Systemic immune-inflammatory index is associated with malignancy in Lung-RADS 4 lung nodules.

BACKGROUND: Better stratification of malignancy risk among high-risk pulmonary nodules detected by low-dose computed tomography (LDCT) is needed. The objective of this study is to determine if an association exists between the systemic immune-inflammatory index (SII) and malignancy in patients with Lung CT Screening Reporting and Data System (Lung-RADS) 4 nodules identified on LDCT. METHODS: A retrospective review of patients who underwent LDCT at a single institution between March 2015 and December 2024 was performed to identify patients with Lung-RADS 4A/B/X nodules. Exclusion criteria included a missing complete blood count with differential, being lost to follow-up, and a diagnosis of inflammatory nodules, granulomas, or metastases from other primary cancers upon biopsy. Univariate and multivariate analyses were used to examine the association between SII and malignancy in Lung-RADS 4 nodules. Cut-point analysis was performed to determine the SII cutoff most strongly correlated with underlying malignancy. RESULTS: A total of 123 patients met study criteria. Among high-risk nodules, 63.4% (78/123) were diagnosed with lung cancer, and the median SII for the cohort was 589 (interquartile range, 360-819). On multivariable linear regression analysis, after adjusting for age, sex, race, smoking history, medical comorbidities, body mass index, and nodule size, individuals with malignant nodules had a significantly higher SII [+272; 95% confidence interval (CI): 75-470; P=0.007]. Utilizing Youden's index analysis, the optimal SII cutoff was 561. On multivariable logistic regression analysis, individuals with a high SII, using a cutoff of 561, had significantly greater odds of having malignant nodules (odds ratio 3.74; 95% CI: 1.42-9.85; P=0.008). CONCLUSIONS: An elevated SII is associated with malignancy in non-inflammatory Lung-RADS 4 nodules identified on LDCT. Incorporating SII calculation may serve as a useful adjunct for risk-stratification and prognostication in patients with high-risk pulmonary nodules.