A Nomogram to Predict Significant Estimated Glomerular Filtration Rate Reduction After Robotic Partial Nephrectomy

Effects of perirenal fat thickness on postoperative renal dysfunction in patients who underwent robot-assisted partial nephrectomy for renal tumours

BACKGROUND

Despite partial nephrectomy (PN) renal function preservation benefits, postoperative renal dysfunction may occur. Perirenal fat thickness (PFT) is associated with renal dysfunction such as diabetes; however, its role in renal tumour surgery is unclear. This study investigates the role of PFT in renal function after robot-assisted partial nephrectomy (RAPN).

METHODS

Pre-operative factors for postoperative renal dysfunction were analysed in 156 patients undergoing RAPN with ≥1-year follow-up. PFT measured using computed tomography categorised patients with PFT >21.0 mm (median) as high-PFT.

RESULTS

Tumour size, total R.E.N.A.L. nephrometry score and its N component, renal calyx opening, achievement of trifecta, and PFT were risk factors for renal dysfunction 1 year postoperatively. Age ≥75 years (p = 0.024), total RNS ≥7 (p = 0.036), and PFT >21.0 mm (p = 0.002) significantly correlated with postoperative renal dysfunction.

CONCLUSIONS

CT-measured PFT is a valuable predictor of postoperative renal dysfunction.

Risk Prediction Models for Renal Function Decline After Cardiac Surgery Within Different Preoperative Glomerular Filtration Rate Strata

BACKGROUND

Our goal was to create a simple risk-prediction model for renal function decline after cardiac surgery to help focus renal follow-up efforts on patients most likely to benefit.

METHODS AND RESULTS

This single-center retrospective cohort study enrolled 24 904 patients who underwent cardiac surgery from 2012 to 2019 at Fuwai Hospital, Beijing, China. An estimated glomerular filtration rate (eGFR) reduction of ≥30% 3 months after surgery was considered evidence of renal function decline. Relative to patients with eGFR 60 to 89 mL/min per 1.73 m2 (4.5% [531/11733]), those with eGFR ≥90 mL/min per 1.73 m2 (10.9% [1200/11042]) had a higher risk of renal function decline, whereas those with eGFR ≤59 mL/min per 1.73 m2 (5.8% [124/2129]) did not. Each eGFR stratum had a different strongest contributor to renal function decline: increased baseline eGFR levels for patients with eGFR ≥90 mL/min per 1.73 m2, transfusion of any blood type for patients with eGFR 60 to 89 mL/min per 1.73 m2, and no recovery of renal function at discharge for patients with eGFR ≤59 mL/min per 1.73 m2. Different nomograms were established for the different eGFR strata, which yielded a corrected C-index value of 0.752 for eGFR ≥90 mL/min per 1.73 m2, 0.725 for eGFR 60-89 mL/min per 1.73 m2 and 0.791 for eGFR ≤59 mL/min per 1.73 m2.

CONCLUSIONS

Predictors of renal function decline over the follow-up showed marked differences across the eGFR strata. The nomograms incorporated a small number of variables that are readily available in the routine cardiac surgical setting and can be used to predict renal function decline in patients stratified by baseline eGFR.

Impact of chronic kidney disease stages on surgical and functional outcomes in robot-assisted partial nephrectomy for localized renal tumors

The influence of chronic kidney disease stage on robot-assisted partial nephrectomy outcomes remains underexplored. This study aimed to assess the impact of chronic kidney disease stage on functional and surgical outcomes of robot-assisted partial nephrectomy and identify preoperative predictors of significant postoperative 1-year renal-function loss (RFL). Clinical data of 408 patients who underwent robot-assisted partial nephrectomy at Yokohama City University Hospital between 2016 and 2023 were retrospectively reviewed. The da Vinci Surgical System was applied in all patients, and outcomes assessed included surgical parameters, postoperative estimated glomerular filtration rate, trifecta and pentafecta achievements, and complications. Significant RFL was defined as estimated glomerular filtration rate reduction ≥ 25% from baseline. Higher chronic kidney disease stages correlated with older age, hypertension, diabetes, and solitary kidneys. Postoperative estimated glomerular filtration rate decline was most pronounced in patients with chronic kidney disease stages 4-5. Although the chronic kidney disease stage did not significantly affect most surgical parameters, pentafecta achievement was higher in patients with chronic kidney disease stage 3 than in those with stages 4-5. Two patients required hemodialysis after robot-assisted partial nephrectomy. Multivariable logistic regression analysis showed that preoperative hemoglobin level and maximum tumor diameter were significant predictive factors for significant RFL. In conclusion, preoperative CKD stage did not influence on surgical outcome except for pentafecta achievement. RAPN may be feasible for patients with CKD stages 4-5 because of no rapid progression to hemodialysis induction and no procedure-related mortality. Preoperative hemoglobin levels and tumor diameter emerged as predictors of significant RFL.

Development and internal validation of a nomogram predicting 3-year chronic kidney disease upstaging following robot-assisted partial nephrectomy

PURPOSE

Aim of the present study was to develop and validate a nomogram to accurately predict the risk of chronic kidney disease (CKD) upstaging at 3 years in patients undergoing robot-assisted partial nephrectomy (RAPN).

METHODS

A multi-institutional database was queried to identify patients treated with RAPN for localized renal tumor (cT1-cT2, cN0, cM0). Significant CKD upstaging (sCKD-upstaging) was defined as development of newly onset CKD stage 3a, 3b, and 4/5. Model accuracy was calculated according to Harrell C-index. Subsequently, internal validation using bootstrapping and calibration was performed. Then nomogram was depicted to graphically calculate the 3-year sCKD-upstaging risk. Finally, regression tree analysis identified potential cut-offs in nomogram-derived probability. Based on this cut-off, four risk classes were derived with Kaplan-Meier analysis tested this classification.

RESULTS

Overall, 965 patients were identified. At Kaplan-Meier analysis, 3-year sCKD-upstaging rate was 21.4%. The model included baseline (estimated glomerular filtration rate) eGFR, solitary kidney status, multiple lesions, R.E.N.A.L. nephrometry score, clamping technique, and postoperative acute kidney injury (AKI). The model accurately predicted 3-year sCKD-upstaging (C-index 84%). Based on identified nomogram cut-offs (7 vs 16 vs 26%), a statistically significant increase in sCKD-upstaging rates between low vs intermediate favorable vs intermediate unfavorable vs high-risk patients (1.3 vs 9.2 vs 22 vs 54.2%, respectively, p < 0.001) was observed.

CONCLUSION

Herein we introduce a novel nomogram that can accurately predict the risk of sCKD-upstaging at 3 years. Based on this nomogram, it is possible to identify four risk categories. If externally validated, this nomogram may represent a useful tool to improve patient counseling and management.

Low rate of severe-end-stage kidney disease after SABR for localised primary kidney cancer

BACKGROUND

Stereotactic ablative body radiotherapy (SABR) is an emerging treatment for patients with primary renal cell carcinoma (RCC). However, its impact on renal function is unclear. This study aimed to evaluate incidence and clinical factors predictive of severe to end-stage chronic kidney disease (CKD) after SABR for RCC.

METHODS AND MATERIALS

This was a Single institutional retrospective analysis of patients with diagnosed primary RCC receiving SABR between 2012-2020. Adult patients with no metastatic disease, baseline estimated glomerular filtration rate (eGFR) of ≥ 30 ml/min/1.73 m2, and at least one post-SABR eGFR at six months or later were included in this analysis. Patients with upper tract urothelial carcinoma were excluded. Primary outcome was freedom from severe to end-stage CKD, determined using the Kaplan-Meier estimator. The impact of baseline CKD, age, hypertension, diabetes, tumor size and fractionation schedule were assessed by Cox proportional hazard models.

RESULTS

Seventy-eight consecutive patients were included, with median age of 77.8 years (IQR 70-83), tumor size of 4.5 cm (IQR 3.9-5.8) and follow-up of 42.2 months (IQR 23-60). Baseline median eGFR was 58 mls/min; 55% (n = 43) of patients had baseline CKD stage 3 and the remainder stage 1-2. By last follow-up, 1/35 (2.8%) of baseline CKD 1-2, 7/27 (25.9%) CKD 3a and 11/16 (68.8%) CKD 3b had developed CKD stage 4-5. The estimated probability of freedom from CKD stage 4-5 at 1 and 5 years was 89.6% (CI 83.0-97.6) and 65% (CI 51.4-81.7) respectively. On univariable analysis, worse baseline CKD (p < 0.0001) and multi-fraction SABR (p = 0.005) were predictive for development of stage 4-5 CKD though only the former remained significant in multivariable model.

CONCLUSION

In this elderly cohort with pre-existing renal dysfunction, SABR achieved satisfactory nephron sparing with acceptable rates of severe to end-stage CKD. It can be an attractive option in patients who are medically inoperable.

Practical Prediction of New Baseline Renal Function After Partial Nephrectomy

BACKGROUND

Partial nephrectomy (PN) is generally preferred for localized renal masses due to strong functional outcomes. Accurate prediction of new baseline glomerular filtration rate (NBGFR) after PN may facilitate preoperative counseling because NBGFR may affect long-term survival, particularly for patients with preoperative chronic kidney disease. Methods for predicting parenchymal volume preservation, and by extension NBGFR, have been proposed, including those based on contact surface area (CSA) or direct measurement of tissue likely to be excised/devascularized during PN. We previously reported that presuming 89% of global GFR preservation (the median value saved from previous, independent analyses) is as accurate as the more subjective/labor-intensive CSA and direct measurement approaches. More recently, several promising complex/multivariable predictive algorithms have been published, which typically include tumor, patient, and surgical factors. In this study, we compare our conceptually simple approach (NBGFRPost-PN = 0.90 × GFRPre-PN) with these sophisticated algorithms, presuming that an even 90% of the global GFR is saved with each PN.

PATIENTS AND METHODS

A total of 631 patients with bilateral kidneys who underwent PN at Cleveland Clinic (2012-2014) for localized renal masses with available preoperative/postoperative GFR were analyzed. NBGFR was defined as the final GFR 3-12 months post-PN. Predictive accuracies were assessed from correlation coefficients (r) and mean squared errors (MSE).

RESULTS

Our conceptually simple approach based on uniform 90% functional preservation had equivalent r values when compared with complex, multivariable models, and had the lowest degree of error when predicting NBGFR post-PN.

CONCLUSIONS

Our simple formula performs equally well as complex algorithms when predicting NBGFR after PN. Strong anchoring by preoperative GFR and minimal functional loss (≈ 10%) with the typical PN likely account for these observations. This formula is practical and can facilitate counseling about expected postoperative functional outcomes after PN.

