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Träfflista för sökning "WFRF:(Huerta Jose M.) srt2:(2017);pers:(Boutron Ruault Marie Christine)"

Sökning: WFRF:(Huerta Jose M.) > (2017) > Boutron Ruault Marie Christine

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1.
  • Ward, Heather A., et al. (författare)
  • Measured adiposity in relation to head and neck cancer risk in the European Prospective Investigation into Cancer and Nutrition
  • 2017
  • Ingår i: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. - : AMER ASSOC CANCER RESEARCH. - 1538-7755 .- 1055-9965. ; 26:6, s. 895-904
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Emerging evidence from cohort studies indicates that adiposity is associated with greater incidence of head and neck cancer (HNC). However, most studies have used self-reported anthropometry which is prone to error.METHODS: Among 363 094 participants in the European Prospective Investigation into Cancer and Nutrition study (EPIC) with measured anthropometry, there were 837 incident cases of HNC. HNC risk was examined in relation to body mass index (BMI) [lean: < 22.5 kg/m2, normal weight (reference): 22.5-24.9 kg/m2, overweight 25-29.9 kg/m2, obese: > 30 kg/m2], waist circumference (WC), hip circumference (HC) and waist to hip ratio (WHR) using Cox proportional hazards models.RESULTS: Among men, a BMI < 22.5 kg/m2 was associated with higher HNC risk [hazard ratio (HR) 1.62, 95% confidence interval (CI) 1.23 - 2.12)]; BMI was not associated with HNC among women. WC and WHR were associated with greater risk of HNC among women, (WC per 5 cm: HR 1.08, 95% CI 1.02 - 1.15; WHR per 0.1 unit: HR 1.64, 95% CI 1.38 - 1.93). After stratification by smoking status, the association for WHR was present only among smokers (p interaction 0.004). Among men, WC and WHR were associated with HNC only upon additional adjustment for BMI (WC per 5 cm: HR 1.16, 95% CI 1.07 - 1.26; WHR per 0.1 unit: HR 1.42, 95% CI 1.21 - 1.65).CONCLUSION: Central adiposity, particularly among women, may have a stronger association with HNC risk than previously estimated.IMPACT: Strategies to reduce obesity may beneficially impact HNC incidence.
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2.
  • Fortner, Renee T., et al. (författare)
  • Endometrial cancer risk prediction including serum-based biomarkers : results from the EPIC cohort
  • 2017
  • Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 140:6, s. 1317-1323
  • Tidskriftsartikel (refereegranskat)abstract
    • Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimina-tion. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigat-ed for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selec-tion process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were select-ed into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including eti-ologic markers on independent pathways and genetic markers may further improve discrimination.
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