Longitudinal Bone Loss Occurs at the Radius in CKD.

Chronic kidney disease (CKD) exposes to an increased incidence of fragility fractures. International guidelines recommend performing bone mineral density (BMD) if the results will impact treatment decisions. It remains unknown where bone loss occurs and what would preclude the longitudinal loss in patients with CKD. Here, we aimed to investigate factors influencing BMD and to analyze the longitudinal BMD changes. In the NephroTest cohort, we measured BMD at the femoral neck, total hip, lumbar spine, and proximal radius, together with circulating biomarkers and standardized measured glomerular filtration rate (mGFR) by <sup>51</sup> Cr-EDTA in a subset of patients with CKD stage 1 to 5 followed during 4.3 ± 2.0 years. A linear mixed model explored the longitudinal bone loss and the relationship of associated factors with BMD changes. A total of 858 patients (mean age 58.9 ± 15.2 years) had at least 1 and 477 had at least 2 BMD measures. At baseline, cross-sectional analysis showed a significantly lower BMD at femoral neck and total hip and a significant higher serum parathyroid hormone (PTH) along with CKD stages. Baseline age, gender, tobacco, low body mass index (BMI), and high PTH levels were significantly associated with low BMD. Longitudinal analysis during the mean 4.3 years revealed a significant bone loss at the radius only. BMD changes at the femoral neck were associated with BMI, but not CKD stages or basal PTH levels. CKD is associated with low BMD and high PTH in the cross-sectional analysis. Longitudinal bone loss occurred at the proximal radius after 4.3 years

PLoS One

Quantifying the association between lifetime exposures and the risk of developing a chronic disease is a recurrent challenge in epidemiology. Individual exposure trajectories are often heterogeneous and studying their associations with the risk of disease is not straightforward. We propose to use a latent class mixed model (LCMM) to identify profiles (latent classes) of exposure trajectories and estimate their association with the risk of disease. The methodology is applied to study the association between lifetime trajectories of smoking or occupational exposure to asbestos and the risk of lung cancer in males of the ICARE population-based case-control study. Asbestos exposure was assessed using a job exposure matrix. The classes of exposure trajectories were identified using two separate LCMM for smoking and asbestos, and the association between the identified classes and the risk of lung cancer was estimated in a second stage using weighted logistic regression and all subjects. A total of 2026/2610 cases/controls had complete information on both smoking and asbestos exposure, including 1938/1837 cases/controls ever smokers, and 1417/1520 cases/controls ever exposed to asbestos. The LCMM identified four latent classes of smoking trajectories which had different risks of lung cancer, all much stronger than never smokers. The most frequent class had moderate constant intensity over lifetime while the three others had either long-term, distant or recent high intensity. The latter had the strongest risk of lung cancer. We identified five classes of asbestos exposure trajectories which all had higher risk of lung cancer compared to men never occupationally exposed to asbestos, whatever the dose and the timing of exposure. The proposed approach opens new perspectives for the analyses of dose-time-response relationships between protracted exposures and the risk of developing a chronic disease, by providing a complete picture of exposure history in terms of intensity, duration, and timing of exposure

Regression methods for investigating risk factors of chronic kidney disease outcomes: the state of the art

Chronic kidney disease (CKD) is a progressive and usually irreversible disease. Different types of outcomes are of interest in the course of CKD such as time-to-dialysis, transplantation or decline of the glomerular filtration rate (GFR). Statistical analyses aiming at investigating the association between these outcomes and risk factors raise a number of methodological issues. The objective of this study was to give an overview of these issues and to highlight some statistical methods that can address these topics. A literature review of statistical methods published between 2002 and 2012 to investigate risk factors of CKD outcomes was conducted within the Scopus database. The results of the review were used to identify important methodological issues as well as to discuss solutions for each type of CKD outcome. Three hundred and four papers were selected. Time-to-event outcomes were more often investigated than quantitative outcome variables measuring kidney function over time. The most frequently investigated events in survival analyses were all-cause death, initiation of kidney replacement therapy, and progression to a specific value of GFR. While competing risks were commonly accounted for, interval censoring was rarely acknowledged when appropriate despite existing methods. When the outcome of interest was the quantitative decline of kidney function over time, standard linear models focussing on the slope of GFR over time were almost as often used as linear mixed models which allow various numbers of repeated measurements of kidney function per patient. Informative dropout was accounted for in some of these longitudinal analyses. This study provides a broad overview of the statistical methods used in the last ten years for investigating risk factors of CKD progression, as well as a discussion of their limitations. Some existing potential alternatives that have been proposed in the context of CKD or in other contexts are also highlighte

Representation of exposures in regression analysis and interpretation of regression coefficients: basic concepts and pitfalls

Regression models are being used to quantify the effect of an exposure on an outcome, while adjusting for potential confounders. While the type of regression model to be used is determined by the nature of the outcome variable, e.g. linear regression has to be applied for continuous outcome variables, all regression models can handle any kind of exposure variables. However, some fundamentals of representation of the exposure in a regression model and also some potential pitfalls have to be kept in mind in order to obtain meaningful interpretation of results. The objective of this educational paper was to illustrate these fundamentals and pitfalls, using various multiple regression models applied to data from a hypothetical cohort of 3000 patients with chronic kidney disease. In particular, we illustrate how to represent different types of exposure variables (binary, categorical with two or more categories and continuous), and how to interpret the regression coefficients in linear, logistic and Cox models. We also discuss the linearity assumption in these models, and show how wrongly assuming linearity may produce biased results and how flexible modelling using spline functions may provide better estimate

Urgent-start dialysis in patients referred early to a nephrologist-the CKD-REIN prospective cohort study

International audienceBACKGROUND: The lack of a well-designed prospective study of the determinants of urgent dialysis start led us to investigate its individual- and provider-related factors in patients seeing nephrologists. METHODS: CKD-REIN is a prospective cohort study that included 3033 patients with CKD (mean age, 67 years; 65% men; mean estimated glomerular filtration rate (eGFR), 32 mL/min/1.73 m2) from 40 nationally representative nephrology clinics from 2013-16, who were followed annually through 2020. Urgent-start dialysis was defined as that "initiated imminently or \textless 48 hours after presentation to correct life-threatening manifestations" according to KDIGO 2018. RESULTS: Over a 4-year (IQR, 3.0-4.8) median follow-up, 541 patients initiated dialysis with a known start status, 86 (16%) urgently. Five-year risks for the competing events of urgent and nonurgent dialysis start, pre-emptive transplantation, and death were 4%, 17%, 3%, and 15%, respectively. Fluid overload, electrolytic disorders, acute kidney injury, and post-surgery kidney function worsening were the reasons most frequently reported for urgent-start dialysis. Adjusted odds ratios (aOR) for urgent start were significantly higher in patients living alone (2.14; 95% CI, 1.08-4.25), or with low health literacy (2.22; 1.28-3.84), heart failure (2.60; 1.47-4.57), or hyperpolypharmacy (taking \textgreater 10 drugs) (2.14; 1.17-3.90), but not with age or lower eGFR at initiation. They were lower in patients with planned dialysis modality (0.46; 0.19-1.10) and more nephrologist visits in the 12 months before dialysis (0.81; 0.70-0.94) for each visit. CONCLUSIONS: This study highlights several patient- and provider-level factors that are important to address to reduce the burden of urgent-start dialysis