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[18F]FDG PET/CT in combination with clinicopathological parameters for outcome prediction in high-grade soft tissue
Shaoli Li1,2,3, Xiaohui Zhang4,5,6, Xiaogang Wang7
1Department of Medical Oncology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China.
Purpose:
This study aimed to investigate the prognostic value of [18F]FDG PET/CT and clinicopathological parameters in patients with high-grade soft tissue sarcoma (STS, Fédération Nationale des Centres de Lutte Contre le Cancer [FNCLCC] G2 or 3) undergoing surgical resection.
Methods:
A total of 102 patients with high-grade STS who underwent [18F]FDG PET/CT prior to surgery were retrospectively enrolled. PET metabolic parameters including maximum standardized uptake value (SUVmax), total metabolic tumour volume (TMTV), and total lesion glycolysis were measured using the LIFEx software. Cox regression analysis was used to develop nomograms to predict progression-free survival (PFS) and overall survival (OS) based on PET and clinicopathological parameters. The predictive performances of the nomograms were assessed using concordance index, receiver operating characteristic curve, and calibration curve. The clinical utilities of the nomograms were determined by decision curve analysis. The predictive efficiency of nomograms, TNM stage, and FNCLCC grading system were compared.
Results:
The median follow-up was 38.5 months. Multivariate analysis demonstrated that SUVmax, TMTV, and lactate dehydrogenase were independent predictors of PFS (all P < 0.05), while TMTV, neutrophil-to-lymphocyte ratio, lactate dehydrogenase, TNM stage, and Ki-67 index were independent predictors of OS (all P < 0.05). The established nomograms had signigicantly higher area under the curve than TNM stage and FNCLCC grading system (all P < 0.05). Decision curve analysis indicated that the nomograms had higher net benefits than TNM stage and FNCLCC grading system. In FNCLCC G3 group, TMTV effectively stratified patients into distinct prognostic subgroups (log-rank P < 0.05). Moreover, the expression of glutathione S-transferase π and glucose transporter 1 were significantly correlated with TMTV (both P < 0.05).
Conclusion:
The nomograms integrating pre-treatment [18F]FDG PET/CT and clinicopathological parameters could significantly improve outcome prediction in patients with high-grade STS. Furthermore, TMTV may provide additional prognostic value for FNCLCC G3 patients, who exhibit metabolic-molecular aggressive phenotypes.
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