Performance of Future Glomerular Filtration Rate Equation by Race in a Large, Racially Diverse Patient Cohort Undergoing Nephrectomy for Renal Cell Carcinoma

OBJECTIVE

To examine the performance of the Palacios et al [Aguilar Palacios D, Wilson B, Ascha M, et al. New baseline renal function after radical or partial nephrectomy: a simple and accurate predictive model. J Urol. 2021;205:1310-1320] post-nephrectomy future glomerular function rate (fGFR) equation in a diverse cohort using both the Chronic Kidney Disease Epidemiology (CKD-EPI) 2009 equation with race, used in the creation of the formula, as well as the CKD-EPI 2021 equation without race.

METHODS

Patients who underwent partial or radical nephrectomy for renal cell carcinoma from 2005-2021 were identified in our institutional database. Patients with creatinine values preoperatively and 3-12 months postoperatively were included. Correlation/bias/accuracy/precision of the fGFR equation (fGFR = 35+ [preoperative eGFR × 0.65] - 18 [if radical] - [age × 0.25] + 3 [if tumor >7 cm] - 2 [if diabetes]) with observed postoperative eGFR was determined by both the CKD-EPI-2021 and CKD-EPI 2009 equations.

RESULTS

A total of 1443 patients were analyzed. Seventy-one percent (1024) were White and 22.9% (331) were Black. Most underwent radical nephrectomy (60.3%). 40% T3-T4 renal cell carcinoma (RCC), with 14.8% of patients having M1 disease. Median observed vs predicted fGFR was 58.0 vs 58.7 mL/min/1.73 m2 for CKD-EPI 2021 and 56.0 vs 57.5 for CKD-EPI 2009. For the total cohort, the correlation/bias/accuracy/precision of the fGFR equation was 0.805/-0.5/81.7/7.9-9.0 for CKD-EPI 2021 and 0.809/-0.8/81.3/-8.1 to 8 for CKD-EPI 2009. In Black patients, fGFR equation demonstrated >75% accuracy with both CKD-EPI equations; however, accuracy was lower in black patients with the CKD-EPI2021 equation (76.1% vs 83.4%, P = .003).

CONCLUSION

The fGFR equation performed well in our large, diverse cohort, though accuracy was relatively lower when using CKD-EPI 2021 compared to CKD-EPI 2009.

A Predictive Model for Kidney Failure After Nephrectomy for Localized Kidney Cancer: The Kidney Cancer Risk Equation

RATIONALE & OBJECTIVE

Nephrectomy is the mainstay of treatment for individuals with localized kidney cancer. However, surgery can potentially result in the loss of kidney function or in kidney failure requiring dialysis/kidney transplantation. There are currently no clinical tools available to preoperatively identify which patients are at risk of kidney failure over the long term. Our study developed and validated a prediction equation for kidney failure after nephrectomy for localized kidney cancer.

STUDY DESIGN

Population-level cohort study.

SETTING & PARTICIPANTS

Adults (n=1,026) from Manitoba, Canada, with non-metastatic kidney cancer diagnosed between January 1, 2004, and December 31, 2016, who were treated with either a partial or radical nephrectomy and had at least 1 estimated glomerular filtration rate (eGFR) measurement before and after nephrectomy. A validation cohort included individuals in Ontario (n=12,043) with a diagnosis of localized kidney cancer between October 1, 2008, and September 30, 2018, who received a partial or radical nephrectomy and had at least 1 eGFR measurement before and after surgery.

NEW PREDICTORS & ESTABLISHED PREDICTORS

Age, sex, eGFR, urinary albumin-creatinine ratio, history of diabetes mellitus, and nephrectomy type (partial/radical).

OUTCOME

The primary outcome was a composite of dialysis, transplantation, or an eGFR<15mL/min/1.73m2 during the follow-up period.

ANALYTICAL APPROACH

Cox proportional hazards regression models evaluated for accuracy using area under the receiver operating characteristic curve (AUC), Brier scores, calibration plots, and continuous net reclassification improvement. We also implemented decision curve analysis. Models developed in the Manitoba cohort were validated in the Ontario cohort.

RESULTS

In the development cohort, 10.3% reached kidney failure after nephrectomy. The final model resulted in a 5-year area under the curve of 0.85 (95% CI, 0.78-0.92) in the development cohort and 0.86 (95% CI, 0.84-0.88) in the validation cohort.

LIMITATIONS

Further external validation needed in diverse cohorts.

CONCLUSIONS

Our externally validated model can be easily applied in clinical practice to inform preoperative discussions about kidney failure risk in patients facing surgical options for localized kidney cancer.

PLAIN-LANGUAGE SUMMARY

Patients with localized kidney cancer often experience a lot of worry about whether their kidney function will remain stable or will decline if they choose to undergo surgery for treatment. To help patients make an informed treatment decision, we developed a simple equation that incorporates 6 easily accessible pieces of patient information to predict the risk of reaching kidney failure 5 years after kidney cancer surgery. We expect that this tool has the potential to inform patient-centered discussions tailored around individualized risk, helping ensure that patients receive the most appropriate risk-based care.

Development of a novel score (RENSAFE) to determine probability of acute kidney injury and renal functional decline post surgery: A multicenter analysis

OBJECTIVE

To create and validate 2 models called RENSAFE (RENalSAFEty) to predict postoperative acute kidney injury (AKI) and development of chronic kidney disease (CKD) stage 3b in patients undergoing partial (PN) or radical nephrectomy (RN) for kidney cancer.

METHODS

Primary objective was to develop a predictive model for AKI (reduction >25% of preoperative eGFR) and de novo CKD≥3b (<45 ml/min/1.73m2), through stepwise logistic regression. Secondary outcomes include elucidation of the relationship between AKI and de novo CKD≥3a (<60 ml/min/1.73m2). Accuracy was tested with receiver operator characteristic area under the curve (AUC).

RESULTS

AKI occurred in 452/1,517 patients (29.8%) and CKD≥3b in 116/903 patients (12.8%). Logistic regression demonstrated male sex (OR = 1.3, P = 0.02), ASA score (OR = 1.3, P < 0.01), hypertension (OR = 1.6, P < 0.001), R.E.N.A.L. score (OR = 1.2, P < 0.001), preoperative eGFR<60 (OR = 1.8, P = 0.009), and RN (OR = 10.4, P < 0.0001) as predictors for AKI. Age (OR 1.0, P < 0.001), diabetes mellitus (OR 2.5, P < 0.001), preoperative eGFR <60 (OR 3.6, P < 0.001) and RN (OR 2.2, P < 0.01) were predictors for CKD≥3b. AUC for RENSAFE AKI was 0.80 and 0.76 for CKD≥3b. AKI was predictive for CKD≥3a (OR = 2.2, P < 0.001), but not CKD≥3b (P = 0.1). Using 21% threshold probability for AKI achieved sensitivity: 80.3%, specificity: 61.7% and negative predictive value (NPV): 88.1%. Using 8% cutoff for CKD≥3b achieved sensitivity: 75%, specificity: 65.7%, and NPV: 96%.

CONCLUSION

RENSAFE models utilizing perioperative variables that can predict AKI and CKD may help guide shared decision making. Impact of postsurgical AKI was limited to less severe CKD (eGFR<60 ml/min 71.73m2). Confirmatory studies are requisite.

A new machine-learning model to predict long-term renal function impairment after minimally invasive partial nephrectomy: the Fundació Puigvert predictive model

PURPOSE

To provide a new model to predict long-term renal function impairment after partial nephrectomy (PN).

METHODS

Data of consecutive patients who underwent minimally invasive PN from 2005 to 2022 were analyzed. A minimum of 12 months of follow-up was required. We relied on a machine-learning algorithm, namely classification and regression tree (CART), to identify the predictors and associated clusters of chronic kidney disease (CKD) stage migration during follow-up.

RESULTS

568 patients underwent minimally invasive PN at our center. A total of 381 patients met our inclusion criteria. The median follow-up was 69 (IQR 38-99) months. A total of 103 (27%) patients experienced CKD stage migration at last follow-up. Progression of CKD stage after surgery, ACCI and baseline CKD stage were selected as the most informative risk factors to predict CKD progression, leading to the creation of four clusters. The progression of CKD stage rates for cluster #1 (no progression of CKD stage after surgery, baseline CKD stage 1-2, ACCI 1-4), #2 (no progression of CKD stage after surgery, baseline CKD stage 1-2, ACCI ≥ 5), #3 (no progression of CKD stage after surgery and baseline CKD stage 3-4-5) and #4 (progression of CKD stage after surgery) were 6.9%, 28.2%, 37.1%, and 69.6%, respectively. The c-index of the model was 0.75.

CONCLUSION

We developed a new model to predict long-term renal function impairment after PN where the perioperative loss of renal function plays a pivotal role to predict lack of functional recovery. This model could help identify patients in whom functional follow-up should be intensified to minimize possible worsening factors of renal function.

The Association of Ischemia Type and Duration with Acute Kidney Injury after Robot-Assisted Partial Nephrectomy

BACKGROUND

Acute kidney injury (AKI) after robot-assisted partial nephrectomy (RAPN) is a robust surrogate for chronic kidney disease. The objective of this study was to evaluate the association of ischemia type and duration during RAPN with postoperative AKI.

MATERIALS AND METHODS

We reviewed all patients who underwent RAPN at our institution since 2011. The ischemia types were warm ischemia (WI), selective artery clamping (SAC), and zero ischemia (ZI). AKI was defined according to the Risk Injury Failure Loss End-Stage (RIFLE) criteria. We calculated ischemia time thresholds for WI and SAC using the Youden and Liu indices. Logistic regression and decision curve analyses were assessed to examine the association with AKI.

RESULTS

Overall, 154 patients met the inclusion criteria. Among all RAPNs, 90 (58.4%), 43 (28.0%), and 21 (13.6%) were performed with WI, SAC, and ZI, respectively. Thirty-three (21.4%) patients experienced postoperative AKI. We extrapolated ischemia time thresholds of 17 min for WI and 29 min for SAC associated with the occurrence of postoperative AKI. Multivariable logistic regression analyses revealed that WIT ≤ 17 min (odds ratio [OR] 0.1, p < 0.001), SAC ≤ 29 min (OR 0.12, p = 0.002), and ZI (OR 0.1, p = 0.035) significantly reduced the risk of postoperative AKI.

CONCLUSIONS

Our results confirm the commonly accepted 20 min threshold for WI time, suggest less than 30 min ischemia time when using SAC, and support a ZI approach if safely performable to reduce the risk of postoperative AKI. Selecting an appropriate ischemia type for patients undergoing RAPN can improve short- and long-term functional kidney outcomes.

Risk factors and predictive model for acute kidney Injury Transition to acute kidney disease in patients following partial nephrectomy

PURPOSE

Acute kidney disease (AKD) is believed to be involved in the transition from acute kidney injury (AKI) to chronic kidney disease in general populations, but little is understood about this possibility among kidney surgical populations. This study aimed to elucidate the incidence of AKD after partial nephrectomy and risk factors that promote the AKI to AKD transition.

