P0729AKARDI: A NEW PREDICTIVE MODEL FOR RENAL DECAY AFTER NEPHRECTOMY
Authors: DI MARCO FEDERICO , Capitanio Umberto , Bettiga Arianna , Vago Riccardo , Cinque Alessandra , Larcher Alessandro , Dell'Antonio Giacomo , Briganti Alberto , Salonia Andrea , Pani Antonello , Montorsi Francesco , Trevisani Francesco 
Published: June 2020

Background and Aims

Radical Nephrectomy is usually associated to the risk of future development of a mild to severe chronic kidney disease stage especially for those patients who already present early stages of CKD (e.g CKD class II and IIIa). Any insight on this topic could influence the clinical decision about the surgery. But how can we know for sure the magnitude of the renal function’s decay? In this preliminary work, our aim was to identify a new model able to predict at time surgery the renal function’s variation at 1 year from the operation

Method

We collected prospectively clinical data of a group of consecutive 114 patients who underwent radical nephrectomy (RN) for the presence of a benign or malignant renal mass. We estimated Glomerular Filtration Rate (eGFR) with MDRD formula. We considered the following clinical varibles: AKI onset (according to RIFLE criteria), age, gender, presence of blood hypertension, diabetes type II and BMI. Moreover, to investigate a possible correlation between renal basal histology and renal functional decay, renal biopsies were performed on each on the healthy part of the removed kidney &gt; 3cm far from tumor. A pathological evaluation using a chronicity score (Remuzzi Score) was subsequently carried out evaluating damage on four parameters: (a) glomerular global sclerosis, (b) tubular atrophy, (c) interstitial fibrosis and (d) arterial narrowing. Statistical analysis were performed using generalized linear model (GLM), Kruskal-Wallis test and chi-square test. Multivariate analysis were applied using stepwise regressions method in order to select the best fitting model. Statistically significant correlations were considered for p-value&lt;0.05.

Results

At t0, 21% of the patients had an eGFR&gt;90ml/min/1.73m2, 45% between 60 and 90, 23% between 30 and 45, and 11% under 45. Median observed decay after 12 months was 32.8% (IQR= 17.9%:41.9%).Taking in account the eGFR decay’s percentage there was a strong correlation with AKI onset (decay increased by 22.4%, CI= 14%:30.8%, p&lt;0.0001), with Diabetes ( decay increased by 13%, CI= 2%: 24.5%, p=0.02) and with the CKD stages at t0 (p=0.0007). Considering the histology, a significative negative correlation was found with the presence of arterial narrowing (-14%, CI=-23%:-6%, p&lt;0.01) even though the whole chronicity score did not correlate (p=0.5). No significative correlations were found between the decay of eGFR and other variables such as age, gender or comorbidities. The multivariate analysis by stepwise regression, including all the significative variables from the univariate analysis, proposed as best model to predict the decay the use of AKI onset (14%, CI=6%:22%, p=0.001), arterial narrowing (-13%, CI=-22%:-5%, p=0.001) and diabetes (p=0.14) as variables.

Conclusion

A precise and reliable prediction of renal function decrease after RN represents a cornerstone for urologist and nephrologist in order to create a personalized medical approach and management.In our cohort of study, CKD stage I and II patients displayed a huge decrease of eGFR in respect to CKD stages III-IV over time. One possible biological explanation can be that the healthy kidney of the patients affected by moderate and severe CKD starts working with a compensatory mechanism before the entire removal of the kidney with cancer so that the surgical acute nephron loss does not represent a shock in comparison to healthy patients with an eGFR &gt;90 ml/min. Our preliminary study identified a new clinical and pathological panel of variables able to predict at time zero the magnitude of eGFR decay after 1 year from surgical operation. Further studies are needed in order to validate and improve this model.