Using the Systemic Inflammatory Response Index and the Prognostic Nutritional Index in Predicting Subsequent Bone Metastases in Patients with Non-Small Cell Lung Cancer

Peng Wang,1 Xiaojing Yan,2 Guangxuan Yan,3 Dan Li,4 Li Ma2,5 1Department of Orthopaedics, Beijing Luhe Hospital, Capital Medical University, Beijing, People’s Republic of China; 2Department of Medical Affairs, Beijing Chest Hospital, Capital Medical University & Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, People’s Republic of China; 3Department of Orthopaedics, Beijing Chest Hospital, Capital Medical University & Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, People’s Republic of China; 4Functional Examination Section, Cancer Hospital Chinese Academy of Medical Sciences, Beijing, People’s Republic of China; 5Department of Medical Oncology, Beijing Chest Hospital, Capital Medical University & Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, People’s Republic of ChinaCorrespondence: Li Ma, Email [email protected]: This study aimed to identify the risk factors for Bone Metastases (BM) in patients with non-small cell lung cancer (NSCLC) and develop a scoring system combining the systemic inflammatory response index (SIRI) and prognostic nutritional index (PNI) to predict subsequent bone metastases in patients with NSCLC.Methods: A retrospective analysis of patients with NSCLC treated at our hospital between February 2019 and January 2025 was conducted. Based on the occurrence of BM during follow-up, patients were stratified into the BM or the non-BM group. After their preoperative SIRI and PNI values were calculated, receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off values for SIRI and PNI, which were used to establish the SIRI–PNI scoring system. The SIRI–PNI scores were compared between the groups, and univariate and multivariate logistic regression analyses were performed to identify factors influencing BM development.Results: Among the 418 patients included with a mean follow-up of 11.91 ± 0.88 months (range: 9– 14 months), 142 were diagnosed with BM (33.97%). ROC analysis determined an optimal threshold of 539.0 for the SIRI (area under the curve [AUC] = 0.877; 95% confidence interval [CI]: 0.807– 0.947) and 44.8 for the PNI (AUC = 0.801; 95% CI: 0.689– 0.912). An SIRI–PNI scoring system was established, with scores ranging from 0 to 2. Clinical stage, lymph node metastasis, and SIRI–PNI score significantly differed between the BM and non-BM groups (P < 0.05). Multivariate analysis identified clinical stage IV (odds ratio = 11.91, P < 0.0001) and a SIRI–PNI score of 2 (P < 0.0001) as independent risk factors for BM.Conclusion: Advanced clinical stage (IV) and a high SIRI–PNI score (2 points) are significant prognostic indicators for BM development in patients with NSCLC. The preoperative SIRI–PNI scoring system may facilitate early identification of high-risk patients.Plain Language Summary: Bone Metastases (BM) are a frequent and debilitating complication of lung cancer, leading to skeletal-related events that severely compromise patient prognosis and quality of life. Early identification of high-risk individuals remains a clinical challenge, as current diagnostic methods are often resource-intensive and employed after symptomatic presentation.This study investigated the utility of a simple scoring system based on the systemic inflammatory response index (SIRI) and the prognostic nutritional index (PNI), both of which are derived from routine blood parameters, to predict the risk of subsequent BM in patients with non-small cell lung cancer (NSCLC).Analysis of 418 patients demonstrated that the combined SIRI and PNI score effectively stratified BM risk. Multivariate analysis identified advanced clinical stage (IV) and a high SIRI–PNI score as significant independent predictors of BM development.The proposed SIRI–PNI scoring system offers a readily accessible, non-invasive tool for the early risk stratification of patients with NSCLC. Its implementation could facilitate timely intervention strategies, such as enhanced surveillance or prophylactic bone-targeting therapy, to mitigate BM-related morbidity and improve clinical outcomes. Keywords: systemic inflammatory response index, prognostic nutritional index, non-small cell lung cancer, bone metastases, prediction