Frontiers in Oncology · 2021 · 17 citations · 34 references
MedicineOncologyCancer EpidemiologyEpidemiologic MethodsEpidemiologyCancer RegistriesCancer RiskCancer Risk AssociationCox RegressionHazard Ratio ModelingLung Cancer EpidemiologyLung Cancer RiskPolygenic Risk Score ConstructionPolygenic Score ModelingProspective Cohort Data
BACKGROUND: The triglyceride-glucose (TyG) index is a practical substitute measure for insulin resistance (IR). The relationship between IR and lung cancer has been examined in previous studies; however, the findings have been controversial. In addition, previous studies had small sample sizes. Thus, we systematically examined the association between IR and lung cancer risk based on the UK Biobank with IR measured by the TyG index and further examined the interactions and joint effects for lung cancer. METHODS: A total of 324,334 individuals free from any type of cancer at recruitment from the UK Biobank prospective cohort were included. The participants were predominantly between 40 and 70 years old. After adjusting for relevant confounders, multivariable Cox regression models were constructed to examine the relationship between the TyG index and the risk of lung cancer. We also checked the interactions and joint effects using a polygenic risk score (PRS) for lung cancer. RESULTS: During a median follow-up of 9 years, 1,593 individuals were diagnosed with lung cancer. No association was found between the TyG index and lung cancer risk after multivariate Cox regression analysis adjusted for risk factors (hazard ratio: 0.91; 95% confidence interval: 0.64-1.18). No interaction or joint effects for genetic risk and the TyG index were observed. CONCLUSION: The TyG index was not associated with the risk of lung cancer. Our results provide limited evidence that IR is not correlated with the risk of lung cancer.
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Global cancer statistics, 2012
Lindsey A. Torre, Freddie Bray, Rebecca L. Siegel et al. · CA A Cancer Journal for Clinicians · 2015 · 27.4K citations · Full text
Marie Ng, Tom Fleming, Margaret S. Robinson et al. · The Lancet · 2014 · 12.1K citations · Full text
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Clare Bycroft, Colin Freeman, Desislava Petkova et al. · Nature · 2018 · 9.7K citations · Full text
Enzo Bonora, Giovanni Targher, Maria Alberiche et al. · Diabetes Care · 2000 · 2.5K citations · Full text