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ABSTRACT: Objective
This study aimed to investigate the prognosis value of 18F-fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) in advanced lung cancer patients with immunotherapy combined with chemotherapy.Methods
Fifty-one advanced lung cancer patients were included in this retrospective study, who underwent 18F-FDG PET/CT imaging before four cycles of immunotherapy combined with chemotherapy at our institution between January 2018 and January 2020. The following PET/CT parameters were calculated: standardized uptake value SUVmax, SUVmean, SUVpeak, SUVsd, metabolic tumor volume (MTV), total lesion glycolysis (TLG), MTV25%, MTV42%, MTV50%, MTV75%, global lung glycolysis (GLG), target-to-background ratio (TBR), SUVpeakwb, MTVwb, TLGwb, SUVmeanwb, SUVmaxwb. Logistics regression analyses were used for assessing the association between baseline metabolic parameters and response to treatment. Kaplan-Meier estimator curves and the log-rank test were constructed for survival analyses.Results
According to RECIST, nine patients (18%) showed partial response, 25 (49%) had SD, and 17 (33%) had progressive disease. The mean ± SD of SUVmax, SUVpeak, MTV were lower in clinical benefit (CB) group than no-clinical benefit (no-CB) group (all P < 0.05). Median PFS was 3.7 months in no-CB group and 9.9 months in CB group (P < 0.001). Multivariate logistic analysis indicated that SUVmax and histology were independent factors significantly related to the evaluation of therapeutic efficiency. Furthermore, SUVmax is an independent predictor of efficacy in non-small cell lung cancer.Conclusion
SUVmax can be used to predict interim treatment response of immunotherapy combination with chemotherapy for advanced lung cancer. Moreover, the combination of SUVmax and histology may predict treatment response with acceptable reliability. However, a large prospective multicenter trial is still needed to examine the above finding for lacking limited evidence.
SUBMITTER: Ke L
PROVIDER: S-EPMC8357040 | biostudies-literature |
REPOSITORIES: biostudies-literature