METHODS

From January 2010 to January 2020, this study retrospectively collected a dataset of consecutive patients with renal masses undergoing partial nephrectomy in 4 urological centers. Cox proportional regression analyses were adopted to identify risk factors that promoted the AKI to AKD transition. To avoid overfitting, the results were then verified by logistic least absolute shrinkage and selection operator (LASSO) regression. A nomogram was then constructed and validated for AKI to AKD transition prediction.

RESULTS

AKI and AKD occurred in 228 (21.4%) and 42 (3.9%) patients among a total of 1062 patients, respectively. In patients with AKI, multivariable Cox regression analysis and LASSO regression identified that age (HR 1.078, 1.029-1.112, p < 0.001), baseline eGFR (HR 1.015, 1.001-1.030, p < 0.001), RENAL score (HR1.612, 1.067-2.437, p = 0.023), ischemia time > 30 min (HR 7.284, 2.210-23.999, p = 0.001), and intraoperative blood loss > 300ml (HR 8.641, 2.751-27.171, p < 0.001) were risk factors for AKD transition. These five risk factors were then integrated into a nomogram. The nomogram showed excellent discrimination, calibration, and clinical net benefit ability.

CONCLUSION

Around 3.9% patients following partial nephrectomy would transit from AKI to AKD. Intraoperative blood loss and ischemia time need to be diminished to avoid on-going functional decline. Our nomogram can accurately predict the transition from AKI to AKD.

Morbidity of elective surgery for localized renal masses among elderly patients: A contemporary multicenter study

BACKGROUND

The aging population and the incidence of renal cell carcinoma (RCC) are increasing worldwide. Over 25% of newly diagnosed LRM (localized renal masses) occur in patients over the eighth decade of life. The decision-making and treatment approach to LRM in this population represents a clinical dilemma due to inherited decreased functional reserve and competing mortality risks. Current literature reports conflicting evidence regarding age as a risk factor for worst surgical outcomes. As such, we aimed to evaluate the contemporary morbidity of elective surgery for LRM among elderly patients, focusing on intraoperative and postoperative complications.

METHODS

After Ethical Committee approval, we queried our prospectively maintained databases to identify patients with preoperative eGFR ≥60 ml/min/1.73 m [(David and Bloom, 2022) 22 and a normal contralateral kidney who underwent partial or radical nephrectomy (PN or RN) for a single cT1-T2N0M0 LRM between 1/2015-12/2021 at four high-volume European Academic Institutions. Patients were categorized by age groups: <50 yrs (young) vs. 50-75 (middle-aged) yrs vs.> 75 yrs (elderly). Postoperative complications were recorded according to Clavien-Dindo (CD) classification. The primary objectives were the proportion of patients experiencing intraoperative (IOC), any grade (AGC), and high-grade postoperative complications (HGC), defined as CD grade 3-5.

RESULTS

Overall, 2469/3076 (80.2%) patients met the inclusion criteria. Of these, 363 (14.7%) were young, 1682 (68.1%) were middle-aged, and 424 (17.2%) were elderly. Compared to middle-aged and young patients, elderly patients had a higher median Charlson Comorbidity Index (6 vs. 4 vs. 0, p < 0.01) and a higher proportion of cT1 renal mass (87.6% vs. 93.0% vs. 93.6%, p < 0.01). No differences among the study groups were found regarding surgical approach (open vs. minimally-invasive) and type of surgery (PN vs. RN). We found that older patients experienced similar IOC (4.5% vs. 4.2% vs. 3.3%, p = 0.7) and AGC (23.1% vs. 20.0% vs. 21.5%, p = 0.4) compared to middle-aged and young patients, respectively. Similarly, there were no significant differences in HGC between the study cohorts (0.7% vs. 1.4% vs. 1.7%, p = 0.8). At multivariable analysis, open approach and PN significantly predicted the occurrence of AGCs, while only the open surgical approach was associated with the occurrence of HGCs.

CONCLUSION

In kidney cancer tertiary referral centers, the risk of IOC and postoperative HGC after PN or RN for localized renal masses (LRM) is low, despite a non-negligible risk of AGC, especially in elderly patients. Further efforts should focus on identifying multidisciplinary strategies to select patients most likely to benefit from surgery among elderly candidates with LRMs and decrease the morbidity of surgery in this specific setting.

New-onset Chronic Kidney Disease After Surgery for Localised Renal Masses in Patients with Two Kidneys and Preserved Renal Function: A Contemporary Multicentre Study

Background

There is a lack of evidence on acute kidney injury (AKI) and new-onset chronic kidney disease (CKD) after surgery for localised renal masses (LRMs) in patients with two kidneys and preserved baseline renal function.

Objective

To evaluate the prevalence and risk of AKI and new-onset clinically significant CKD (csCKD) in patients with a single renal mass and preserved renal function after being treated with partial (PN) or radical (RN) nephrectomy.

Design setting and participants

We queried our prospectively maintained databases to identify patients with a preoperative estimated glomerular filtration rate (eGFR) of ≥60 ml/min/1.73 m² and a normal contralateral kidney who underwent PN or RN for a single LRM (cT1-T2N0M0) between January 2015 and December 2021 at four high-volume academic institutions.

Intervention

PN or RN.

Outcome measurements and statistical analysis

The outcomes of this study were AKI at hospital discharge and the risk of new-onset csCKD, defined as eGFR <45 ml/min/1.73 m², during the follow-up. Kaplan-Meier curves were used to examine csCKD-free survival according to tumour complexity. A Multivariable logistic regression analysis assessed the predictors of AKI, while a multivariable Cox regression analysis assessed the predictors of csCKD. Sensitivity analyses were performed in patients who underwent PN.

Results and limitations

Overall, 2469/3076 (80%) patients met the inclusion criteria. At hospital discharge, 371/2469 (15%) developed AKI (8.7% vs 14% vs 31% in patients with low- vs intermediate- vs high-complexity tumours, p < 0.001). At the multivariable analysis, body mass index, history of hypertension, tumour complexity, and RN significantly predicted the occurrence of AKI. Among 1389 (56%) patients with complete follow-up data, 80 events of csCKD were recorded. The estimated csCKD-free survival rates were 97%, 93% and 86% at 12, 36, and 60 mo, respectively, with significant differences between patients with high- versus low-complexity and high- versus intermediate-complexity tumours (p = 0.014 and p = 0.038, respectively). At the Cox regression analysis, age-adjusted Charlson Comorbidity Index, preoperative eGFR, tumour complexity, and RN significantly predicted the risk of csCKD during the follow-up. The results were similar in the PN cohort. The main limitation of the study was the lack of data on eGFR trajectories within the 1st year after surgery and on long-term functional outcomes.

Conclusions

The risk of AKI and de novo csCKD in elective patients with an LRM and preserved baseline renal function is not clinically negligible, especially in those with higher-complexity tumours. While baseline nonmodifiable patient/tumour-related characteristics modulate this risk, PN should be prioritised over RN to maximise nephron preservation if oncological outcomes are not jeopardised.

Patient summary

In this study, we evaluated how many patients with a localised renal mass and two functioning kidneys, who were candidates for surgery at four referral European centres, experienced acute kidney injury at hospital discharge and significant renal functional impairment during the follow-up. We found that the risk of acute kidney injury and clinically significant chronic kidney disease in this patient population is not negligible, and was associated with specific baseline patient comorbidities, preoperative renal function, tumour anatomical complexity, and surgery-related factors, in particular the performance of radical nephrectomy.

External validation of yonsei nomogram predicting chronic kidney disease development after partial nephrectomy: An international, multicenter study

OBJECTIVE

To externally validate Yonsei nomogram.

METHODS

From 2000 through 2018, 3526 consecutive patients underwent on-clamp PN for cT1 renal masses at 23 centers were included. All patients had two kidneys, preoperative eGFR ≥60 ml/min/1.73 m2, and a minimum follow-up of 12 months. New-onset CKD was defined as upgrading from CKD stage I or II into CKD stage ≥III. We obtained the CKD-free progression probabilities at 1, 3, 5, and 10 years for all patients by applying the nomogram found at https://eservices.ksmc.med.sa/ckd/. Thereafter, external validation of Yonsei nomogram for estimating new-onset CKD stage ≥III was assessed by calibration and discrimination analysis.

RESULTS AND LIMITATION

Median values of patients' age, tumor size, eGFR and follow-up period were 47 years (IQR: 47-62), 3.3 cm (IQR: 2.5-4.2), 90.5 ml/min/1.73 m2 (IQR: 82.8-98), and 47 months (IQR: 27-65), respectively. A total of 683 patients (19.4%) developed new-onset CKD. The 5-year CKD-free progression rate was 77.9%. Yonsei nomogram demonstrated an AUC of 0.69, 0.72, 0.77, and 0.78 for the prediction of CKD stage ≥III at 1, 3, 5, and 10 years, respectively. The calibration plots at 1, 3, 5, and 10 years showed that the model was well calibrated with calibration slope values of 0.77, 0.83, 0.76, and 0.75, respectively. Retrospective database collection is a limitation of our study.

CONCLUSIONS

The largest external validation of Yonsei nomogram showed good calibration properties. The nomogram can provide an accurate estimate of the individual risk of CKD-free progression on long-term follow-up.

Predictive Factors for Acute Kidney Injury and Long-Term Renal Function Loss After Partial Nephrectomy: A Prospective Single-Center Study

OBJECTIVE

To find factors related to postoperative acute kidney injury and long-term significant renal function (RF) loss after partial nephrectomy (PN) in Chinese population.

METHODS

The main outcome was significant RF loss during the last follow-up, which was defined as >25% decrease in estimated glomerular filtration rate.

RESULTS

A total of 416 patients were included with median age as 57 (interquartile ranges,IQR 49.8-65.0) year with body mass index as 24.2 (IQR 22.0-26.5) kg/m² and preoperative estimated glomerular filtration rate as 90.5 (IQR 79.8-101) mL/min. Summarily, 259 (62.3%) patients were male, 54 (13%) had diabetes, 180 (43.3%) hypertension and 80 (19.2%) hyperuricemia. Median (IQR) tumor diameter was 3.1 (2.4-4.1) cm. All patients underwent PN, in which 135 (32.5%) by open PN approach, 109 (26.2%) by laparoscopic PN and 172 (41.3%) by robot assisted PN. RF was followed up for 16.88 (10.15-36.37) months, where 58 (13.9%) patients suffered significant RF loss. Multivariable analysis showed age (P = .0039), body mass index (P = .0049), diabetes (P = .0351), operative time > 110 minutes (P = .0034), diameter classification by Diameter-Axial-Polar score (diameter 2.4 cm-4.4 cm, P = .0225: diameter > 4.4 cm, P = .0207), postoperative acute kidney injury (P < .001) to be predictors of RF loss with area under the curve as 0.850.

