COX MODELS WITH NONLINEAR EFFECT OF COVARIATES MEASURED WITH ERROR: A CASE STUDY OF CHRONIC KIDNEY DISEASE INCIDENCE

We propose, develop and implement the simulation extrapolation (SIMEX) methodology for Cox regression models when the log hazard function is linear in the model parameters but nonlinear in the variables measured with error (LPNE). The class of LPNE functions contains but is not limited to strata indicators, splines, quadratic and interaction terms. The first order bias correction method proposed here has the advantage that it remains computationally feasible even when the number of observations is very large and multiple models need to be explored. Theoretical and simulation results show that the SIMEX method outperforms the naive method even with small amounts of measurement error. Our methodology was motivated by and applied to the study of time to chronic kidney disease (CKD) progression as a function of baseline kidney function and applied to the Atherosclerosis Risk in Communities (ARIC), a large epidemiological cohort stud

Lifetime Risk of Lower-Extremity Peripheral Artery Disease Defined by Ankle-Brachial Index in the United States.

Background There are no available lifetime risk estimates of lower-extremity peripheral artery disease (PAD). Methods and Results Using data from 6 US community-based cohorts and the vital statistics, we estimated the prevalence and incidence of PAD, defined as an ankle-brachial index < 0.90, at each year of age from birth to 80 years for white, black, and Hispanic men and women. Then, we used Markov Monte Carlo simulations in a simulated cohort of 100 000 individuals to estimate lifetime risk of PAD. On the basis of odds ratios of PAD for traditional atherosclerotic risk factors (eg, diabetes mellitus and smoking), we developed a calculator providing residual lifetime risk of PAD. In an 80-year horizon, lifetime risks of PAD were 30.0% in black men and 27.6% in black women, but ≈19% in white men and women and ≈22% in Hispanic men and women. From another perspective, 9% of blacks were estimated to develop PAD by 60 years of age, while the same proportion was seen at ≈70 years for whites and Hispanics. The residual lifetime risk within the same race/ethnicity varied by 3.5- to 5-fold according to risk factors (eg, residual lifetime risk in 45-year-old black men was 19.9% when current smoking, diabetes mellitus, and history of cardiovascular disease were absent versus 70.4% when all were present). Conclusions In the United States, ≈30% of blacks are estimated to develop PAD during their lifetime, whereas the corresponding estimate is ≈20% for whites and Hispanics. The residual lifetime risk within the same race/ethnicity substantially varies according to traditional risk factors

Does oral sodium bicarbonate therapy improve function and quality of life in older patients with chronic kidney disease and low-grade acidosis (the BiCARB trial)? Study protocol for a randomized controlled trial

Date of acceptance: 01/07/2015 © 2015 Witham et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Acknowledgements UK NIHR HTA grant 10/71/01. We acknowledge the financial support of NHS Research Scotland in conducting this trial.Peer reviewedPublisher PD

Comparing the association of GFR estimated by the CKD-EPI and MDRD study equations and mortality: the third national health and nutrition examination survey (NHANES III)

BACKGROUND: The Chronic Kidney Disease Epidemiology Collaboration equation for estimation of glomerular filtration rate (eGFR(CKD-EPI)) improves GFR estimation compared with the Modification of Diet in Renal Disease Study equation (eGFR(MDRD)) but its association with mortality in a nationally representative population sample in the US has not been studied. METHODS: We examined the association between eGFR and mortality among 16,010 participants of the Third National Health and Nutrition Examination Survey (NHANES III). Primary predictors were eGFR(CKD-EPI) and eGFR(MDRD). Outcomes of interest were all-cause and cardiovascular disease (CVD) mortality. Improvement in risk categorization with eGFR(CKD-EPI) was evaluated using adjusted relative hazard (HR) and Net Reclassification Improvement (NRI). RESULTS: Overall, 26.9% of the population was reclassified to higher eGFR categories and 2.2% to lower eGFR categories by eGFR(CKD-EPI,) reducing the proportion of prevalent CKD classified as stage 3–5 from 45.6% to 28.8%(.) There were 3,620 deaths (1,540 from CVD) during 215,082 person-years of follow-up (median, 14.3 years). Among those with eGFR(MDRD) 30–59 ml/min/1.73 m(2), 19.4% were reclassified to eGFR(CKD-EPI) 60–89 ml/min/1.73 m(2) and these individuals had a lower risk of all-cause mortality (adjusted HR, 0.53; 95% CI, 0.34-0.84) and CVD mortality (adjusted HR, 0.51; 95% CI, 0.27-0.96) compared with those not reclassified. Among those with eGFR(MDRD) >60 ml/min/1.73 m(2), 0.5% were reclassified to lower eGFR(CKD-EPI) and these individuals had a higher risk of all-cause (adjusted HR, 1.31; 95% CI, 1.01-1.69) and CVD (adjusted HR, 1.42; 95% CI, 1.01-1.99) mortality compared with those not reclassified. Risk prediction improved with eGFR(CKD-EPI); NRI was 0.21 for all-cause mortality (p < 0.001) and 0.22 for CVD mortality (p < 0.001). CONCLUSIONS: eGFR(CKD-EPI) categories improve mortality risk stratification of individuals in the US population. If eGFR(CKD-EPI) replaces eGFR(MDRD) in the US, it will likely improve risk stratification

Family History of Exceptional Longevity Is Associated with Lower Serum Uric Acid Levels in A shkenazi J ews

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91205/1/jgs3902.pd

Improving the prognosis of patients with severely decreased glomerular filtration rate (CKD G4+): conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference.

Patients with severely decreased glomerular filtration rate (GFR) (i.e., chronic kidney disease [CKD] G4+) are at increased risk for kidney failure, cardiovascular disease (CVD) events (including heart failure), and death. However, little is known about the variability of outcomes and optimal therapeutic strategies, including initiation of kidney replacement therapy (KRT). Kidney Disease: Improving Global Outcomes (KDIGO) organized a Controversies Conference with an international expert group in December 2016 to address this gap in knowledge. In collaboration with the CKD Prognosis Consortium (CKD-PC) a global meta-analysis of cohort studies (n = 264,515 individuals with CKD G4+) was conducted to better understand the timing of clinical outcomes in patients with CKD G4+ and risk factors for different outcomes. The results confirmed the prognostic value of traditional CVD risk factors in individuals with severely decreased GFR, although the risk estimates vary for kidney and CVD outcomes. A 2- and 4-year model of the probability and timing of kidney failure requiring KRT was also developed. The implications of these findings for patient management were discussed in the context of published evidence under 4 key themes: management of CKD G4+, diagnostic and therapeutic challenges of heart failure, shared decision-making, and optimization of clinical trials in CKD G4+ patients. Participants concluded that variable prognosis of patients with advanced CKD mandates individualized, risk-based management, factoring in competing risks and patient preferences

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c

Ethnic differences in the association between blood pressure components and chronic kidney disease in middle aged and older Asian adults

10.1186/1471-2369-14-86BMC Nephrology141

Assessing risk prediction models using individual participant data from multiple studies

Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied).We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell’s concordance index, and Royston’s discrimination measure within each study; we then combine the estimates across studies using aweighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from casecontrol studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous.Lisa Pennells, Stephen Kaptoge, Ian R. White, Simon G. Thompson, Angela M. Wood and the Emerging Risk Factors Collaboration (Debbie A. Lawlor