Genome-wide association study identifies an early onset pancreatic cancer risk locus

Early onset pancreatic cancer (EOPC) is a rare disease with a very high mortality rate. Almost nothing is known on the genetic susceptibility of EOPC, therefore we performed a genome-wide association study (GWAS) to identify novel genetic variants specific for patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) at younger ages. In the first phase, conducted on 821 cases with age of onset 6460\u2009years, of whom 198 with age of onset 6450, and 3227 controls from PanScan I-II, we observed four SNPs (rs7155613, rs2328991, rs4891017 and rs12610094) showing an association with EOPC risk (P <\u20091x10-4 ). We replicated these SNPs in the PANcreatic Disease ReseArch (PANDoRA) consortium and used additional in silico data from PanScan III and PanC4. Among these four variants rs2328991 was significant in an independent set of 855 cases with age of onset 6460\u2009years, of whom 265 with age of onset 6450, and 4142 controls from the PANDoRA consortium while in the in silico data we observed no statistically significant association. However, the resulting meta-analysis supported the association (P =\u20091.15x10-4 ). In conclusion we propose a novel variant rs2328991 to be involved in EOPC risk. Even though it was not possible to find a mechanistic link between the variant and the function, the association is supported by a solid statistical significance obtained in the largest study on EOPC genetics present so far in the literature. This article is protected by copyright. All rights reserved

Impact of smoking and smoking cessation on cardiovascular events and mortality among older adults: Meta-analysis of Individual participant data from prospective cohort studies of the CHANCES consortium

Objective: To investigate the impact of smoking and smoking cessation on cardiovascular mortality, acute coronary events, and stroke events in people aged 60 and older, and to calculate and report risk advancement periods for cardiovascular mortality in addition to traditional epidemiological relative risk measures. Design: Individual participant meta-analysis using data from 25 cohorts participating in the CHANCES consortium. Data were harmonised, analysed separately employing Cox proportional hazard regression models, and combined by meta-analysis. Results: Overall, 503?905 participants aged 60 and older were included in this study, of whom 37?952 died from Cardiovascular Diseases. Random effects meta-analysis of the association of smoking status with cardiovascular mortality yielded a summary hazard ratio of 2.07 (95% CI 1.82 to 2.36) for current smokers and 1.37 (1.25 to 1.49) for former smokers compared with never smokers. Corresponding summary estimates for risk advancement periods were 5.50 years (4.25 to 6.75) for current smokers and 2.16 years (1.38 to 2.39) for former smokers. The excess risk in smokers increased with cigarette consumption in a dose-response manner, and decreased continuously with time since smoking cessation in former smokers. Relative risk estimates for acute coronary events and for stroke events were somewhat lower than for cardiovascular mortality, but patterns were similar. Conclusions: Our study corroborates and expands evidence from previous studies in showing that smoking is a strong independent risk factor of cardiovascular events and mortality even at older age, advancing cardiovascular mortality by more than five years, and demonstrating that smoking cessation in these age groups is still beneficial in reducing the excess risk

Covariate-adjusted measures of discrimination for survival data

MOTIVATION: Discrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination statistics in censored survival data. OBJECTIVE: To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s). METHOD: We define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration. RESULTS: The proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were substantially smaller than unadjusted values. The study-specific standard deviation of baseline age was strongly associated with the unadjusted C-index and D-index but not significantly associated with the age-adjusted indices. CONCLUSIONS: The proposed estimators improve meta-analysis comparisons, are easy to implement and give a more meaningful clinical interpretation