CONCLUSION

We prospectively found predictive factors of short and long-term significant RF loss in all operative methods and constructed a clinical nomogram for long-term Chinese patients RF loss.

Estimating Postoperative Renal Function After Surgery for Nonmetastatic Renal Masses: A Systematic Review of Available Prediction Models

CONTEXT

A variety of models predicting postoperative renal function following surgery for nonmetastatic renal tumors have been reported, but their validity and clinical usefulness have not been formally assessed.

OBJECTIVE

To summarize prediction models available for estimation of mid- to long-term (>3 mo) postoperative renal function after partial nephrectomy (PN) or radical nephrectomy (RN) for nonmetastatic renal masses that include only preoperative or modifiable intraoperative variables.

EVIDENCE ACQUISITION

A systematic review of the English-language literature was conducted using the MEDLINE, Embase, and Web of Science databases from January 2000 to March 2022 according to the PRISMA guidelines (PROSPERO ID: CRD42022303492). Risk of bias was assessed according to the Prediction Model Study Risk of Bias Assessment Tool.

EVIDENCE SYNTHESIS

Overall, 21 prediction models from 18 studies were included (nine for PN only; eight for RN only; four for PN or RN). Most studies relied on retrospective patient cohorts and had a high risk of bias and high concern regarding the overall applicability of the proposed model. Patient-, kidney-, surgery-, tumor-, and provider-related factors were included among the predictors in 95%, 86%, 100%, 61%, and 0% of the models, respectively. All but one model included both patient age and preoperative renal function, while only a few took into account patient gender, race, comorbidities, tumor size/complexity, and surgical approach. There was significant heterogeneity in both the model building strategy and the performance metrics reported. Five studies reported external validation of six models, while three assessed their clinical usefulness using decision curve analysis.

CONCLUSIONS

Several models are available for predicting postoperative renal function after kidney cancer surgery. Most of these are not ready for routine clinical practice, while a few have been externally validated and might be of value for patients and clinicians.

PATIENT SUMMARY

We reviewed the tools available for predicting kidney function after partial or total surgical removal of a kidney for nonmetastatic cancer. Most of the models include patient and kidney characteristics such as age, comorbidities, and preoperative kidney function, and a few also include tumor characteristics and intraoperative variables. Some models have been validated by additional research groups and appear promising for improving counseling for patients with nonmetastatic cancer who are candidates for surgery.

Preoperative hydronephrosis is an independent protective factor of renal function decline after nephroureterectomy for upper tract urothelial carcinoma

Objectives

To evaluate the predictive role of pre-nephroureterectomy (NU) hydronephrosis on post-NU renal function (RF) change and preserved eligibility rate for adjuvant therapy in patients with upper tract urothelial carcinoma (UTUC).

Patients and methods

This retrospective study collected data of 1018 patients from the Taiwan UTUC Collaboration Group registry of 26 institutions. The patients were divided into two groups based on the absence or presence of pre-NU hydronephrosis. Estimated glomerular filtration rate (eGFR) was calculated pre- and post-NU respectively. The one month post-NU RF change, chronic kidney disease (CKD) progression, and the preserved eligibility rate for adjuvant therapy were compared for each CKD stage.

Results

404 (39.2%) patients without and 614 (60.8%) patients with pre-NU hydronephrosis were enrolled. The median post-NU change in the eGFR was significantly lower in the hydronephrosis group (-3.84 versus -12.88, p<0.001). Pre-NU hydronephrosis was associated with a lower post-NU CKD progression rate (33.1% versus 50.7%, p< 0.001) and was an independent protective factor for RF decline after covariate adjustment (OR=0.46, p<0.001). Patients with pre-NU hydronephrosis had a higher preserved eligibility rate for either adjuvant cisplatin-based chemotherapy (OR=3.09, 95%CI 1.95-4.69) or immune-oncology therapy (OR=2.31, 95%CI 1.23-4.34).

Conclusion

Pre-NU hydronephrosis is an independent protective predictor for post-NU RF decline, CKD progression, and eligibility for adjuvant therapy. With cautious selection for those unfavorably prognostic, non-metastatic UTUC patients with preoperative hydronephrosis, adjuvant rather than neoadjuvant therapy could be considered due to higher chance of preserving eligibility.

Validation of new baseline renal function predictive model in robotic-assisted partial nephrectomy cohort

OBJECTIVE

To validate a new baseline estimated glomerular filtration rate (NB-GFR) formula in a cohort of robotic-assisted partial nephrectomies (RAPN).

METHODS

NB-GFR = 35 + preoperative GFR (× 0.65) - 18 (if radical nephrectomy) - age (× 0.25) + 3 (if tumor size >7 cm) - 2 (if diabetes). NB-GFR was calculated in 464 consecutive RAPN from a single surgeon cohort. 143 patients were excluded secondary to insufficient eGFR follow up. We analyzed NB-GFR accuracy utilizing the last observed eGFR 3-12 months post RAPN. Categorical variables were summarized with the frequency and percentage of patients. Numerical variables were summarized with the median, 25^th percentile, and 75^th percentile.

RESULTS

The mean difference between observed and predicted NB-GFR was 4.6 ml/min/1.73m² (95% CI -6.9 to 16.1 ml/min/1.73m² ). There was a pattern of higher observed NB-GFRs being underestimated by the NB-GFR equation while lower observed NB-GFRs were overestimated by the NB-GFR equation. The NB-GFR formula had a high level of accuracy with 98.8% of predicted NB-GFRs falling within 30% of the observed NB-GFR (95% CI 86.8% to 99.5%). The median and interquartile range of the difference between observed and predicted NB-GFR was 3.9 ml/min/1.73m² (IQR 0.7 to 8.2 ml/min/1.73m² ). The sensitivity, specificity, positive predictive value, and negative predictive value for the ability of predicted NB-GFR to identify those with an observed NB-GFR <60 ml/min/1.73m² after RAPN was 98%, 92%, 88%, and 99%, respectively.

CONCLUSION

The NB-GFR equation developed with partial and radical nephrectomy cohorts is accurate in predicting post-operative eGFR 3-12 months following RAPN.

Robot-assisted laparoscopic versus open partial nephrectomy for renal cell carcinoma in patients with severe chronic kidney disease

OBJECTIVES

To compare surgical and functional outcomes between robot-assisted laparoscopic partial nephrectomy and open partial nephrectomy in patients with renal cell carcinoma with stage 4 chronic kidney disease.

METHODS

This was a retrospective analysis of 60 patients with stage 4 chronic kidney disease (estimated glomerular filtration rate 15-30 ml/min/1.73 m² ) who underwent partial nephrectomy for T1 renal cell carcinoma between April 2004 and April 2020. We compared perioperative outcomes according to the surgical approach. Multivariable analysis was performed to identify predictive factors for end-stage renal disease.

RESULTS

Robot-assisted laparoscopic partial nephrectomy and open partial nephrectomy were performed in 31 and 29 patients, respectively. The median age was 68 years and 17% of all patients were women. Patient and tumor characteristics did not differ between groups. The operative time (155.2 vs. 221.0 min, p < 0.0001) and the postoperative length of hospital stay (5.2 vs. 10.6 days, p = 0.0083) were significantly shorter, and the estimated blood loss was lower (53.4 vs. 363.2 ml, p = 0.0003) in the robot-assisted laparoscopic partial nephrectomy group than in the open partial nephrectomy group. Preoperative estimated glomerular filtration rate was the only significant predictor of end-stage renal disease after partial nephrectomy on multivariable analysis.

CONCLUSIONS

Both procedures preserved renal function in this patient cohort, delaying the requirement for postoperative dialysis. Furthermore, robot-assisted laparoscopic partial nephrectomy was associated with shorter operative time and postoperative length of hospital stay, as well as lesser estimated blood loss than open partial nephrectomy.

A dynamic predictive nomogram of long-term survival in primary gastric lymphoma: a retrospective study

Background

Primary gastric lymphoma (PGL) is the most common extranodal non-Hodgkin lymphoma (NHL). Due to the rarity of the disease, it is important to create a predictive model that provides treatment and prognosis for patients with PGL and physicians.

Methods

A total of 8898 and 127 patients diagnosed with PGL were obtained from the SEER database and from our Cancer Center as training and validation cohorts, respectively. Univariate and multivariate Cox proportional hazards models were used to investigate independent risk factors for the construction of predictive survival nomograms, and a web nomogram was developed for the dynamic prediction of survival of patients with PGL. The concordance index (C-index), calibration plot, and receiver operating characteristics (ROC) curve were used to evaluate and validate the nomogram models.

Results

There were 8898 PGL patients in the SEER cohort, most of whom were married men over the age of 60, 16.1% of the primary tumors were localized in the antrum and pylori of the stomach, which was similar to the composition of 127 patients in the Chinese cohort, making both groups comparable. The Nomogram of overall survival (OS) was compiled based on eight variables, including age at diagnosis, sex, race, marital status, histology, stage, radiotherapy and chemotherapy. Cancer-specific survival (CSS) nomogram was developed with eight variables, including age at diagnosis, sex, marital status, primary tumor site, histology, stage, radiotherapy and chemotherapy. The C-index of OS prediction nomogram was 0.948 (95% CI: 0.901–0.995) in the validation cohort, the calibration plots showed an optimal match and a high area below the ROC curve (AUC) was observed in both training and validation sets. Also, we established the first web-based PGL survival rate calculator (https://yangjinru.shinyapps.io/DynNomapp/).

Conclusion

The web dynamic nomogram provided an insightful and applicable tool for evaluating PGL prognosis in OS and CSS, and can effectively guide individual treatment and monitoring.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02419-2.

Estimated Glomerular Filtration Rate Decline at 1 Year After Minimally Invasive Partial Nephrectomy: A Multimodel Comparison of Predictors

Background

Long-term renal function after partial nephrectomy (PN) is difficult to predict as it is influenced by several modifiable and nonmodifiable variables, often intertwined in complex relations.

Objective

To identify variables influencing long-term renal function after PN and to assess their relative weight.

Design, setting, and participants

A total of 457 patients who underwent either robotic (n = 412) or laparoscopic PN (n = 45) were identified from a multicenter international database.

Outcome measurements and statistical analysis

The 1-yr estimated glomerular filtration rate (eGFR) percentage loss (1YPL), defined as the eGFR percentage change from baseline at 1 yr after surgery, was the outcome endpoint. Predictors evaluated included demographic data, tumor features, and operative and postoperative variables. Bayesian multimodel analysis of covariance was used to build all possible models and compare the fit of each model to the data via model Bayes factors. Bayesian model averaging was used to quantify the support for each predictor via the inclusion Bayes factor (BF_incl). High-dimensional undirected graph estimation was used for network analysis of conditional independence between predictors.

Results and limitations

Several models were found to be plausible for estimation of 1YPL. The best model, comprising postoperative eGFR percentage loss (PPL), sex, ischemia technique, and preoperative eGFR, was 207 times more likely than all the other models regarding relative predictive performance. Its components were part of the top 44 models and were the predictors with the highest BF_incl. The role of cold ischemia, solitary kidney status, surgeon experience, and type of renorraphy was not assessed.

Conclusions

Preoperative eGFR, sex, ischemia technique, and PPL are the best predictors of eGFR percentage loss at 1 yr after minimally invasive PN. Other predictors seem to be irrelevant, as their influence is insignificant or already nested in the effect of these four parameters.

Patient summary

Kidney function at 1 year after partial removal of a kidney depends on sex, the technique used to halt blood flow to the kidney during surgery, and kidney function at baseline and in the early postoperative period.

Development and external validation of a nomogram for predicting renal function based on preoperative data from in-hospital patients with simple renal cysts

Objective

To develop and validate a nomogram for predicting renal dysfunction in patients with simple renal cysts (SRCs).

Methods

We performed a multivariable logistic regression analysis of an in-hospital retrospective cohort of patients with SRCs in the Urology Department of the First Affiliated Hospital of Anhui Medical University. For prognostic model development, 386 patients with SRCs were enrolled from January 2016 to December 2018. External validation was performed in 46 patients with SRCs from January 2019 to April 2019. The primary outcome was renal dysfunction.

Results

Patients were divided into normal or abnormal estimated glomerular filtration rate groups (293 vs. 93) based on the cut-off value of 90 mL/minute/1.73 m². Logistical regression analysis determined that age, haemoglobin, globulin, and creatinine might be associated with renal dysfunction, and a novel nomogram was established. Calibration curves showed that the true prediction rate was 77.42%, and decision curve analysis revealed that the nomogram was more effective with threshold probabilities ranging from 0.1 to 0.8. The area under the curves were 0.829, 0.752, and 0.888 in the overall training, internal, and external validation cohorts, respectively.

Conclusions

We established a nomogram to predict the probability of developing renal dysfunction in patients with SRCs.

Prediction of significant renal function decline after open, laparoscopic, and robotic partial nephrectomy: External validation of the Martini's nomogram on the RECORD2 project cohort

OBJECTIVES

Martini et al. developed a nomogram to predict significant (>25%) renal function loss after robot-assisted partial nephrectomy and identified four risk categories. We aimed to externally validate Martini's nomogram on a large, national, multi-institutional data set including open, laparoscopic, and robot-assisted partial nephrectomy.

METHODS

Data of 2584 patients treated with partial nephrectomy for renal masses at 26 urological Italian centers (RECORD2 project) were collected. Renal function was assessed at baseline, on third postoperative day, and then at 6, 12, 24, and 48 months postoperatively. Multivariable models accounting for variables included in the Martini's nomogram were applied to each approach predicting renal function loss at all the specific timeframes.

RESULTS

Multivariable models showed high area under the curve for robot-assisted partial nephrectomy at 6- and 12-month (87.3% and 83.6%) and for laparoscopic partial nephrectomy (83.2% and 75.4%), whereas area under the curves were lower in open partial nephrectomy (78.4% and 75.2%). The predictive ability of the model decreased in all the surgical approaches at 48 months from surgery. Each Martini risk group showed an increasing percentage of patients developing a significant renal function reduction in the open, laparoscopic and robot-assisted partial nephrectomy group, as well as an increased probability to develop a significant estimated glomerular filtration rate reduction in the considered time cutoffs, although the predictive ability of the classes was <70% at 48 months of follow-up.

CONCLUSIONS

Martini's nomogram is a valid tool for predicting the decline in renal function at 6 and 12 months after robot-assisted partial nephrectomy and laparoscopic partial nephrectomy, whereas it showed a lower performance at longer follow-up and in patients treated with open approach at all these time cutoffs.

External validation of the Palacios' equation: a simple and accurate tool to estimate the new baseline renal function after renal cancer surgery

PURPOSE

To externally validate the Palacios' equation estimating the new baseline glomerular filtration rate (NB-GFR) after partial or radical-nephrectomy (PN, RN) for Renal cancer carcinoma (RCC).

MATERIALS AND METHODS

Our research group recently published two studies that investigated the association between renal function and cancer-specific survival in RCC. The first one included 3457 patients undergone RN or PN for a cT1-2 RCC coming from five high-volume centers; the second one considered 1767 patients undergone RN or PN for a cT1-4 RCC in a single high-volume center. From such datasets, available complete patients' data were used to calculate the predicted NB-GFR through the Palacios' equation: predicted NB-GFR = 35.03 + 0.65 ∙ preoperative GFR - 18.19 ∙ (if radical nephrectomy) - 0.25 ∙ age + 2.83 ∙ (if tumor size > 7 cm) - 2.09 ∙ (if diabetes). The observed NB-GFR was calculated by the CKD-EPI equation on serum creatinine at 3-12 months after surgery. Concordance between observed and predicted NB-GFR was evaluated by Lin's concordance correlation coefficient and Bland-Altman analysis.

RESULTS

2419 patients were included (1210, cohort #1; 1219, cohort #2). The median observed NB-GFR value in cohorts #1 and #2 was 73.0 ml/min/1.73 m² (IQR 56.1-90.1) and 64.2 ml/min/1.73 m² (IQR 49.6-83); the median predicted NB-GFR was 71.1 ml/min/1.73 m² (IQR 58-81.5) and 62.6 ml/min/1.73m² (IQR 47.9-75.9). The concordance line showed a slope of 0.80 and 0.86, and an intercept at 11.02 and 5.41 ml/min/1.73 m² in the cohort#1 and #2, respectively. The Palacio's equation moderately over-estimated and under-estimated NB-GFR, for values below and above the cut-off of 50 ml/min/1.73 m² and 35 ml/min/1.73m² in cohort#1 and #2. The Lin's concordance correlation coefficient was 0.79 (95% CI 0.77-0.81) and 0.83 (95% CI 0.82-0.85).

CONCLUSIONS

We confirm the predictive performances of Palacios' equation, supporting its utilization in clinical practice.

Changes in renal function after nephroureterectomy for upper urinary tract carcinoma: analysis of a large multicenter cohort (Radical Nephroureterectomy Outcomes (RaNeO) Research Consortium)

PURPOSE

To investigate prevalence and predictors of renal function variation in a multicenter cohort treated with radical nephroureterectomy (RNU) for upper tract urothelial carcinoma (UTUC).

METHODS

Patients from 17 tertiary centers were included. Renal function variation was evaluated at postoperative day (POD)-1, 6 and 12 months. Timepoints differences were Δ1 = POD-1 eGFR - baseline eGFR; Δ2 = 6 months eGFR - POD-1 eGFR; Δ3 = 12 months eGFR - 6 months eGFR. We defined POD-1 acute kidney injury (AKI) as an increase in serum creatinine by ≥ 0.3 mg/dl or a 1.5 1.9-fold from baseline. Additionally, a cutoff of 60 ml/min in eGFR was considered to define renal function decline at 6 and 12 months. Logistic regression (LR) and linear mixed (LM) models were used to evaluate the association between clinical factors and eGFR decline and their interaction with follow-up.

RESULTS

A total of 576 were included, of these 409(71.0%) and 403(70.0%) had an eGFR < 60 ml/min at 6 and 12 months, respectively, and 239(41.5%) developed POD-1 AKI. In multivariable LR analysis, age (Odds Ratio, OR 1.05, p < 0.001), male gender (OR 0.44, p = 0.003), POD-1 AKI (OR 2.88, p < 0.001) and preoperative eGFR < 60 ml/min (OR 7.58, p < 0.001) were predictors of renal function decline at 6 months. Age (OR 1.06, p < 0.001), coronary artery disease (OR 2.68, p = 0.007), POD-1 AKI (OR 1.83, p = 0.02), and preoperative eGFR < 60 ml/min (OR 7.80, p < 0.001) were predictors of renal function decline at 12 months. In LM models, age (p = 0.019), hydronephrosis (p < 0.001), POD-1 AKI (p < 0.001) and pT-stage (p = 0.001) influenced renal function variation (ß 9.2 ± 0.7, p < 0.001) during follow-up.

CONCLUSION

Age, preoperative eGFR and POD-1 AKI are independent predictors of 6 and 12 months renal function decline after RNU for UTUC.

Development and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure

Background: Acute kidney injury is an adverse event that carries significant morbidity among patients with acute decompensated heart failure (ADHF). We planned to develop a parsimonious model that is simple enough to use in clinical practice to predict the risk of acute kidney injury (AKI) occurrence. Methods: Six hundred and fifty patients with ADHF were enrolled in this study. Data for each patient were collected from medical records. We took three different approaches of variable selection to derive four multivariable logistic regression model. We selected six candidate predictors that led to a relatively stable outcome in different models to derive the final prediction model. The prediction model was verified through the use of the C-Statistics and calibration curve. Results: Acute kidney injury occurred in 42.8% of the patients. Advanced age, diabetes, previous renal dysfunction, high baseline creatinine, high B-type natriuretic peptide, and hypoalbuminemia were the strongest predictors for AKI. The prediction model showed moderate discrimination C-Statistics: 0.766 (95% CI, 0.729-0.803) and good identical calibration. Conclusion: In this study, we developed a prediction model and nomogram to estimate the risk of AKI among patients with ADHF. It may help clinical physicians detect AKI and manage it promptly.

Impact of surgical approach and resection technique on the risk of Trifecta Failure after partial nephrectomy for highly complex renal masses

INTRODUCTION

We aimed to compare the outcomes of open vs robotic partial nephrectomy (PN), focusing on predictors of Trifecta failure in patients with highly complex renal masses.

PATIENTS AND METHODS

We queried the prospectively collected database from the SIB International Consortium, including 507 consecutive patients with cT1-2N0M0 renal masses treated at 16 high-volume referral centres, to select those with highly complex (PADUA score ≥10) tumors undergoing PN. RT was classified as enucleation, enucleoresection or resection according to the SIB score. Trifecta was defined as achievement of negative surgical margins, no acute kidney injury and no Clavien-Dindo grade ≥2 postoperative surgical complications. Multivariable logistic regression analysis was used to assess independent predictors of Trifecta failure.

RESULTS

113 patients were included. Patients undergoing open PN (n = 47, 41.6%) and robotic PN (n = 66, 58.4%) were comparable in baseline characteristics. RT was classified as enucleation, enucleoresection and resection in 46.9%, 34.0% and 19.1% of open PN, and in 50.0%, 40.9% and 9.1% of robotic PN (p = 0.28). Trifecta was achieved in significantly more patients after robotic PN (69.7% vs. 42.6%, p = 0.004). On multivariable analysis, surgical approach (open vs robotic, OR: 2.62; 95%CI: 1.11-6.15, p = 0.027) and tumor complexity (OR for each additional unit of the PADUA score: 2.27; 95%CI: 1.27-4.06, p = 0.006) were significant predictors of Trifecta failure, while RT was not. The study is limited by lack of randomization; as such, selection bias and confounding cannot be entirely ruled out.

