SwePub
Sök i LIBRIS databas

  Utökad sökning

onr:"swepub:oai:openarchive.ki.se:10616/41406"
 

Sökning: onr:"swepub:oai:openarchive.ki.se:10616/41406" > Cumulative impact o...

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00005067naa a2200865 4500
001oai:openarchive.ki.se:10616/41406
003SwePub
008240410s2012 | |||||||||||000 ||eng|
022 a 1468-3288
0247 a 10616/414062 hdl
0247 a http://hdl.handle.net/10616/414062 URI
0247 a https://doi.org/10.1136/gutjnl-2011-3005372 DOI
040 a (SwePub)ki
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
1001 a Dunlop, Malcolm G4 aut
2451 0a Cumulative impact of 10 common genetic variants on colorectal cancer risk in 42,333 individuals from eight populations
264 c 2012-04-05
264 1a Stockholm :b Karolinska Institutet, Dept of Molecular Medicine and Surgery,c 2012
338 a electronic2 rdacarrier
520 a OBJECTIVE: Colorectal cancer (CRC) has a substantial heritable component. Common genetic variation has been shown to contribute to CRC risk. A study was conducted in a large multi-population study to assess the feasibility of CRC risk prediction using common genetic variant data combined with other risk factors. A risk prediction model was built and applied to the Scottish population using available data. DESIGN: Nine populations of European descent were studied to develop and validate CRC risk prediction models. Binary logistic regression was used to assess the combined effect of age, gender, family history (FH) and genotypes at 10 susceptibility loci that individually only modestly influence CRC risk. Risk models were generated from case-control data incorporating genotypes alone (n=39 266) and in combination with gender, age and FH (n=11 324). Model discriminatory performance was assessed using 10-fold internal cross-validation and externally using 4187 independent samples. The 10-year absolute risk was estimated by modelling genotype and FH with age- and gender-specific population risks. RESULTS: The median number of risk alleles was greater in cases than controls (10 vs 9, p<2.2×10(-16)), confirmed in external validation sets (Sweden p=1.2×10(-6), Finland p=2×10(-5)). The mean per-allele increase in risk was 9% (OR 1.09; 95% CI 1.05 to 1.13). Discriminative performance was poor across the risk spectrum (area under curve for genotypes alone 0.57; area under curve for genotype/age/gender/FH 0.59). However, modelling genotype data, FH, age and gender with Scottish population data shows the practicalities of identifying a subgroup with >5% predicted 10-year absolute risk. CONCLUSION: Genotype data provide additional information that complements age, gender and FH as risk factors, but individualised genetic risk prediction is not currently feasible. Nonetheless, the modelling exercise suggests public health potential since it is possible to stratify the population into CRC risk categories, thereby informing targeted prevention and surveillance.
7001 a Tenesa, Albert4 aut
7001 a Farrington, Susan M4 aut
7001 a Ballereau, Stephane4 aut
7001 a Brewster, David H4 aut
7001 a Koessler, Thibaud4 aut
7001 a Pharoah, Paul4 aut
7001 a Schafmayer, Clemens4 aut
7001 a Hampe, Jochen4 aut
7001 a Voelzke, Henry4 aut
7001 a Chang-Claude, Jenny4 aut
7001 a Hoffmeister, Michael4 aut
7001 a Brenner, Hermann4 aut
7001 a von Holst, Susanna4 aut
7001 a Picelli, Simone4 aut
7001 a Lindblom, Annika4 aut
7001 a Jenkins, Mark A4 aut
7001 a Hopper, John L4 aut
7001 a Casey, Graham4 aut
7001 a Duggan, David J4 aut
7001 a Newcomb, Polly A4 aut
7001 a Abuli, Anna4 aut
7001 a Bessa, Xavier4 aut
7001 a Ruiz-Ponte, Clara4 aut
7001 a Castellvi-Bel, Sergi4 aut
7001 a Niittymaeki, Iina4 aut
7001 a Tuupanen, Sari4 aut
7001 a Karhu, Auli4 aut
7001 a Aaltonen, Lauri A4 aut
7001 a Zanke, Brent4 aut
7001 a Hudson, Tom4 aut
7001 a Gallinger, Steven4 aut
7001 a Barclay, Ella4 aut
7001 a Martin, Lynn4 aut
7001 a Gorman, Maggie4 aut
7001 a Carvajal-Carmona, Luis G4 aut
7001 a Walther, Axel4 aut
7001 a Kerr, David J4 aut
7001 a Lubbe, Steven4 aut
7001 a Broderick, Peter4 aut
7001 a Chandler, Ian4 aut
7001 a Pittman, Alan4 aut
7001 a Penegar, Steven4 aut
7001 a Campbell, Harry4 aut
7001 a Tomlinson, Ian4 aut
7001 a Houlston, Richard S4 aut
7102 a Karolinska Institutet
7102 a Karolinska Institutet
7730 t Gutd Stockholm : Karolinska Institutet, Dept of Molecular Medicine and Surgeryx 1468-3288x 0017-5749
8564 u http://hdl.handle.net/10616/41406x primaryx Object in contextx freey FULLTEXT
8564 u https://europepmc.org/articles/pmc5105590?pdf=render
8564 8u http://hdl.handle.net/10616/41406
8564 8u https://doi.org/10.1136/gutjnl-2011-300537

Hitta via bibliotek

  • Gut (Sök värdpublikationen i LIBRIS)

Till lärosätets databas

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy