Colorectal Cancer and Central Obesity.

Importance: The proportion of colorectal cancer (CRC) cases attributable to excess weight, known as population attributable fraction (PAF), has been commonly based on measures of body mass index (BMI). Central obesity metrics, such as waist circumference (WC) and waist to hip ratio (WHR), are potentially better indicators of adiposity and have demonstrated stronger associations with CRC incidence.

Objectives: To examine PAFs of CRC cases that are attributable to high WC and WHR and compare them to those attributable to high BMI.

Improving 10-year cardiovascular risk prediction in patients with type 2 diabetes with metabolomics.

Background: Existing cardiovascular risk prediction models still have room for improvement in patients with type 2 diabetes who represent a high-risk population. This study evaluated whether adding metabolomic biomarkers could enhance the 10-year prediction of major adverse cardiovascular events (MACE) in these patients.

Methods: Data from 10,257 to 1,039 patients with type 2 diabetes from the UK Biobank (UKB) and the German ESTHER cohort, respectively, were used for model derivation, internal and external validation.

Accounting for differential exclusions in the NordICC trial discloses stronger-than-reported effects of screening colonoscopy.

Objective: Recently, results on colorectal cancer (CRC) incidence and mortality reduction by the offer of screening colonoscopy were reported for the first time from a randomized controlled trial (RCT), the Nordic-European Initiative on Colorectal Cancer (NordICC) trial. Despite randomization, there was a substantially lower proportion of post-randomization exclusions of CRC cases due to cancer registry-recorded date of diagnosis before recruitment in the invited group than in the usual-care group. We aimed to evaluate the impact of such differential exclusions on the trial's effect estimates on CRC risk.

Pathway Polygenic Risk Scores (pPRS) for the Analysis of Gene-environment Interaction.

Unlabelled: A polygenic risk score (PRS) is used to quantify the combined disease risk of many genetic variants. For complex human traits there is interest in determining whether the PRS modifies, i.e.