A Novel Nephrometry Scoring System for Predicting Peri-operative Outcomes of Retroperitoneal Laparoscopic Partial Nephrectomy
The management of renal cell carcinoma (RCC) increasingly emphasizes nephron-sparing approaches such as partial nephrectomy (PN), which balances oncological control with preservation of renal function. Laparoscopic partial nephrectomy (LPN) via the retroperitoneal approach is a technically challenging procedure due to anatomical complexities and variable tumor characteristics. Existing nephrometry scoring systems, including the RENAL score (RNS) and Mayo adhesive probability (MAP) score, focus on tumor anatomy or patient-specific factors like adherent perirenal fat (APF) but lack integration of these aspects. This study introduces the RNP score, a novel nephrometry system combining optimized components of the RNS and MAP score, to predict peri-operative outcomes of retroperitoneal LPN with improved accuracy and reproducibility.
Background and Rationale
Renal tumor complexity, quantified by scoring systems like RNS, PADUA, and DAP, correlates with surgical outcomes such as operative time, blood loss, and ischemia duration. However, these systems overlook patient-specific factors influencing surgical difficulty, particularly APF. APF, characterized by inflammatory adipose tissue, complicates kidney mobilization and tumor isolation, increasing operative time and bleeding risk. The MAP score, which evaluates posterior perinephric fat thickness and stranding on preoperative CT scans, predicts APF but does not integrate tumor anatomical features. Recognizing the limitations of existing tools, this study aimed to develop a unified scoring system that accounts for both tumor complexity and perinephric fat characteristics to optimize surgical planning and outcome prediction.
Methodology
Patient Cohort and Surgical Technique
A retrospective analysis included 159 patients undergoing retroperitoneal LPN for cT1 RCC between January 2015 and August 2016. Exclusion criteria encompassed congenital kidney anomalies, solitary kidneys, coagulation disorders, and prior abdominal surgery. All procedures followed standardized retroperitoneal LPN techniques, emphasizing tumor excision under ultrasound guidance and renal reconstruction with controlled ischemia.
Radiological Assessment
Preoperative contrast-enhanced CT scans were analyzed by three independent scorers (two radiologists, one urologist) blinded to surgical outcomes. The RNS components (tumor radius [R], exophytic/endophytic property [E], nearness to sinus/collecting system [N], and polar location [L]) and MAP score components (posterior fat thickness, stranding) were evaluated. Discrepancies were resolved by a senior radiologist.
Outcome Measures
Primary outcomes included operative time, estimated blood loss (EBL), and MIC achievement rate—a composite endpoint defined by negative surgical margins, warm ischemia time (WIT) <20 minutes, and absence of Clavien III/IV complications.
Statistical Analysis
Univariate and multivariate regression analyses identified predictors of outcomes. The RNP score was developed using independent predictors. Receiver operating characteristic (ROC) curves compared predictive performance between scoring systems. Inter-observer agreement was assessed using kappa statistics.
Key Findings
Independent Predictors of Outcomes
Univariate analysis associated operative time with R score (tumor radius), N score (nearness to sinus), posterior fat thickness, and stranding (all P < 0.05). Multivariate analysis confirmed R score (β = 24.753, P = 0.014), N score (β = 10.183, P = 0.034), and posterior fat thickness (β = 16.536, P = 0.014) as independent predictors. For EBL, only R score (β = 34.964, P = 0.039) remained significant, while N score predicted MIC achievement (OR = 0.627, P = 0.046).
Development of the RNP Score
The RNP score integrates three components:
- R score: Tumor radius (≤4 cm = 1 point; 4.1–6.9 cm = 2; ≥7 cm = 3).
- N score: Nearness to sinus/collecting system (≥7 mm = 1; 4.1–6.9 mm = 2; ≤4 mm = 3).
- Posterior fat thickness: Perirenal fat on CT (<1.0 cm = 1; 1.1–1.9 cm = 2; ≥2.0 cm = 3).
Scores range from 3 to 9, stratifying tumors into low (3–4), moderate (5–6), and high complexity (7–9).
Predictive Performance of RNP
The RNP score demonstrated strong associations with peri-operative outcomes:
- Operative time: Median times were 125, 142, and 213 minutes for low, moderate, and high complexity groups (P < 0.001).
- EBL: Median losses were 10, 20, and 50 mL (P < 0.001).
- MIC achievement: Rates declined from 42.4% (low) to 13.3% (high) (P = 0.031).
Multivariate analysis confirmed RNP as an independent predictor of operative time (β = 17.749, P < 0.001), EBL (β = 20.725, P = 0.018), and MIC rate (OR = 0.523, P = 0.023).
Comparative Analysis with RNS and MAP
ROC curves revealed superior performance of RNP versus RNS for predicting operative time >150 minutes (AUC 0.697 vs. 0.569, P = 0.004) and EBL >20 mL (AUC 0.701 vs. 0.591, P = 0.014). RNP also outperformed MAP in predicting EBL (P = 0.011) and MIC rate (P = 0.008).
Inter-observer Agreement
RNP showed higher inter-observer agreement (76.7% vs. 57.8%) and kappa values (0.804 vs. 0.726) compared to RNS. Posterior fat thickness had the best agreement (kappa = 0.883), while stranding scored poorly (kappa = 0.585).
Discussion
Clinical Implications
The RNP score addresses critical gaps in existing nephrometry systems by combining tumor anatomy (R, N) with perinephric fat thickness, a surrogate for APF. Unlike RNS, which overemphasizes less impactful factors like tumor exophyticity, RNP prioritizes radius and proximity to critical structures—key drivers of technical complexity. The inclusion of posterior fat thickness acknowledges the biomechanical challenges posed by APF, which increases dissection difficulty and bleeding risk.
Advantages Over Existing Systems
RNP’s design eliminates subjective components (e.g., E score) and simplifies scoring to three quantifiable CT parameters. This enhances reproducibility, as evidenced by superior inter-observer agreement. For urologists, RNP provides a pragmatic tool to stratify patients, anticipate operative challenges, and guide preemptive measures like vascular control or adjunct imaging.
Limitations and Future Directions
Retrospective design and single-institution data limit generalizability. Variability in surgeon experience and exclusion of transperitoneal LPN cases may bias outcomes. Future validation in diverse cohorts and comparison with other systems (e.g., DAP, PADUA) will strengthen clinical utility. Additionally, incorporating 3D reconstruction or AI-based measurements could further refine predictive accuracy.
Conclusion
The RNP score represents a significant advancement in nephrometry by harmonizing tumor complexity and perirenal fat characteristics. Its strong predictive performance and reproducibility make it a valuable tool for optimizing patient selection and surgical planning in retroperitoneal LPN. By integrating anatomical and patient-specific factors, RNP enhances the precision of outcome prediction, ultimately supporting improved clinical decision-making and patient care.
doi.org/10.1097/CM9.0000000000000668
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