ObjectiveTo validate the Martini nomogram predicting the decline in estimated glomerular filtration rate after robotic‐assisted partial nephrectomy.MethodsEstimated glomerular filtration rate of 406 patients from a single surgeon series was calculated before robotic‐assisted partial nephrectomy and at postoperative intervals. To determine the risk group, we calculated the total score and corresponding risk of significant estimated glomerular filtration rate reduction at 15 months using the Martini nomogram. The primary outcome was a reduction in estimated glomerular filtration rate of ≥25% from preoperative levels between 1 and 12 months after surgery.ResultsThe median length of follow up for this study was 12 months (interquartile range 6–12 months). Overall, 134 (33%) patients were in the low‐, 143 (35%) in the intermediate‐, 119 (29%) in the high‐ and 10 (2%) in the very high‐risk groups. The Kaplan–Meier estimates for the probability of significant estimated glomerular filtration rate reduction by 12 months after robotic‐assisted partial nephrectomy was 12.9% in the low‐risk group, 24.0% in the intermediate‐risk group, 49.7% in the high‐risk group and 40.0% in the very high‐risk group. Harrell’s C‐index for discriminating between those with and without a significant reduction in estimated glomerular filtration rate 1–12 months after robotic‐assisted partial nephrectomy was 0.73 (95% confidence interval 0.68–0.78).ConclusionsThe risk groups proposed by the Martini nomogram are accurate in predicting those at higher risk for a >25% decline in postoperative estimated glomerular filtration rate after robotic‐assisted partial nephrectomy at 12 months.

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Introduction: Limited data exists on utilization of protein post-translational modifications as biomarkers for clear cell renal cell carcinoma (ccRCC). We employed high-throughput glycoproteomics to evaluate differential expression of glycoprotein-isoforms as novel markers for ccRCC progression-free survival (PFS). Methods: Plasma samples were obtained from 77 patients treated surgically for ccRCC. Glycoproteomic analyses were carried out after liquid chromatography tandem mass spectrometry. Age-adjusted Cox proportional hazard models were constructed to evaluate PFS. Optimized Harrells c-index was employed to dichotomize the collective for the construction of Kaplan-Meier curves. Results: The average length of follow-up was 3.4 (range: 0.04-9.83) years. Glycoproteomic analysis identified 39 glycopeptides and 14 non-glycosylated peptides that showed statistically significant (false discovery rate p ≤0.05) differential expression associated with PFS. Five of the glycosylated peptides conferred continuous hazard ratio of > 6 (range 6.3-11.6). These included prothrombin A2G2S glycan motif (HR=6.47, P=9.53E-05), immunoglobulin J chain FA2G2S2 motif (HR=10.69, P=0.001), clusterin A2G2 motif (HR=7.38, P=0.002), complement component C8A A2G2S2 motif (HR=11.59, P=0.002), and apolipoprotein M glycopeptide with non-fucosylated and non-sialylated hybrid-type glycan (HR=6.30, P=0.003). Kaplan-Meier curves based on dichotomous expression of these five glycopeptides resulted in hazard ratios of 3.9-10.7, all with p-value < 0.03. Kaplan-Meyer plot using the multivariable model comprising 3 of the markers yielded HR of 11.96 (p <0.0001). Conclusion: Differential glyco-isoform abundance of plasma proteins may be a useful source of biomarkers for the clinical course and prognosis of ccRCC.

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