Be analyzedEarle et al. J Transl Med (2016) 14:Page 5 ofwith a linear
Be analyzedEarle et al. J Transl Med (2016) 14:Page 5 ofwith a linear mixed model for longitudinal data [24]. In the model, eGFR is the dependent variable and time is an independent variable; the model will also contain as independent variables a dummy variable for each of the two factors, a term for the two-way interaction between the two factors, and continuous covariates for various measures of oxidative stress and inflammation at baseline. The model allows for the correlation between repeated measures on the same individual, but assumes that there is independence from one subject to the next. The correlation within measurements on a given subject will be modeled using compound symmetry as well as an autoregressive correlation structure. Whichever structure gives the best fitting model to the data will be used.Results The primary hypothesis of interest in this study is whether there is an interaction between the AZD3759 site selenium and Vitamin E supplements. If interaction is present, then the effect of each supplement will have to be estimated separately in the presence and absence of the other supplement. If no interaction is present, then it will be possible to estimate the main effects of selenium and Vitamin E separately without having to take the other supplement into consideration. The effect sizes are conservative and will be based on the estimated changes from baseline to 1 year [25]. A study population of 150 will have 85 power to detect an ES of 1.0 SD, and a population of 200 will have 83 power to detect an ES of 0.85 SD PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/28854080 at a two-sided alpha level of 5 [26]. The two heritage groups will have their eGFR slopes compared over time and considered as either, (a) Caucasian and non-Caucasian, or (b) High and Low levels of oxidative stress/inflammation, with the oxidative stress and inflammation markers dichotomized at their median value. The power will not be heavily dependent on any of the assumptions; regardless of the true value of the underlying correlation among observations with subjects, of the correlation structure, of the attrition rate, or of the number of repeated measurements. Discussion Chronic kidney disease is a world-wide, major public health concern which, depending upon classification codes affects up to 1:3 patients with type 2 diabetes [27]. Chronic kidney disease is a costly complication of diabetes. In the United Kingdom, it has been estimated that 10 of its ?10 billion ( 183 billion USD) healthcare budget is spent managing diabetes and ?.5 ( 2.5 billion) on CKD and renal replacement therapy [28]. There has been a reduction in ESRD over the last decade which may be related to better management oftraditional risk factors [29]. However, diabetes remains the leading cause of ESRD and has a striking predilection for persons of non-white heritage. The 2014 United Renal Data System reported that in 2012, the incidence of ESRD amongst persons with diabetes of African (nonCaucasian) heritage was fourfold greater compared with those of white (Caucasian) origin. Of interest, the report reveals that between 2007 and 2012 there was a difference of only 2 in the prevalence of CKD between the groups. Some of the difference in kidney disease progression is explained by the relatively higher rates of hypertension and proteinuria in the patients of African origin, but is unrelated to variations in access to healthcare before dialysis [30]. However, 1:3 patients with diabetes at risk of CKD may not have increased urinary p.
