Please use this identifier to cite or link to this item: https://doi.org/10.1038/s41390-019-0277-z
Title: MeSsAGe risk score: tool for renal biopsy decision in steroid-dependent nephrotic syndrome
Other Titles: Risk score model for kidney biopsy
Authors: CHAN CHANG YIEN 
LOURDES PAULA REAL RESONTOC 
Md Abdul Qader
CHAN YIONG HUAK 
LIU DESHENG, ISAAC 
LAU YEW WENG PERRY 
MYA THAN 
YEO WEE SONG 
LOH HWAI LIANG ALWIN 
TAN PUAY HOON 
WEI CHANGLI 
Jochen Reiser
Subhra K Biswas
NG KAR HUI 
YAP HUI KIM 
Keywords: Kidney Biopsy
focal segmental glomerulosclerosis
minimal change disease
Biomarkers
Issue Date: 1-Mar-2019
Publisher: Springer Nature
Citation: CHAN CHANG YIEN, LOURDES PAULA REAL RESONTOC, Md Abdul Qader, CHAN YIONG HUAK, LIU DESHENG, ISAAC, LAU YEW WENG PERRY, MYA THAN, YEO WEE SONG, LOH HWAI LIANG ALWIN, TAN PUAY HOON, WEI CHANGLI, Jochen Reiser, Subhra K Biswas, NG KAR HUI, YAP HUI KIM (2019-03-01). MeSsAGe risk score: tool for renal biopsy decision in steroid-dependent nephrotic syndrome. Pediatric Research 85 (4) : 477-483. ScholarBank@NUS Repository. https://doi.org/10.1038/s41390-019-0277-z
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Abstract: BACKGROUND: A lack of consensus exists as to the timing of kidney biopsy in children with steroid-dependent nephrotic syndrome (SDNS) where minimal change disease (MCD) predominates. This study aimed at examining the applicability of a biomarker-assisted risk score model to select SDNS patients at high risk of focal segmental glomerulosclerosis (FSGS) for biopsy. METHODS: Fifty-five patients with SDNS and biopsy-proven MCD (n = 40) or FSGS (n = 15) were studied. A risk score model was developed with variables consisting of age, sex, eGFR, suPAR levels and percentage of CD8(+) memory T cells. Following multivariate regression analysis, total risk score was calculated as sum of the products of odds ratios and corresponding variables. Predictive cut-off point was determined using receiver operator characteristics (ROC) curve analysis. RESULTS: Plasma suPAR levels in FSGS patients were significantly higher, while percentage of CD45RO(+)CD8(+)CD3(+) was significantly lower than in MCD patients and controls. ROC analysis suggests the risk score model with threshold score of 16.7 (AUC 0.84, 95% CI 0.72-0.96) was a good predictor of FSGS on biopsy. The 100% PPV cut-off was >24.0, while the 100% NPV was <13.3. CONCLUSION: A suPAR and CD8(+) memory T cell percentage-based risk score model was developed to stratify SDNS patients for biopsy and for predicting FSGS.
Source Title: Pediatric Research
URI: http://scholarbank.nus.edu.sg/handle/10635/152682
ISSN: 0031-3998
DOI: 10.1038/s41390-019-0277-z
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
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