CONCLUSIONS

Tumor complexity and surgical approach were independent predictors of Trifecta failure after PN for highly complex renal masses.

Validation of predictive model for new baseline renal function after robot-assisted partial nephrectomy or radical nephrectomy in Japanese patients

PURPOSE

The study aim was to externally validate a new predictive model for new baseline glomerular filtration rate post-nephrectomy among Japanese patients.

MATERIALS AND METHODS

Patients with renal tumors who underwent radical nephrectomy or robot-assisted partial nephrectomy at a single Japanese institution in 2000-2020 were retrospectively analyzed. New baseline glomerular filtration rate is defined as the final estimated glomerular filtration rate within postoperative 3-12 months. The correlation/bias/accuracy/precision of the equation was examined by comparing the calculated new baseline glomerular filtration rate with the observed rate.

RESULTS

The study included 485 cases of radical nephrectomy, and 1030 cases of robot-assisted partial nephrectomy. The correlation/bias/accuracy/precision of the new equation predicting new baseline glomerular filtration rate were 0.86/-0.92/95.9/-5.65-3.62 in robot-assisted partial nephrectomy and 0.79/-1.02/87.8/-6.26-3.91 in radical nephrectomy, respectively. The fractional polynomial regression line approximated zero and its pointwise 95% confidence interval was considerably tight for the majority of both cohorts. The 95% confidence interval to discriminate new baseline glomerular filtration rates of ≥45 ml/min/1.73 m2 from receiver operating curves was 0.96 (0.95-0.97) and 0.89 (0.87-0.92) in robot-assisted partial nephrectomy and radical nephrectomy, respectively. Various preoperative factors including age, tumor size, complexity, body mass index, hypertension, and diabetes did not affect the predictive ability (correlation > 0.7) from the subgroup analysis.

CONCLUSION

The novel simple equation can accurately predict new baseline glomerular filtration rates after radical and robot-assisted partial nephrectomies in Japanese patients. This model will help physicians choose surgical treatments for renal tumors in daily clinical practice.

Evaluation of Routine Postoperative Labs Following Robotic Assisted Partial Nephrectomy in Patients With Normal Preoperative Renal Function

OBJECTIVE

To evaluate predictors of abnormal routine postoperative day 1 (POD1) labs in patients with normal pre-operative renal function following robotic assisted partial nephrectomy (RAPN) and the associated clinical outcomes of these lab results.

METHODS

We analyzed 500 consecutive RAPN from a single surgeon series. Patients with chronic kidney disease (CKD) III or greater were excluded from the study. Three hundred ninty-three RAPN were included in the analysis. Routine POD1 lab tests including hemoglobin (Hgb), creatinine, potassium, and sodium were evaluated to determine rates of abnormal values and rates of clinical intervention. Abnormal Hgb at POD1 was defined as <8 g/dL or ≥3 g/dL decrease from the preoperative (baseline) value. Abnormal sodium (Na) preoperatively and postoperatively was defined as <135 mEq/L or >145 mEq/L. Abnormal potassium (K) was defined preoperatively and POD1 as <3.5 mEq/L or >5 mEq/L.

RESULTS

Of 37.4% (147/393) had one or more abnormal labs at POD1. Of the 101 patients with abnormal Hgb, 15 patients required blood transfusion. Twenty-six patients had abnormal sodium for which two were treated with IV fluids. Twenty-seven patients had potassium abnormalities (12/25 were hypokalemia). Acute kidney injury stage I was seen in 27 patients (6.9%) and stage II in 3 (0.8%). Patients with abnormal labs were more likely to have larger renal mass, higher R.E.N.A.L. scores, intraoperative complications, longer operative times, and higher EBL on multivariate analysis.

CONCLUSION

POD1 serum laboratory tests appear to be necessary following RAPN in patients with normal pre-operative renal function.

Tumor volume and tumor crossing of the axial renal midline predict renal function after robotic partial nephrectomy

There are several nephrometry scoring systems for predicting surgical complexity and potential perioperative morbidity. The R.E.N.A.L. scoring system, one of the most well-known nephrometry scoring systems, emphasizes the features on which it is based (Radius, Exophytic/endophytic, Nearness to collecting system or sinus, Anterior/posterior, and Location relative to polar lines). The ability of these nephrometry scoring systems to predict loss of renal function after robotic partial nephrectomy (RPN) remains controversial. Therefore, we verified which combination of factors from nephrometry scoring systems, including tumor volume, was the most significant predictor of postoperative renal function. Patients who underwent RPN for cT1 renal tumors in our hospital were reviewed retrospectively (n = 163). The preoperative clinical data (estimated glomerular filtration rate [eGFR], comorbidities, and nephrometry scoring systems including R.E.N.A.L.) and perioperative outcomes were evaluated. We also calculated the tumor volume using the equation applied to an ellipsoid by three-dimensional computed tomography. The primary outcome was reduced eGFR, which was defined as an eGFR reduction of ≥ 20% from baseline to 6 months after RPN. Multivariable logistic regression analyses were used to evaluate the relationships between preoperative variables and reduced eGFR. Of 163 patients, 24 (14.7%) had reduced eGFR. Multivariable analyses indicated that tumor volume (cutoff value ≥ 14.11 cm³, indicating a sphere with a diameter ≥ approximately 3 cm) and tumor crossing of the axial renal midline were independent factors associated with a reduced eGFR (odds ratio [OR] 4.57; 95% confidence interval [CI] 1.69-12.30; P = 0.003 and OR 3.50; 95% CI 1.30-9.46; P = 0.034, respectively). Our classification system using these two factors showed a higher area under the receiver operating characteristic curve (AUC) than previous nephrometry scoring systems (AUC = 0.786 vs. 0.653-0.719), and it may provide preoperative information for counseling patients about renal function after RPN.

Nomograms for Predicting Cancer-Specific Survival of Patients with Gingiva Squamous Cell Carcinoma: A Population-Based Study

OBJECTIVE

The use of the traditional American Joint Committee on Cancer (AJCC) staging system alone has limitations in predicting the survival of gingiva squamous cell carcinoma (GSCC) patients. We aimed to establish a comprehensive prognostic nomogram with a prognostic value similar to the AJCC system.

METHODS

Patients were identified from SEER database. Variables were selected by a backward stepwise selection method in a Cox regression model. A nomogram was used to predict cancer-specific survival rates for 3, 5 and 10 years in patients with GSCC. Several basic features of model validation were used to evaluate the performance of the survival model: consistency index (C-index), receiver operating characteristic (ROC) curve, calibration chart, net weight classification improvement (NRI), comprehensive discriminant improvement (IDI) and decision curve analysis (DCA).

RESULTS

Multivariate analyses revealed that age, race, marital status, insurance, AJCC stage, pathology grade and surgery were risk factors for survival. In particular, the C-index, the area under the ROC curve (AUC) and the calibration plots showed good performance of the nomogram. Compared to the AJCC system, NRI and IDI showed that the nomogram has improved performance. Finally, the nomogram's 3-year and 5-year and 10-year DCA curves yield net benefits higher than traditional AJCC, whether training set or a validation set.

CONCLUSION

We developed and validated the first GSCC prognosis nomogram, which has a better prognostic value than the separate AJCC staging system. Overall, the nomogram of this study is a valuable tool for clinical practice to consult patients and understand their risk for the next 3, 5 and 10 years.

Nomogram predicting the risk of three-year chronic kidney disease adverse outcomes among East Asian patients with CKD

Background

Chronic kidney disease (CKD) is a common health challenge. There are some risk models predicting CKD adverse outcomes, but seldom focus on the Mongoloid population in East Asian. So, we developed a simple but intuitive nomogram model to predict 3-year CKD adverse outcomes for East Asian patients with CKD.

Methods

The development and internal validation of prediction models used data from the CKD-ROUTE study in Japan, while the external validation set used data collected at the First People’s Hospital of Foshan in southern China from January 2013 to December 2018. Models were developed using the cox proportional hazards model and nomogram with SPSS and R software. Finally, the model discrimination, calibration and clinical value were tested by R software.

Results

The development and internal validation data-sets included 797 patients (191 with progression [23.96%]) and 341 patients (89 with progression [26.10%]), respectively, while 297 patients (108 with progression [36.36%]) were included in the external validation data set. The nomogram model was developed with age, eGFR, haemoglobin, blood albumin and dipstick proteinuria to predict three-year adverse-outcome-free probability. The C-statistics of this nomogram were 0.90(95% CI, 0.89–0.92) for the development data set, 0.91(95% CI, 0.89–0.94) for the internal validation data set and 0.83(95% CI, 0.78–0.88) for the external validation data-set. The calibration and decision curve analyses were good in this model.

Conclusion

This visualized predictive nomogram model could accurately predict CKD three-year adverse outcomes for East Asian patients with CKD, providing an easy-to-use and widely applicable tool for clinical practitioners.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-021-02496-7.

A Nomogram for the Prediction of Intermediate Significant Renal Function Loss After Robot-assisted Partial Nephrectomy for Localized Renal Tumors: A Prospective Multicenter Observational Study (RECORd2 Project)

BACKGROUND

Robot-assisted partial nephrectomy (RAPN) is increasingly adopted for the treatment of localized renal tumors; however, rates and predictors of significant renal function (RF) loss after RAPN are still poorly investigated, especially at a long-term evaluation.

OBJECTIVE

To analyze the predictive factors and develop a clinical nomogram for predicting the likelihood of ultimate RF loss after RAPN.

DESIGN, SETTING, AND PARTICIPANTS

We prospectively evaluated all patients treated with RAPN in a multicenter series (RECORd2 project).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Significant RF loss was defined as >25% reduction in estimated glomerular filtration rate (eGFR) from preoperative assessment at 48th month follow-up after surgery. Uni- and multivariable logistic regression analyses for RF loss were performed. The area under the receiving operator characteristic curve (AUC) was used to quantify predictive discrimination. A nomogram was created from the multivariable model.

RESULTS AND LIMITATIONS

A total of 981 patients were included. The median age at surgery was 64.2 (interquartile range [IQR] 54.3-71.4) yr, and 62.4% of patients were male. The median Charlson Comorbidity Index (CCI) was 1 (IQR 0-2), 12.9% of patients suffered from diabetes mellitus, and 18.6% of patients showed peripheral vascular disease (PVD). The median Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) score was 7 (IQR 7-9). Imperative indications to partial nephrectomy were present in 3.6% of patients. Significant RF loss at 48th month postoperative evaluation was registered in 108 (11%) patients. At multivariable analysis, age (p = 0.04), female gender (p < 0.0001), CCI (p < 0.0001), CCI (p < 0.0001), diabetes (p < 0.0001), PVD (p < 0.0001), eGFR (p = 0.02), imperative (p = 0.001) surgical indication, and PADUA score (p < 0.0001) were found to be predictors of RF loss. The developed nomogram including these variables showed an AUC of 0.816.

