Evaluation of the E-PASS, mE-PASS, and POSSUM scoring systems for predicting postoperative complications following radical nephrectomy

BACKGROUND: Accurate prediction of postoperative complications following radical nephrectomy is of great clinical importance for perioperative risk stratification and patient management. Although several scoring systems are used in urological surgery, there is no widely accepted, procedure-specific risk assessment tool. This study aimed to evaluate the performance of the Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (POSSUM), Estimation of Physiologic Ability and Surgical Stress (E-PASS), and its modified version (mE-PASS) in predicting postoperative complications after radical nephrectomy. As a secondary objective, the association between modified Glasgow Prognostic Score (mGPS), Prognostic Nutritional Index (PNI), and neutrophil-to-lymphocyte ratio (NLR), which reflect systemic inflammation and nutritional status, and postoperative complications was also investigated. MATERIALS AND METHODS: A total of 148 patients who underwent radical nephrectomy for renal tumors at our institution between January 2022 and March 2025 were retrospectively analyzed. Patients were divided into two groups based on the presence of postoperative complications. Postoperative complications were assessed according to the Clavien-Dindo classification, and complications of grade ≥ 2 were included in the analysis. Demographic characteristics, comorbidities, preoperative laboratory parameters, surgical variables, and postoperative outcomes were recorded. The predictive performance of the scoring systems was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). RESULTS: Postoperative complications were observed in 51 patients (34.5%). The POSSUM score demonstrated the highest predictive performance with an AUC of 0.810, showing high sensitivity (82.4%) and specificity (71.1%). The E-PASS score was also statistically significant but exhibited a more limited predictive performance (AUC: 0.682). In contrast, the mE-PASS score showed markedly lower predictive ability (AUC: 0.599). Patients who developed complications had significantly lower PNI values and higher NLR values (p < 0.05). Additionally, intraoperative blood loss, tumor size, and length of hospital stay were significantly greater in the complication group (p < 0.05). CONCLUSION: POSSUM and E-PASS may serve as useful tools for predicting postoperative complications following radical nephrectomy. However, given their moderate predictive performance and the limitations of the present study, these findings should be validated in larger, prospective, multicenter studies.

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Journal
BMC Surgery
Published
2026-06-16
DOI
https://doi.org/10.1186/s12893-026-03960-7
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
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article
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article

Evaluation of the E-PASS, mE-PASS, and POSSUM scoring systems for predicting postoperative complications following radical nephrectomy

Kadir Karkin, Adem Altunkol, Mert Hamza Özbilen, Ergün Alma et al.
BMC Surgery
Inflammatory Biomarkers in Disease Prognosis
article

Evaluation of the E-PASS, mE-PASS, and POSSUM scoring systems for predicting postoperative complications following radical nephrectomy

Kadir Karkin, Adem Altunkol, Mert Hamza Özbilen, Ergün Alma, Hakan Anıl, Buğra Aksay, Umit Uysal, Yusuf Enes Kök, Cafer Tayyer Akçor
article en

Abstract

BACKGROUND: Accurate prediction of postoperative complications following radical nephrectomy is of great clinical importance for perioperative risk stratification and patient management. Although several scoring systems are used in urological surgery, there is no widely accepted, procedure-specific risk assessment tool. This study aimed to evaluate the performance of the Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (POSSUM), Estimation of Physiologic Ability and Surgical Stress (E-PASS), and its modified version (mE-PASS) in predicting postoperative complications after radical nephrectomy. As a secondary objective, the association between modified Glasgow Prognostic Score (mGPS), Prognostic Nutritional Index (PNI), and neutrophil-to-lymphocyte ratio (NLR), which reflect systemic inflammation and nutritional status, and postoperative complications was also investigated. MATERIALS AND METHODS: A total of 148 patients who underwent radical nephrectomy for renal tumors at our institution between January 2022 and March 2025 were retrospectively analyzed. Patients were divided into two groups based on the presence of postoperative complications. Postoperative complications were assessed according to the Clavien-Dindo classification, and complications of grade ≥ 2 were included in the analysis. Demographic characteristics, comorbidities, preoperative laboratory parameters, surgical variables, and postoperative outcomes were recorded. The predictive performance of the scoring systems was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). RESULTS: Postoperative complications were observed in 51 patients (34.5%). The POSSUM score demonstrated the highest predictive performance with an AUC of 0.810, showing high sensitivity (82.4%) and specificity (71.1%). The E-PASS score was also statistically significant but exhibited a more limited predictive performance (AUC: 0.682). In contrast, the mE-PASS score showed markedly lower predictive ability (AUC: 0.599). Patients who developed complications had significantly lower PNI values and higher NLR values (p < 0.05). Additionally, intraoperative blood loss, tumor size, and length of hospital stay were significantly greater in the complication group (p < 0.05). CONCLUSION: POSSUM and E-PASS may serve as useful tools for predicting postoperative complications following radical nephrectomy. However, given their moderate predictive performance and the limitations of the present study, these findings should be validated in larger, prospective, multicenter studies.

BMC Surgery
Sağlık Bilimleri Üniversitesi (TR)
Zero hunger
Openalex Percentile: Top 12%
Inflammatory Biomarkers in Disease Prognosis
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