Association between 12 composite inflammatory indices and postoperative complications in colorectal cancer surgery: a two-center retrospective study
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background Postoperative complications (POCs) remain a major challenge in colorectal cancer (CRC) surgery. Easily accessible composite inflammatory indices derived from routine blood tests hold promise for preoperative risk stratification, but their comparative predictive value for POCs is unclear. Methods We conducted a two-center, retrospective study of 1331 patients who underwent radical CRC surgery between January 2021 to October 2025. The associations between preoperative composite inflammatory indices and the complications after surgery were evaluated using logistic regression. Their predictive discriminative performances were further assessed and compared using receiver operating characteristic (ROC) curve analysis, with the areas under the curve (AUC) compared by DeLong’s test. Results The complication rate was 17.2% (229/1331). Patients with complications exhibited a significantly more pronounced pro-inflammatory and immunosuppressive preoperative profile across all indices (all P < 0.05). After adjustment, the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), C-reactive protein-to-lymphocyte ratio (CLR), and systemic inflammation response index (SIRI) were identified as the strongest independent predictors, with the highest quartile (Q4) conferring substantially increased risks (OR for SII: 7.51; for NLR: 5.86; for CLR: 2.24; for SIRI: 2.99; all P -trend <0.05). ROC analysis confirmed SII as the best single predictor (AUC: 0.738). A combined model integrating SII, NLR, CLR, and SIRI achieved superior discriminative ability (AUC: 0.792), significantly outperforming any single index (all P < 0.05). Conclusion The SII, NLR, CLR and SIRI, are strongly associated with the risk of POCs after CRC surgery. A model combining these four indices provides superior predictive performance.
Source: Frontiers in Oncology
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7155225394
