| 1. |
- Schmidt, Julie A, et al.
(författare)
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Insulin-like growth factor-I and risk of differentiated thyroid carcinoma in the European Prospective Investigation into Cancer and Nutrition
- 2014
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 23:6, s. 976-985
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Tidskriftsartikel (refereegranskat)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.
(författare)
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A Risk Model for Lung Cancer Incidence
- 2012
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Ingår i: Cancer Prevention Research. - Philadelphia : American Association for Cancer Research. - 1940-6207 .- 1940-6215. ; 5:6, s. 834-846
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Tidskriftsartikel (refereegranskat)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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| 3. |
- Xun, Wei Wei, et al.
(författare)
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Single-nucleotide polymorphisms (5p15.33, 15q25.1, 6p22.1, 6q27 and 7p15.3) and lung cancer survival in the European Prospective Investigation into Cancer and Nutrition (EPIC).
- 2011
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Ingår i: Mutagenesis. - : Oxford University Press (OUP). - 0267-8357 .- 1464-3804. ; 26:5, s. 657-666
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Tidskriftsartikel (refereegranskat)abstract
- The single-nucleotide polymorphisms (SNPs) rs402710 (5p15.33), rs16969968 and rs8034191 (15q25.1) have been consistently identified by genome-wide association studies (GWAS) as significant predictors of lung cancer risk, while rs4324798 (6p22.1) was previously found to influence survival time in small-cell lung cancer (SCLC) patients. Using the same population of one of the original GWAS, we investigated whether the selected SNPs and 31 others (also identified in GWAS) influence survival time, assuming an additive model. The effect of each polymorphism on all cause survival was estimated in 1094 lung cancer patients, and lung cancer-specific survival in 763 patients, using Cox regression adjusted for a priori confounders and competing causes of death where appropriate. Overall, after 1558 person-years of post-diagnostic follow-up, 874 deaths occurred from all causes, including 690 from lung cancer. In the lung cancer-specific survival analysis (1102 person-years), only rs7452888 (6q27) and rs2710994 (7p15.3) modified survival, with adjusted hazard ratios of 1.19 (P = 0.009) and 1.32 (P = 0.011) respectively, taking competing risks into account. Some weak associations were identified in subgroup analysis for rs16969968 and rs8034191 (15q25.1) and rs4324798 (6p22.1) and survival in never-smokers, as well as for rs402710 in current smokers and SCLC patients. In conclusion, rs402710 (5p15.33), rs16969968 and rs8034191 (both 15q25.1) and rs4324798 (6p22.1) were found to be unrelated to survival times in this large cohort of lung cancer patients, regardless of whether the cause of death was from lung cancer or not. However, rs7452888 (6q27) was identified as a possible candidate SNP to influence lung cancer survival, while stratified analysis hinted at a possible role for rs8034191, rs16969968 (15q25.1) and rs4324798 (6p22.1) in influencing survival time in lung cancer patients who were never-smokers, based on a small sample.
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