A novel nephrometry scoring system for predicting peri-operative outcomes of retroperitoneal laparoscopic partial nephrectomy

Background:Although the impact of tumor complexity on peri-operative outcomes has been well established using several nephrometry scoring systems,the impact of adherent perirenal fat remains poorly defined.This study aimed to develop a novel nephrometry scoring system for predicting the peri-operative outcomes of laparoscopic partial nephrectomy(LPN)by integrating and optimizing the RENAL score(RNS)and Mayo adhesive probability(MAP)score.Methods:We retrospectively evaluated 159 patients treated with retroperitoneal LPN.The patients’demographic parameters,RNSs,and MAP scores were evaluated as potential predictors of perioperative outcomes,including operation time,estimated blood loss(EBL),and margin,ischemia,and complication(MIC)achievement rate.The independent predictors were used to develop a novel nephrometry scoring system.The predictive value and inter-observer agreement for the novel nephrometry scoring system were evaluated.Results:Tumor radius(R score),nearness to the renal sinus or collecting system(N score),and posterior perinephric fat thickness were independent predictors of peri-operative outcomes and were used to develop the RNP score.The univariate analysis revealed that the RNP score was significantly associated with operation time,EBL,and MIC achievement rate(P<0.050).The RNP score was an independent predictor of operation time(P<0.001),EBL(P=0.018),and MIC achievement rate(P=0.023)in the multivariate analysis.The RNP score was not inferior to RNS in the area under the curve for predicting peri-operative outcomes and performed better in inter-observer agreement(76.7%vs.57.8%)and kappa value(0.804 vs.0.726).Conclusion:The RNP score,combining the advantages of the RNS and MAP score,demonstrated a good predictive value for the peri-operative outcomes of retroperitoneal LPN and better inter-observer agreement.

A novel nomogram provides improved accuracy for predicting biochemical recurrence after radical prostatectomy

Background:Various prediction tools have been developed to predict biochemical recurrence(BCR)after radical prostatectomy(RP);however,few of the previous prediction tools used serum prostate-specific antigen(PSA)nadir after RP and maximum tumor diameter(MTD)at the same time.In this study,a nomogram incorporating MTD and PSA nadir was developed to predict BCR-free survival(BCRFS).Methods:A total of 337 patients who underwent RP between January 2010 and March 2017 were retrospectively enrolled in this study.The maximum diameter of the index lesion was measured on magnetic resonance imaging(MRI).Cox regression analysis was performed to evaluate independent predictors of BCR.A nomogram was subsequently developed for the prediction of BCRFS at 3 and 5 years after RP.Time-dependent receiver operating characteristic(ROC)curve and decision curve analyses were performed to identify the advantage of the new nomogram in comparison with the cancer of the prostate risk assessment post-surgical(CAPRA-S)score.Results:A novel nomogram was developed to predict BCR by including PSA nadir,MTD,Gleason score,surgical margin(SM),and seminal vesicle invasion(SVI),considering these variables were significantly associated with BCR in both univariate and multivariate analyses(P<0.05).In addition,a basic model including Gleason score,SM,and SVI was developed and used as a control to assess the incremental predictive power of the new model.The concordance index of our model was slightly higher than CAPRA-S model(0.76 vs.0.70,P=0.02)and it was significantly higher than that of the basic model(0.76 vs.0.66,P=0.001).Time-dependent ROC curve and decision curve analyses also demonstrated the advantages of the new nomogram.Conclusions:PSA nadir after RP and MTD based on MRI before surgery are independent predictors of BCR.By incorporating PSA nadir and MTD into the conventional predictive model,our newly developed nomogram significantly improved the accuracy in predicting BCRFS after RP.