The Clinical Role of Systemic Inflammation-Based Biomarkers in Predicting Mortality in Post-Pneumonectomy Bronchopleural Fistula: A Multicenter Retrospective Analysis.

Background: Post-pneumonectomy bronchopleural fistula (PPBPF), although infrequent, represents one of the most devastating complications after pneumonectomy, carrying high morbidity and mortality. Accurate risk stratification is essential for timely management. Systemic inflammation-based hematologic indices-such as neutrophil-to-lymphocyte ratio (NLR), C-reactive protein/albumin ratio (CAR), systemic inflammation response index (SIRI), systemic immune-inflammation index (SIII), prognostic immune-inflammation index (PIII), and platelet-to-lymphocyte ratio (PLR)-serve as accessible, low-cost biomarkers reflecting host immune status and inflammatory burden. This study aimed to evaluate their association with mortality risk in patients with PPBPF. Methods: A multicenter retrospective cohort of 33 PPBPF patients (2014-2023) was analyzed. Demographic, clinical, and laboratory data at diagnosis were retrieved. Inflammatory indices were calculated from hematologic parameters. Associations with mortality were assessed using receiver operating characteristic (ROC) curves and univariate logistic regression. Post hoc power analyses were performed for key biomarkers. Results: Nine patients (27.3%) died during follow-up. Non-survivors had significantly higher levels of all biomarkers (p < 0.05). ROC analysis identified NLR as the most powerful discriminatory marker (AUC: 0.862), while SIII, SIRI, and CAR also demonstrated high accuracy (AUC > 0.83). Optimal thresholds of NLR ≥ 12 and CAR ≥ 10 yielded 88.9% sensitivity, >80% specificity, and excellent negative predictive values (NLR: 94.4%; CAR: 94.7%). Post hoc power analysis demonstrated robust statistical power for SIRI (94.9%), CAR (87.2%), and SIII (84.5%). Conclusions: Systemic inflammation-based biomarkers, particularly NLR and CAR, show strong associations with mortality in PPBPF. Incorporating these indices into clinical practice may help identify patients at increased risk and facilitate tailored surveillance and management strategies.