NephJC short on an empagliflozin meta-analysis

Makowski et al., (2025). modelbased: An R package to make the most out of your statistical models through marginal means, marginal effects, and model predictions. Journal of Open Source Software, 10(1...

I am doing a study to assess the association between transplant factors and kidney transplant outcomes (specifically survival of the transplanted kidney) using US registry data. I’m using `cph()`. A key issue is that when looking at outcomes, most recipients are not truly independent as they are clustered by donor. Specifically, in our analysis we have 57,153 donors where both kidneys were transplanted (into different recipients) and 39,389 donors where only one kidney was transplanted into a single recipient. So our analysis on recipient outcomes has n=153,695 recipients, and 96,542 donor clusters (each of which has either 1 or 2 recipients). The focus of the research study is to assess if how the kidney was preserved impacts on kidney graft survival, and I adjust for several donor and recipient factors in the model. This is how I am currently using robcov to get cluster robust SE (from which I am calculating 95% confidence intervals) fit <- cph(Surv(time, event) ~ var1 + var2 + var3, data, x = TRUE, y = TRUE) fit_robust <- robcov(fit, cluster = data$donor_id) My understanding is that this uses the Huber-White method for updating the variance-covariance, which will increase the variance due to the clustering. I’ve seen other papers in the field use frailty terms (or other mixed effect models for non-survival outcomes). However, I think that robust SE using `robcov()` is probably a better solution here. Is this a valid approach, given the large number of clusters, but small cluster size (either 2 or 1 per cluster)? Would the same approach be valid for logistic regression and linear (fit with `ols()`)?

This article has detailed examples with complete R code for computing frequentist power for ordinal, continuous, and mixed ordinal/continuous outcomes in two-group comparisons with equal sample sizes....

Journal of Translational Medicine

Background Fecal microbiota transplantation (FMT) from humans with specific medical conditions to animal models can demonstrate causality by inducing or exacerbating pathophenotypes, linking the gut m...

Mitochondrial diseases, taking into account those that affect the processes of the respiratory

Tenofovir-induced nephrotoxicity in HIV-positive patients receiving TDF was mostly reversible after changing to TAF. Thus, TAF-containing regimens can be administered safely to HIV-positive patients w...

The association between ear and kidney abnormalities has long been recognized; however, the connection between these two disparate organs is not always straightforward. Although Alport syndrome is the...