Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Keywords: CANCER ; carcinoma ; COHORT ; EPIDEMIOLOGY ; RISK ; OBESITY ; HUMAN-PAPILLOMAVIRUS ; cholesterol ; METAANALYSIS ; VULVAR CANCER ; COMPLETENESS ; REGRESSION DILUTION ; COFACTORS ; MetS ; rare gynecological cancers
    Abstract: Background: Risk factors for rare gynecological cancers are largely unknown. Initial research has indicated that the metabolic syndrome (MetS) or individual components could play a role. Materials and methods: The Metabolic syndrome and Cancer project cohort includes 288 834 women. During an average follow-up of 11 years, 82 vulvar, 26 vaginal and 43 other rare gynecological cancers were identified. Hazard ratios (HRs) were estimated fitting Cox proportional hazards regression models for tertiles and standardized z-scores [with a mean of 0 and a standard deviation (SD) of 1] of body mass index (BMI), blood pressure, glucose, cholesterol, triglycerides and MetS. Risk estimates were corrected for random error in the measurement of metabolic factors. Results: The MetS was associated with increased risk of vulvar [HR 1.78, 95% confidence interval (CI) 1.30-2.41) and vaginal cancer (HR 1.87, 95% CI 1.07-3.25). Among separate MetS components, 1 SD increase in BMI was associated with overall risk (HR 1.43, 95% CI 1.23-1.66), vulvar (HR 1.36, 95% CI 1.11-1.69) and vaginal cancer (HR 1.79, 95% CI 1.30-2.46). Blood glucose and triglyceride concentrations were associated with increased risk of vulvar cancer (HR 1.98, 95% CI 1.10-3.58 and HR 2.09, 95% CI 1.39-3.15, respectively). Conclusion: The results from this first prospective study on rare gynecological cancers suggest that the MetS and its individual components may play a role in the development of these tumors
    Type of Publication: Journal article published
    PubMed ID: 20966183
    Signatur Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...