Risk Factors for Postoperative Pulmonary Complications in Esophageal Cancer: Focus on Inflammatory Markers

Mengchao Xue¹Zhang Ruihao¹Yirou Ma¹Yiyang Liu¹Junjie Liu²Zhenyi Li²Bingtao Huang³Zheng Ma²Ming Lu²Yongxin Zhou^1*

• ¹Tongji Hospital Affiliated to Tongji University, Shanghai, China
• ²Qilu Hospital of Shandong University, Jinan, China
• ³Binzhou Medical University Hospital, Binzhou, China

Background: In patients with esophageal cancer (EC), postoperative pulmonary complications (PPCs) have an impact on both the long-term prognosis and postoperative recovery. The prognostic utility of novel inflammatory biomarkers for PPCs is yet unknown, despite the fact that systemic inflammation is a hallmark of malignancy. The objective of this study was to methodically identify perioperative parameters that are independently linked to the formation of PPCs, with an emphasis on inflammatory markers. Methods: 781 individuals receiving elective EC resection between January 2022 and December 2024 were included in this retrospective, single-center cohort analysis. Patients were divided into two groups at random: a validation set (n = 232) and a training set (n = 549). To find independent factors linked to PPCs, univariate and multivariate logistic regression analyses were carried out. A nomogram based on the factors found was created for exploratory purposes, and its effectiveness was evaluated. Results: 11.7% of people had PPCs overall. Five independent predictors were found by multivariate analysis: the eosinophil count (OR=5.924, p=0.027), intraoperative pleural metastasis (OR=6.853, p=0.026), postoperative ICU admission(OR=6.963, p=0.006), and postoperative anastomotic leakage (OR=13.454, p=0.000) were found to be significant risk factors, while the LMR (OR=0.791, p=0.021) was a protective factor. Limited discriminative ability was demonstrated by the exploratory nomogram based on these parameters (AUC 0.665 in training, 0.561 in validation sets). With modified C-statistics of 0.666 and 0.557 for the training and validation sets, respectively, the DCA showed acceptable discriminatory performance. The DCA revealed a clinically net advantage throughout a broad range of threshold probabilities, and the model demonstrated satisfactory calibration (Hosmer-Lemeshow test p>0.05). Conclusion: Clinical parameters and inflammatory biomarkers are identified as independent risk factors for PPCs in EC patients. Higher LMR is a protective factor for PPCs, while postoperative ICU admission, higher eosinophil counts, intraoperative pleural metastases, and postoperative anastomotic leaks are risk factors. In order to lower the incidence of PPC, these results offer a theoretical foundation for clinical risk classification and focused preventive measures.