While the Charlson Comorbidity Index (CCI) remains a widely used tool for perioperative risk stratification, it was developed in 1987 and is not specific to the biological and technical complexity of RCC surgery. Our hypothesis was that integrating systemic inflammatory markers into the CCI framework could yield a more precise and clinically useful model for identifying patients at higher perioperative risk.
We analyzed data from 4,122 patients across four high-volume academic centers who underwent partial or radical nephrectomy for non-metastatic RCC. Using Akaike Information Criterion modeling, we identified optimal cutoffs for each biomarker (NLR > 2.7, PLR > 200, De Ritis ratio > 2.3). Major complications, defined as Clavien-Dindo grade > 2, occurred in 4.8% of patients. All three biomarkers were independently associated with increased odds of major complications, and incorporating them into a model with CCI and clinicopathologic covariates improved predictive accuracy from an AUC of 0.63 (CCI alone) to 0.85, with stable performance after internal validation (bootstrapped AUC 0.77).
These findings have important clinical implications. First, NLR, PLR, and the De Ritis ratio are already included in routine preoperative laboratory panels, requiring no additional cost. Second, they are potentially modifiable, opening the door to targeted “prehabilitation” strategies aimed at reducing systemic inflammation before surgery. Even in our cohort of patients without overt inflammatory disease, who were hence suitable for elective surgery, subtle biomarker elevations were associated with worse outcomes, suggesting a need for proactive optimization.
Beyond enhancing surgical risk prediction, such markers may help refine treatment selection for patients at elevated risk, including consideration of less invasive alternatives. Their integration into preoperative assessment could also support more individualized postoperative monitoring and patient counseling.
Limitations include the retrospective nature of the study, the absence of postoperative biomarker data, and the need for external validation. Nevertheless, this work provides a pragmatic and scalable step toward modernizing perioperative risk assessment in RCC – one that anchors decision-making in both comorbidity and host inflammatory status. Future studies should aim to refine and validate these tools to optimize patient care in an individualized setting, shifting the paradigm toward truly patient-centered rather than disease-centered management.
Written by: Giacomo Musso,1,2 Ithaar H. Derweesh3
- Division of Experimental Oncology/Unit of Urology; URI; IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Urology, UC San Diego School of Medicine, La Jolla, CA, USA