Association of MYH9/APOL1 with chronic kidney disease in a UK population

Following the first report on the association between MYH9 gene variants and glomerular disorders [1], many studies have evaluated MYH9 loci for association with a range of kidney diseases [2]. In 2010, functional mutations in the adjacent APOL1 gene were identified as the primary variants responsible for associations with kidney disease that had previously been attributed to the MHY9 gene [3]. Nevertheless, several loci within MHY9 continue to be independently reported as risk factors for chronic kidney disease (CKD) [2, 4].

A literature review of end-stage renal disease and cachexia:Understanding experience to inform evidence-based healthcare

Introduction: Cachexia is a major cause of morbidity and mortality in people who have end-stage renal disease (ESRD). The majority of research into cachexia in ESRD has focused on the biological aspects of the syndrome and potential treatment modalities. While this research is necessary, it predominately focuses on the physical impact of cachexia in ESRD. The multi-dimensional psychosocial ramifications of this syndrome have been highlighted in other end-stage illness trajectories, but have not been systematically explored in persons who have ESRD. Aim: This paper discusses why this research is necessary, alongside further studies to help define the pathophysiology of this syndrome. Conclusion: The rich insightful data gained from understanding the patients' illness experience will positively contribute to the limited knowledge base available and inform future holistic patient-centred care delivery which recognises and responds to not only the biological but also the psychosocial impact of cachexia. © 2013 European Dialysis and Transplant Nurses Association/European Renal Care Association.

Advances in joint modelling: A review of recent developments with application to the survival of end stage renal disease patients

The use of joint modelling approaches is becoming increasingly popular when an association exists between survival and longitudinal processes. Widely recognized for their gain in efficiency, joint models also offer a reduction in bias compared with naïve methods. With the increasing popularity comes a constantly expanding literature on joint modelling approaches. The aim of this paper is to give an overview of recent literature relating to joint models, in particular those that focus on the time-to-event survival process. A discussion is provided on the range of survival submodels that have been implemented in a joint modelling framework. A particular focus is given to the recent advancements in software used to build these models. Illustrated through the use of two different real-life data examples that focus on the survival of end-stage renal disease patients, the use of the JM and joineR packages within R are demonstrated. The possible future direction for this field of research is also discussed. © 2013 International Statistical Institute.

Survival in dialysis patients is different between patients with diabetes as primary renal disease and patients with diabetes as a co-morbid condition.

AIMS/HYPOTHESIS:

A previous study in Dutch dialysis patients showed no survival difference between patients with diabetes as primary renal disease and those with diabetes as a co-morbid condition. As this was not in line with our hypothesis, we aimed to verify these results in a larger international cohort of dialysis patients.

METHODS:

For the present prospective study, we used data from the European Renal Association-European Dialysis and Transplant Association (ERA-EDTA) Registry. Incident dialysis patients with data on co-morbidities (n?=?15,419) were monitored until kidney transplantation, death or end of the study period (5 years). Cox regression was performed to compare survival for patients with diabetes as primary renal disease, patients with diabetes as a co-morbid condition and non-diabetic patients.

RESULTS:

Of the study population, 3,624 patients (24%) had diabetes as primary renal disease and 1,193 (11%) had diabetes as a co-morbid condition whereas the majority had no diabetes (n?=?10,602). During follow-up, 7,584 (49%) patients died. In both groups of diabetic patients mortality was higher compared with the non-diabetic patients. Mortality was higher in patients with diabetes as primary renal disease than in patients with diabetes as a co-morbid condition, adjusted for age, sex, country and malignancy (HR 1.20, 95% CI 1.10, 1.30). An analysis stratified by dialysis modality yielded similar results.

CONCLUSIONS/INTERPRETATION:

Overall mortality was significantly higher in patients with diabetes as primary renal disease compared with those with diabetes as a co-morbid condition. This suggests that survival in diabetic dialysis patients is affected by the extent to which diabetes has induced organ damage.