CONCLUSIONS

We developed a clinical nomogram for the prediction of late RF loss after RAPN using preoperative and surgical variables from a large multicenter dataset.

PATIENT SUMMARY

We developed a nomogram that could represent a clinical tool for early detection of patients at the highest risk of significant renal function impairment after robotic conservative surgery for renal tumors.

Near-term prognostic impact of integrated muscle mass and function in upper gastrointestinal cancer

BACKGROUND

Despite the known association between muscle mass/function and malnutrition-related mortality in upper gastrointestinal (UGI) cancer, no comprehensive study to determine the impact of muscle mass-dominant nutritional status on cancer prognosis has been conducted. The present study aimed to investigate the prognostic significance of integrated muscle mass and function in UGI cancer.

METHODS

Between July 2013 and March 2018, we enrolled 2546 cancer patients with risks of malnutrition (Nutrition Risk Screening 2002, ≥3 points) from a multicenter cohort study and split 527 patients with primary UGI cancer into an internal validation group. We prospectively performed instant nutritional assessment and recorded all general clinical characteristics of the participants, such as weight loss, body mass index, anthropometric measurements of muscle mass and function, dietary intake conditions, and disease burden and/or inflammation status based on the validated tools. Prognostic analyses were performed with post-assessment overall survival (OS).

RESULTS

According to the entire set, UGI cancer was identified as the dominant risk factor for disease burden and inflammation criteria (hazard ratio (HR), 2.08, 95% confidence interval (Cl), 1.81-2.39, P < 0.001). Integrated muscle mass/function analysis with validated cutoff values showed that hand grip strength/weight followed by triceps skinfold thickness and maximum calf circumference are the most potent predictors. Univariate and multivariate analyses revealed that reduced muscle mass/function (74.8%) and dietary intake (66.2%) independently affect OS of patients with UGI cancer. Significant associations were found between the reduced muscle mass/reduced dietary intake and the shortest OS (HR, 4.48; 95% Cl, 3.07-6.53; P < 0.001). Appending subgroups of muscle mass/function and dietary intake to the pre-existing risk model increased the efficiency of the time-dependent receiver operating characteristic curve analysis for OS in UGI cancer, particularly within 2 years of instant nutritional assessment.

CONCLUSION

Impaired muscle mass/function adversely affects the near-term prognosis in patients with UGI cancer. Along with a comprehensive evaluation of dietary intake conditions, the timely nutritional assessment might be useful for risk stratification of UGI cancers with potential for enteral and parenteral nutrition interventions.

REGISTRATION NUMBER

ChiCTR1800020329.

Predicting the risk of postoperative acute kidney injury: development and assessment of a novel predictive nomogram

OBJECTIVE

This study aimed to establish and internally verify the risk nomogram of postoperative acute kidney injury (AKI) in patients with renal cell carcinoma.

METHODS

We retrospectively collected data from 559 patients with renal cell carcinoma from June 2016 to May 2019 and established a prediction model. Twenty-six clinical variables were examined by least absolute shrinkage and selection operator regression analysis, and variables related to postoperative AKI were determined. The prediction model was established by multiple logistic regression analysis. Decision curve analysis was conducted to evaluate the nomogram.

RESULTS

Independent predictors of postoperative AKI were smoking, hypertension, surgical time, blood glucose, blood uric acid, alanine aminotransferase, estimated glomerular filtration rate, and radical nephrectomy. The C index of the nomogram was 0.825 (0.790-0.860) and 0.814 was still obtained in the internal validation. The nomogram had better clinical benefit when the intervention was decided at the threshold probabilities of >4% and <79% for patients and doctors, respectively.

CONCLUSIONS

This novel postoperative AKI nomogram incorporating smoking, hypertension, the surgical time, blood glucose, blood uric acid, alanine aminotransferase, the estimated glomerular filtration rate, and radical nephrectomy is convenient for facilitating the individual postoperative risk prediction of AKI in patients with renal cell carcinoma.

Machine learning-based prediction of acute kidney injury after nephrectomy in patients with renal cell carcinoma

The precise prediction of acute kidney injury (AKI) after nephrectomy for renal cell carcinoma (RCC) is an important issue because of its relationship with subsequent kidney dysfunction and high mortality. Herein we addressed whether machine learning (ML) algorithms could predict postoperative AKI risk better than conventional logistic regression (LR) models. A total of 4104 RCC patients who had undergone unilateral nephrectomy from January 2003 to December 2017 were reviewed. ML models such as support vector machine, random forest, extreme gradient boosting, and light gradient boosting machine (LightGBM) were developed, and their performance based on the area under the receiver operating characteristic curve, accuracy, and F1 score was compared with that of the LR-based scoring model. Postoperative AKI developed in 1167 patients (28.4%). All the ML models had higher performance index values than the LR-based scoring model. Among them, the LightGBM model had the highest value of 0.810 (0.783-0.837). The decision curve analysis demonstrated a greater net benefit of the ML models than the LR-based scoring model over all the ranges of threshold probabilities. The application of ML algorithms improves the predictability of AKI after nephrectomy for RCC, and these models perform better than conventional LR-based models.

Predictive factors for survival following stereotactic body radiotherapy for hepatocellular carcinoma with portal vein tumour thrombosis and construction of a nomogram

Background

We evaluated the treatment response and predictive factors for overall survival (OS) in patients with hepatocellular carcinoma (HCC) and portal vein tumour thrombosis (PVTT), who underwent stereotactic body radiotherapy (SBRT). Additionally, we developed and validated a personalised prediction model for patient survival.

Methods

Clinical information was retrospectively collected for 80 patients with HCC and PVTT, who were treated with SBRT at the Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital) between December 2015 and June 2019. A multivariate Cox proportional hazard regression model was used to identify the independent predictive factors for survival. Clinical factors were subsequently presented in a nomogram. The area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to evaluate the accuracy of the model and the net clinical benefit.

Results

All patients completed the planned radiotherapy treatment, and the median follow-up duration was 10 months (range, 1–35.3 months). The median survival duration was 11.5 months, with 3-, 6-, and 12-month survival rates of 92.5, 74.5, and 47.5%, respectively. The multivariable Cox regression model indicated that the following were significant independent predictors of OS: clinical T stage (p = 0.001, hazard ratio [HR] = 3.085, 95% confidence interval [CI]: 1.514–6.286), cirrhosis (p = 0.014, HR = 2.988, 95% CI: 1.246–7.168), age (p = 0.005, HR = 1.043, 95% CI: 1.013–1.075), alpha-fetoprotein level (p = 0.022, HR = 1.000, 95% CI: 1.000–1.000), and haemoglobin level (p = 0.008, HR = 0.979, 95% CI: 0.963–0.994). A nomogram based on five independent risk factors and DCA demonstrated a favourable predictive accuracy of patient survival (AUC = 0.74, 95% CI: 0.63–0.85) and the clinical usefulness of the model.

Conclusions

SBRT is an effective treatment for patients with HCC with PVTT. Notably, clinical T stage, presence of cirrhosis, age, alpha-fetoprotein levels, and haemoglobin levels are independent prognostic factors for survival. The presented nomogram can be used to predict the survival of patients with HCC and PVTT, who underwent SBRT.

Salvage Robot-assisted Renal Surgery for Local Recurrence After Surgical Resection or Renal Mass Ablation: Classification, Techniques, and Clinical Outcomes

BACKGROUND

Salvage treatment for local recurrence after prior partial nephrectomy (PN) or local tumor ablation (LTA) for kidney cancer is, as of yet, poorly investigated.

OBJECTIVE

To classify the treatments and standardize the nomenclature of salvage robot-assisted renal surgery, to describe the surgical technique for each scenario, and to investigate complications, renal function, and oncologic outcomes.

DESIGN, SETTING, AND PARTICIPANTS

Sixty-seven patients underwent salvage robot-assisted renal surgery from October 2010 to December 2020 at nine tertiary referral centers.

SURGICAL PROCEDURE

Salvage robot-assisted renal surgery classified according to treatment type as salvage robot-assisted partial or radical nephrectomy (sRAPN or sRARN) and according to previous primary treatment (PN or LTA).

MEASUREMENTS

Postoperative complications, renal function, and oncologic outcomes were assessed.

RESULTS AND LIMITATIONS

A total of 32 and 35 patients underwent salvage robotic surgery following PN and LTA, respectively. After prior PN, two patients underwent sRAPN, while ten underwent sRARN for a metachronous recurrence in the same kidney. No intra- or perioperative complication occurred. For local recurrence in the resection bed, six patients underwent sRAPN, while 14 underwent sRARN. For sRAPN, the intraoperative complication rate was 33%; there was no postoperative complication. For sRARN, there was no intraoperative complication and the postoperative complication rate was 7%. At 3 yr, the local recurrence-free rates were 64% and 82% for sRAPN and sRARN, respectively, while the 3-yr metastasis-free rates were 80% and 79%, respectively. At 33 mo, the median estimated glomerular filtration rates (eGFRs) were 57 and 45 ml/min/1.73 m² for sRAPN and sRARN, respectively. After prior LTA, 35 patients underwent sRAPN and no patient underwent sRARN. There was no intraoperative complication; the overall postoperative complications rate was 20%. No local recurrence occurred. The 3-yr metastasis-free rate was 90%. At 43 mo, the median eGFR was 38 ml/min/1.73 m². The main limitations are the relatively small population and the noncomparative design of the study.

CONCLUSIONS

Salvage robot-assisted surgery has a safe complication profile in the hands of experienced surgeons at high-volume institutions, but the risk of local recurrence in this setting is non-negligible.

PATIENT SUMMARY

Patients with local recurrence after partial nephrectomy or local tumor ablation should be aware that further treatment with robot-assisted surgery is not associated with a worrisome complication profile, but also that they are at risk of further recurrence.

Clinical advantages of robot-assisted partial nephrectomy versus laparoscopic partial nephrectomy in terms of global and split renal functions: A propensity score-matched comparative analysis

OBJECTIVES

To identify predictors of renal function preservation, and to compare the global and split renal function outcomes of robot-assisted partial nephrectomy and laparoscopic partial nephrectomy.

METHODS

Demographic, operative and pathological data, as well as renal function outcomes, of 251 patients who underwent laparoscopic (n = 104) and robot-assisted (n = 147) partial nephrectomy between 2008 and 2018 were retrospectively analyzed. Propensity score matching (1:1) was carried out to adjust for potential baseline confounders. Functional outcomes were assessed based on the estimated glomerular filtration rate and dynamic renal scintigraphy (using ^99m Tc-mercaptoacetyltriglycine), including renal volumetric analysis.

