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Träfflista för sökning "swepub ;lar1:(umu);pers:(Riboli Elio);pers:(Chirlaque Maria Dolores);pers:(Trichopoulou Antonia);pers:(Panico Salvatore);pers:(Agudo Antonio);pers:(Allen Naomi E)"

Search: swepub > Umeå University > Riboli Elio > Chirlaque Maria Dolores > Trichopoulou Antonia > Panico Salvatore > Agudo Antonio > Allen Naomi E

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1.
  • Schmidt, Julie A, et al. (author)
  • Insulin-like growth factor-I and risk of differentiated thyroid carcinoma in the European Prospective Investigation into Cancer and Nutrition
  • 2014
  • In: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 23:6, s. 976-985
  • Journal article (peer-reviewed)abstract
    • Background: Little is known about the causes of thyroid cancer, but insulin-like growth factor-I (IGF-I) might play an important role in its development due to its mitogenic and anti-apoptotic properties. Methods: This study prospectively investigated the association between serum IGF-I concentrations and risk of differentiated thyroid carcinoma in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition. 345 incident cases of differentiated thyroid carcinoma were individually matched to 735 controls by study centre, sex, and age, date, time, and fasting status at blood collection, follow-up duration, and for women menopausal status, use of exogenous hormones, and phase of menstrual cycle at blood collection. Serum IGF-I concentrations were measured by immunoassay, and risk of differentiated thyroid cancer in relation to IGF-I concentration was estimated using conditional logistic regression. Results: There was a positive association between IGF-I concentrations and risk of differentiated thyroid carcinoma: the odds ratio for a doubling in IGF-I concentration was 1.48 (95% confidence interval: 1.06 - 2.08; ptrend = 0.02). The positive association with IGF-I was stable over time between blood collection and cancer diagnosis. Conclusion: These findings suggest that IGF-I concentrations may be positively associated with risk of differentiated thyroid carcinoma. Impact: This study provides the first prospective evidence of a potential association between circulating IGF-I concentrations and risk of differentiated thyroid carcinoma and may prompt the further investigations needed to confirm the association.
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2.
  • Hoggart, Clive, et al. (author)
  • A Risk Model for Lung Cancer Incidence
  • 2012
  • In: Cancer Prevention Research. - Philadelphia : American Association for Cancer Research. - 1940-6207 .- 1940-6215. ; 5:6, s. 834-846
  • Journal article (peer-reviewed)abstract
    • Risk models for lung cancer incidence would be useful for prioritising individuals for screening and participation in clinical trials of chemoprevention. We present a risk model for lung cancer built using prospective cohort data from a general population which predicts individual incidence in a given time period.We build separate risk models for current and former smokers utilising 169,035 ever smokers from the multicentre European Prospective Investigation into Cancer and Nutrition (EPIC) and considered a model for never smokers. The data set was split into independent training and test sets. Lung cancer incidence was modelled using survival analysis, stratifying by age started smoking, and for former smokers, also smoking duration. Other risk factors considered were smoking intensity, ten occupational/environmental exposures previously implicated with lung cancer, and SNPs at two loci identified by genome-wide association studies of lung cancer. Individual risk in the test set was measured by the predicted probability of lung cancer incidence in the year preceding last follow-up time, predictive accuracy was measured by the area under the receiver operator characteristic curve (AUC).Utilising smoking information alone gave good predictive accuracy: the AUC and 95% confidence interval in ever smokers was 0.843 (0.810, 0.875), the Bach model applied to the same data gave an AUC of 0.775 (0.737, 0.813). Other risk factors had negligible effect on the AUC, including never smokers for whom prediction was poor.Our model is generalisable and straightforward to implement. Its accuracy can be attributed to its modelling of lifetime exposure to smoking.
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