Brenner, Hermann
|0 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2
|b 17
|u dkfz
700 1 _ |a Buchanan, Daniel D
|0 0000-0003-2225-6675
|b 18
700 1 _ |a Burnett-Hartman, Andrea
|0 0000-0003-4009-0680
|b 19
700 1 _ |a Campbell, Peter T
|0 0000-0002-5549-2036
|b 20
700 1 _ |a Casey, Graham
|0 0000-0003-1584-5551
|b 21
700 1 _ |a Castellví-Bel, Sergi
|0 0000-0003-1217-5097
|b 22
700 1 _ |a Chan, Andrew T
|0 0000-0001-7284-6767
|b 23
700 1 _ |a Chang-Claude, Jenny
|0 P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253
|b 24
|u dkfz
700 1 _ |a Figueiredo, Jane C
|0 0000-0001-8040-3341
|b 25
700 1 _ |a Gallinger, Steven J
|0 0000-0002-6998-9414
|b 26
700 1 _ |a Giles, Graham G
|0 0000-0003-4946-9099
|b 27
700 1 _ |a Gruber, Stephen B
|0 0000-0001-8656-7822
|b 28
700 1 _ |a Gsur, Andrea
|0 0000-0002-9795-1528
|b 29
700 1 _ |a Gunter, Marc J
|0 0000-0001-5472-6761
|b 30
700 1 _ |a Hampe, Jochen
|0 0000-0002-2421-6127
|b 31
700 1 _ |a Hampel, Heather
|0 0000-0001-7558-9794
|b 32
700 1 _ |a Harrison, Tabitha A
|0 0000-0002-4173-7530
|b 33
700 1 _ |a Hoffmeister, Michael
|0 P:(DE-He78)6c5d058b7552d071a7fa4c5e943fff0f
|b 34
|u dkfz
700 1 _ |a Hua, Xinwei
|0 0000-0003-2114-2975
|b 35
700 1 _ |a Huyghe, Jeroen R
|0 0000-0001-6027-9806
|b 36
700 1 _ |a Jenkins, Mark A
|0 0000-0002-8964-6160
|b 37
700 1 _ |a Keku, Temitope O
|0 0000-0003-4019-3903
|b 38
700 1 _ |a Le Marchand, Loic
|0 0000-0001-5013-980X
|b 39
700 1 _ |a Li, Li
|b 40
700 1 _ |a Lindblom, Annika
|0 0000-0001-7675-7569
|b 41
700 1 _ |a Moreno, Victor
|0 0000-0002-2818-5487
|b 42
700 1 _ |a Newcomb, Polly A
|0 0000-0001-8786-0043
|b 43
700 1 _ |a Pharoah, Paul D P
|0 0000-0001-8494-732X
|b 44
700 1 _ |a Platz, Elizabeth A
|0 0000-0003-3676-8954
|b 45
700 1 _ |a Potter, John D
|0 0000-0001-5439-1500
|b 46
700 1 _ |a Qu, Conghui
|0 0000-0003-1927-6245
|b 47
700 1 _ |a Rennert, Gad
|0 0000-0002-8512-068X
|b 48
700 1 _ |a Schoen, Robert E
|0 0000-0001-7153-2766
|b 49
700 1 _ |a Slattery, Martha L
|0 0000-0002-1655-6543
|b 50
700 1 _ |a Song, Mingyang
|0 0000-0002-1324-0316
|b 51
700 1 _ |a van Duijnhoven, Fränzel J B
|0 0000-0001-8367-2352
|b 52
700 1 _ |a Van Guelpen, Bethany
|0 0000-0002-9692-101X
|b 53
700 1 _ |a Vodicka, Pavel
|0 0000-0003-2376-1243
|b 54
700 1 _ |a Wolk, Alicja
|0 0000-0001-7387-6845
|b 55
700 1 _ |a Woods, Michael O
|0 0000-0001-8180-418X
|b 56
700 1 _ |a Wu, Anna H
|0 0000-0003-0546-902X
|b 57
700 1 _ |a Hayes, Richard B
|0 0000-0002-0918-661X
|b 58
700 1 _ |a Peters, Ulrike
|0 0000-0001-5666-9318
|b 59
700 1 _ |a Corley, Douglas A
|0 0000-0001-6132-5165
|b 60
700 1 _ |a Hsu, Li
|0 0000-0001-8168-4712
|b 61
773 _ _ |a 10.1158/1055-9965.EPI-22-0817
|g p. EPI-22-0817
|0 PERI:(DE-600)2036781-8
|n 3
|p 353–362
|t Cancer epidemiology, biomarkers & prevention
|v 32
|y 2023
|x 1055-9965
909 C O |p VDB
|o oai:inrepo02.dkfz.de:186696
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 17
|6 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 24
|6 P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 34
|6 P:(DE-He78)6c5d058b7552d071a7fa4c5e943fff0f
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF4-310
|0 G:(DE-HGF)POF4-313
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Krebsrisikofaktoren und Prävention
|x 0
914 1 _ |y 2023
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2022-11-10
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2022-11-10
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2022-11-10
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2023-08-19
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2023-08-19
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2023-08-19
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2023-08-19
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2023-08-19
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2023-08-19
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b CANCER EPIDEM BIOMAR : 2022
|d 2023-08-19
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2023-08-19
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2023-08-19
920 1 _ |0 I:(DE-He78)C070-20160331
|k C070
|l C070 Klinische Epidemiologie und Alternf.
|x 0
920 1 _ |0 I:(DE-He78)C020-20160331
|k C020
|l C020 Epidemiologie von Krebs
|x 1
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)C070-20160331
980 _ _ |a I:(DE-He78)C020-20160331
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21