A Split Renal Function-Based Approach for Predicting New Baseline Glomerular Filtration Rate After Radical...

Area of Science:

• Nephrology
• Urology
• Radiology

Background:

• Accurate prediction of new baseline glomerular filtration rate (NBGFR) is crucial for managing upper tract urothelial carcinoma (UTUC) post-radical nephroureterectomy (RNU).
• Current prediction models lack split renal function (SRF) assessment, leading to modest accuracy.
• Parenchymal volume analysis (PVA) and enhancement degree are key factors in renal function.

Purpose of the Study:

• To evaluate the accuracy of an SRF-based model, PVA+, incorporating parenchymal volume analysis and enhancement degree.
• To compare the PVA+ model against other SRF-based and non-SRF-based prediction algorithms for NBGFR after RNU.
• To assess the model's performance in patients with hydronephrosis and infiltrative renal masses (IRMs).

Main Methods:

• A retrospective review of 712 UTUC patients managed with RNU (2013-2023).
• Inclusion criteria: pre-operative contrast-enhanced CT, GFR, and post-operative NBGFR.
• The PVA+ model was developed using semiautomated software for differential parenchymal volumes and enhancement, and compared with other models using a 20% accuracy threshold.

Main Results:

• The PVA+ model demonstrated superior accuracy (84%) in predicting NBGFR after RNU compared to PVA alone (79%), nuclear renal scans (73%), and a non-SRF algorithm (65%).
• Among patients with hydronephrosis, PVA+ showed significant improvement (88% accuracy) over PVA alone (61%).
• For IRMs, PVA+ showed comparable accuracy to other methods in predicting NBGFR.

Conclusions:

• The PVA+ model, integrating differential renal function and parenchymal volumes, outperforms existing methods for NBGFR prediction post-RNU.
• This model alleviates concerns about reduced accuracy in populations with hydronephrosis and IRMs.
• PVA+ can enhance patient counseling regarding systemic chemotherapy timing for high-risk UTUC.