Objective To investigate the value of baseline ¹⁸F-fluorodeoxyglucose (FDG) PET/CT metabolic parameters in primary and metastatic lesions for predicting the treatment efficacy and prognosis in patients with advanced non-small cell lung cancer (NSCLC) treated with first-line immunotherapy combined with chemotherapy.

Methods A retrospective analysis was conducted on clinical and imaging data from 86 patients with advanced NSCLC who underwent ¹⁸F-FDG PET/CT at the Affiliated Hospital of Qingdao University from December 2018 to September 2023. The patients included 73 males and 13 females, with an average age of (65.1±7.4) years. Treatment efficacy was evaluated after four cycles of immunotherapy, and patients were classified into a clinical benefit (CB) group and a non-clinical benefit (NCB) group. Metabolic parameters were measured using a cut-off values of 42% of the maximum standardized uptake value (SUV_max), including SUV_max of primary lesion, metabolic tumor volume of primary lesion (MTV_p), total lesion glycolysis of primary lesion (TLG_p), metabolic tumor volume of whole body (MTV_wb), total lesion glycolysis of whole body (TLG_wb), the ratio of SUV_max for metastatic to primary lesions (R-SUV_max), the ratio of metabolic tumor volume for metastatic to primary lesions (R-MTV), the ratio of total lesion glycolysis for metastatic to primary lesions (R-TLG). Normally distributed measurement data were compared using two independent sample t-test (equal variances assumed), whereas non-normally distributed measurement data were analyzed using Mann-Whitney U test. Count data were compared using chi-square test. Binary Logistic regression was performed for multivariate analysis, and a composite model was constructed on the basis of statistically significant parameters. Receiver operating characteristic (ROC) curves were plotted to determine the optimal cut-off values of each parameter and predictive performance. Progression-free survival (PFS) curves was plotted using the Kaplan-Meier method, and the Log-rank test was employed to compare differences in PFS among patients under different parameter cut-off values. Variables with statistical significance in univariate analysis (differences between groups) were included in a multivariate Cox proportional hazard regression model to identify independent predictors of PFS.

Results The CB group included 57 patients (66.28%, 57/86), and the NCB group included 29 patients (33.72%, 29/86). The median follow-up duration was 26.5 months. By the end of follow-up, disease progression occurred in 64 patients (74.42%, 64/86), with a median PFS of 8 months, ranging from 1 to 55 months. Univariate analysis revealed significant differences between CB group and NCB group in clinical stage, MTV_p, TLG_p, R-SUV_max, R-MTV, and R-TLG (χ²=5.570, Z=from −2.909 to −1.998; all P<0.05), these as risk factors for predicting the efficacy of immunotherapy in patients with advanced NSCLS. Multivariate analysis showed that clinical stage (OR=0.277, 95%CI: 0.085–0.909; P=0.034), R-MTV (OR=0.231, 95%CI: 0.068–0.780; P=0.018), and R-TLG (OR=1.812, 95%CI: 1.067–3.074; P=0.028) were independent predictors of immunotherapy efficacy in patients with advanced NSCLC. ROC curve analysis demonstrated an area under the curve of 0.696 (95%CI: 0.574–0.817) for the composite model, with a sensitivity of 0.554 and specificity of 0.852. Kaplan-Meier survival analysis indicated that advanced clinical stage, higher R-MTV, and higher R-TLG were associated with shorter patient survival and poorer prognosis. Cox proportional hazards regression model analysis identified R-MTV (HR=1.443, 95%CI: 1.109–1.877; P=0.006) and R-TLG (HR=0.862, 95%CI: 0.772–0.963; P=0.008) as independent prognostic factors for PFS in patients with advanced NSCLC.

Conclusions R-MTV, R-TLG, and clinical stage can predict immunotherapy efficacy in patients with advanced NSCLC. R-MTV and R-TLG are independent prognostic factors of PFS in NSCLC patients.