Quantifying Replicability and Consistency in Systematic Reviews

Combining Partial True Discovery Guarantee Procedures

Closed testing has recently been shown to be optimal for simultaneous true discovery proportion control. It is, however, challenging to construct true discovery guarantee procedures in such a way that it focuses power on some feature sets chosen by users based on their specific interest or expertise. We propose a procedure that allows users to target power on prespecified feature sets, that is, "focus sets." Still, the method also allows inference for feature sets chosen post hoc, that is, "nonfocus sets," for which we deduce a true discovery lower confidence bound by interpolation. Our procedure is built from partial true discovery guarantee procedures combined with Holm's procedure and is a conservative shortcut to the closed testing procedure. A simulation study confirms that the statistical power of our method is relatively high for focus sets, at the cost of power for nonfocus sets, as desired. In addition, we investigate its power property for sets with specific structures, for example, trees and directed acyclic graphs. We also compare our method with AdaFilter in the context of replicability analysis. The application of our method is illustrated with a gene ontology analysis in gene expression data.

Evaluation of N-acetyl-β-D-glucosaminidase as a prognostic marker for diabetic nephropathy in type 2 diabetics: systematic review and meta-analysis

OBJECTIVE

This review aimed to assess the utility of urinary N-acetyl-β-D-glucosaminidase (uNAG) as a prognostic biomarker for nephropathy in patients with type 2 diabetes mellitus.

METHODS

The search for relevant studies was conducted across multiple databases, including PubMed (Medline), EMBASE, LILACS, CENTRAL, IBECS, and gray literature. We employed a random effects model to calculate the standardized mean difference and 95% confidence interval. Furthermore, we assessed heterogeneity using Cochrane's Q test and Higgins' I2 statistics.

RESULTS

This review included a total of 16 articles involving 1669 patients, with 13 being case-control studies and three being cohorts. The meta-analysis conducted across all studies revealed significant heterogeneity. However, subgroup analysis of four studies indicated that an increase in uNAG among normoalbuminuric patients was associated with the development of macroalbuminuria (DMP = - 1.47; 95% CI = - 1.98 to 0.95; p < 0.00001; I2 = 45%). Conversely, it did not demonstrate effectiveness in predicting the development of microalbuminuria (DMP = 0.26; 95% CI = - 0.08 to 0.60; p = 0.13; I2 = 17%).

CONCLUSIONS

Elevated uNAG levels in normoalbuminuric patients may indicate an increased risk for the development of macroalbuminuria, but not microalbuminuria. However, the high heterogeneity observed among the studies highlights the necessity for further research to validate these findings.