RESULTS

A total of 98 patients were allocated to each partial nephrectomy group. Ischemic (laparoscopic vs robot-assisted partial nephrectomy: 29 vs 15 min, P < 0.001) and operative times (181 vs 100 min, P < 0.001) were shorter in robot-assisted partial nephrectomy. The preservation ratio of global renal function at 3 months (88.3% vs 91.4%, P = 0.040) and 12 months (87.8% vs 91.5%, P = 0.010) postoperatively, and the renal function of the operated kidney (80.3% vs 88.2%, P < 0.001) were greater after robot-assisted partial nephrectomy. In robot-assisted partial nephrectomy, the volume of resected parenchyma was significantly smaller (27.2 vs 15.5 mL, P < 0.001), resulting in greater postoperative normal parenchymal volumes (120 vs 132 mL, P < 0.001) and a greater parenchymal preservation ratio (81.1% vs 90.1%, P < 0.001). The parenchymal preservation ratio was the strongest predictor of renal function preservation after surgery (P < 0.001, odds ratio 6.02).

CONCLUSIONS

Robot-assisted partial nephrectomy allows better preservation of split renal function than laparoscopic partial nephrectomy by increasing the parenchymal preservation ratio. This translates into better postoperative global renal function.

Nomograms in Urologic Oncology: Lights and Shadows

Decision-making in urologic oncology involves integrating multiple clinical data to provide an answer to the needs of a single patient. Although the practice of medicine has always been an “art” involving experience, clinical data, scientific evidence and judgment, the creation of specialties and subspecialties has multiplied the challenges faced every day by physicians. In the last decades, with the field of urologic oncology becoming more and more complex, there has been a rise in tools capable of compounding several pieces of information and supporting clinical judgment and experience when approaching a difficult decision. The vast majority of these tools provide a risk of a certain event based on various information integrated in a mathematical model. Specifically, most decision-making tools in the field of urologic focus on the preoperative or postoperative phase and provide a prognostic or predictive risk assessment based on the available clinical and pathological data. More recently, imaging and genomic features started to be incorporated in these models in order to improve their accuracy. Genomic classifiers, look-up tables, regression trees, risk-stratification tools and nomograms are all examples of this effort. Nomograms are by far the most frequently used in clinical practice, but are also among the most controversial of these tools. This critical, narrative review will focus on the use, diffusion and limitations of nomograms in the field of urologic oncology.

Robot-assisted partial nephrectomy for high-complexity tumors (PADUA score ≥10): Perioperative, long-term functional and oncologic outcomes

OBJECTIVES

To evaluate the safety and efficacy, and long-term functional and oncologic outcomes of robot-assisted partial nephrectomy in high-complexity tumors.

METHODS

Data of 155 patients with a high-complexity tumor (PADUA score ≥10) were reviewed. Trifecta achievement, intra-, perioperative, functional, and oncologic outcomes were analyzed and compared between patients with increasing complexity.

RESULTS

Of the 155 patients, 65 (41.9%) patients had a PADUA score of 10, 55 (35.5%) had a PADUA score of 11, and 35 (22.6%) had a PADUA score of 12-13, respectively. The median (interquartile range) operative time, warm ischemia time and estimated blood loss were 150 min (112-186 min), 26 min (23-32 min) and 250 mL (100-500 mL), respectively. Postoperatively, complications occurred in 25 (16.1%) patients, and positive surgical margins in 15 (10.5%) patients. Trifecta was achieved in 67 (43.2%) patients. At a median follow-up period of 58 months, the median estimated glomerular filtration rate preservation was 87% (78-110), and 12 (7.7%) patients developed new-onset chronic kidney disease. Recurrence-free survival and overall survival rates were 93.6% and 96.7%, respectively. Positive surgical margins were statistically different between the groups of PADUA score 10, 11 and 12-13 (P = 0.017), whereas functional and oncologic outcomes were similar. In multivariate logistic regression analysis, increasing tumor size (odds ratio 1.48, 95% confidence interval 1.21-1.87; P < 0.001) and the American Society of Anesthesiologists score 2/3 (odds ratio 0.48, 95% confidence interval 0.24-0.96; P = 0.041) were independent predictors of trifecta failure.

CONCLUSIONS

Robot-assisted partial nephrectomy is a safe and effective treatment for high-complexity tumors providing excellent long-term functional and oncologic outcomes.

Collaborative Review: Factors Influencing Treatment Decisions for Patients with a Localized Solid Renal Mass

CONTEXT

With the addition of active surveillance and thermal ablation (TA) to the urologist's established repertoire of partial (PN) and radical nephrectomy (RN) as first-line management options for localized renal cell carcinoma (RCC), appropriate treatment decision-making has become increasingly nuanced.

OBJECTIVE

To critically review the treatment options for localized, nonrecurrent RCC; to highlight the patient, renal function, tumor, and provider factors that influence treatment decisions; and to provide a framework to conceptualize that decision-making process.

EVIDENCE ACQUISITION

A collaborative critical review of the medical literature was conducted.

EVIDENCE SYNTHESIS

We identify three key decision points when managing localized RCC: (1) decision for surveillance versus treatment, (2) decision regarding treatment modality (TA, PN, or RN), and (3) decision on surgical approach (open vs minimally invasive). In evaluating factors that influence these treatment decisions, we elaborate on patient, renal function, tumor, and provider factors that either directly or indirectly impact each decision point. As current nomograms, based on preselected patient datasets, perform poorly in prospective settings, these tools should be used with caution. Patient decision aids are an underutilized tool in decision-making.

CONCLUSIONS

Localized RCC requires highly nuanced treatment decision-making, balancing patient- and tumor-specific clinical variables against indirect structural influences to provide optimal patient care.

PATIENT SUMMARY

With expanding treatment options for localized kidney cancer, treatment decision is highly nuanced and requires shared decision-making. Patient decision aids may be helpful in the treatment discussion.

Impact of postoperative acute kidney injury on predicting the upstaging of chronic kidney disease after robot-assisted partial nephrectomy

INTRODUCTION

The aim of our study was to assess the impact of acute kidney injury (AKI) on postoperative upstaging of chronic kidney disease (CKD) after robot-assisted partial nephrectomy (RAPN).

METHODS

This study consisted of 110 patients who had undergone RAPN and were followed up for at least 6 months after surgery. Patients were classified as AKI or non-AKI based on their serum creatinine level and estimated glomerular filtration rate within 7 days after surgery. Patient characteristics, outcome of RAPN and estimated glomerular filtration rate, and CKD upstage 6 months after surgery were compared between the AKI and non-AKI groups.

RESULTS

A total of 26 patients (23.6%) experienced AKI after surgery. RENAL (radius, exophytic/endophitic properties, nearness of the tumor to the collecting system or sinus, anterior/posterior, location relative to the polar lines) nephrometry scores were ≥7 for 22 (84.6%) in the AKI group and 39 (46.4%) in the non-AKI group (P = .0006). A significantly smaller proportion of patients in the AKI group than in the non-AKI group recovered 90% of baseline function (38.5% vs 81.0%, P < .0001). CKD upstaging occurred in a total of 27 patients 24.5%) and in a significantly larger proportion of patients in the AKI group than in the non-AKI group (42.3% vs 19.0%, P = .0160). There was no significant difference in characteristics and perioperative outcomes between the patients with and without CKD, except for in those experiencing AKI.

CONCLUSION

After RAPN, AKI can be associated with CKD upstaging.

Renal function after partial nephrectomy following intra-arterial embolization of renal tumors

Laparoscopic Partial Nephrectomy (LPN) after intra-arterial Embolization of renal tumors (LPNE) in a hybrid operating room allows renal tumor enucleation without dissection and clamping of the renal pedicle. The purpose was to assess the potential negative impact of embolization on the renal function. This prospective monocentric study included all patients treated with LPNE between May 2015 and June 2019. Clinical data was collected and incorporated into the UroCCR database (NCT03293563). Glomerular Filtration Rate (GFR) and Computed Tomography Renal Volume (CTRV) were compared before and after 6 months following LPNE. The mean post-operative GFR was 86.6 mL/min (SD 22.9). The mean GFR loss was 9.4% (SD 15.1) and the median renal parenchyma loss was 21 mL (SD 20.6). Using a threshold of 25% GFR loss, age was the only significant predictive factor of renal function impairment according to bivariate (59.5 vs 69.3 years, p = 0.017) and multivariable analysis (OR 1.075, CI 1–1.2], p = 0.05). Significant renal function impairment was not correlated with the renal parenchymal volume loss (OR 0.987, CI [0.95–1.02], p = 0.435). Renal function impairment after LPNE seems to be comparable to other techniques of partial nephrectomy.

Development and Validation of a Nomogram Model to Predict Acute Kidney Disease After Nephrectomy in Patients with Renal Cell Carcinoma

Purpose

To develop and validate a nomogram model to predict the occurrence of acute kidney disease (AKD) after nephrectomy.

Patients and Methods

A retrospective cohort including 378 patients with renal cell carcinoma (RCC) who had undergone radical or partial nephrectomy between March 2013 and December 2017 at the First Affiliated Hospital of Zhengzhou University was analyzed. Of these, patients who had undergone surgery in an earlier period of time formed the training cohort (n=265) for nomogram development, and those who had undergone surgery thereafter formed the validation cohort (n=113) to confirm the model's performance. The incidence rate of AKD was measured. Univariate and multivariate logistics regression analysis was used to estimate the independent risk factors associated with AKD. The independent risk factors were incorporated into the nomogram. The accuracy and utility of the nomogram were evaluated by calibration curve and decision curve analysis, respectively.

Results

Overall, AKD occurred in 27.5% and 28.3% of patients in the training and validation cohorts, separately. The final nomogram included surgery approach, Charlson comorbidity index (CCI), and the decrement of eGFR. This model achieved good concordance indexes of 0.78 (95% CI=0.71-0.84) and 0.76 (95% CI=0.67-0.86) in the training and validation cohorts, respectively. The calibration curves and decision curve analysis (DCA) demonstrated the accuracy and the clinical usefulness of the proposed nomogram, separately.

Conclusion

The nomogram accurately predicts AKD after nephrectomy in patients with RCC. The risk for patients' progress into AKD can be determined, which is useful in guiding clinical decisions.

Independent external validation of a nomogram to define risk categories for a significant decline in estimated glomerular filtration rate after robotic-assisted partial nephrectomy

OBJECTIVE

To validate the Martini nomogram predicting the decline in estimated glomerular filtration rate after robotic-assisted partial nephrectomy.

METHODS

Estimated 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.

RESULTS

The 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).

CONCLUSIONS

The 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.