Limited Predictive Utility of Inflammatory Indices for Postoperative Complications in Primary Lung Cancer Surgery

Muharrem Özkaya,1 Nilay Çavuşoğlu Yalçın,1 Erhan Özyurt,2 Mehmet Tercan2 1Department of Thoracic Surgery, University of Health Sciences, Antalya Training and Research Hospital, Antalya, Türkiye; 2Department of Anesthesiology and Reanimation, University of Health Sciences, Antalya Training and Research Hospital, Antalya, TürkiyeCorrespondence: Muharrem Özkaya, Department of Thoracic Surgery, University of Health Sciences, Antalya Training and Research Hospital, Varlık Mahallesi, Kazım Karabekir Street No: 48, Muratpasa, Antalya, 07100, Türkiye, Tel +905326543438, Fax +902422494662, Email [email protected]: Systemic inflammatory indices such as the Pan-Immune Inflammation Value (PIV), Systemic Immune-Inflammation Index (SII), and Systemic Inflammation Response Index (SIRI) are recognized prognostic markers in oncology. Their potential role in predicting early postoperative complications after lung cancer surgery, however, remains uncertain.Methods: We retrospectively analyzed 68 patients who underwent pulmonary resection for primary lung cancer between January 2019 and November 2024. PIV, SII, and SIRI were calculated from preoperative and first postoperative day blood counts. Associations with 30-day complications were assessed using comparative statistics and receiver operating characteristic (ROC) analysis.Results: Complications occurred in 10 patients (14.7%). None of the indices differed significantly between patients with and without complications. ROC analysis demonstrated poor predictive performance across all indices (AUC range: 0.447– 0.612). A significant histology imbalance (p=0.039) suggested that tumor biology may have contributed to complication risk.Conclusion: Despite their established prognostic relevance in oncology, PIV, SII, and SIRI provided limited discrimination for early postoperative complications in lung cancer surgery. These negative findings underscore the importance of cautious interpretation, particularly given the small number of events and low statistical power. They highlight the limited perioperative utility of such indices, helping to prevent their overestimation in clinical practice, and point to the need for prospective studies exploring alternative predictive markers within multimodal models.Keywords: lung cancer, postoperative complications, PIV, SII, SIRI, inflammatory biomarkers, ROC analysis