Value of 18F-FDG PET metabolic parameters combined with the dynamic monitoring of molecular residual disease (MRD) in predicting the prognosis of non-small-cell lung cancer after surgery
You Cheng , Guo-Jian Huang , Xiao-bo Chen , Hao-yu Zhu , Kai-yu Lu , Fan Yang , Jia-tao Zhang , Zai-yi Liu , Dan Shao
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引用次数: 0
Abstract
Objective
To study the ability of the combination of 18F-FDG positron-emission tomography/computed tomography (PET/CT) metabolic parameters and the dynamic monitoring of molecular residual disease (MRD) in predicting the prognosis of non-small-cell lung cancer (NSCLC) after surgery.
Methods
The clinical data and disease-free survival (DFS) data of 157 NSCLC patients who underwent 18F-FDG PET/CT at 2 weeks before surgery and were regularly monitored for MRD after surgery were retrospectively analyzed. The correlation between PET metabolic parameters and the dynamic monitoring of MRD and the values of the two in predicting prognosis of NSCLC were analyzed.
Results
Survival analysis revealed that patients with elevated 18F-FDG PET metabolism had a worse prognosis, while MRD-positive patients had a significantly worse prognosis than MRD-negative patients. By combining of PET metabolic parameters and MRD status, the PET-high-metabolism + MRD-positive group had a worse prognosis than the PET-high-metabolism + MRD-negative group or the PET-low-metabolism + MRD-positive group and the PET-low-metabolism + MRD-negative group. The prognostic model established by tumor TNM staging, clinical data and PET metabolic parameters(comd 1 model) had a high predictive value (C-index: 0.759, 95 % CI: 0.683–0.835). After adding this model to the MRD detection results(comd 2 model), the prognostic accuracy of the model improved (C-index: 0.873, 95 % CI: 0.824–0.922).
Conclusion
The prognostic model made up of Tumor TNM staging,18F-FDG PET metabolic parameters and clinical data can accurately predict recurrence in NSCLC patients after surgery. Incorporating the results of the dynamic monitoring of MRD detection into the model can significantly enhance its the prognostic accuracy.
期刊介绍:
Lung Cancer is an international publication covering the clinical, translational and basic science of malignancies of the lung and chest region.Original research articles, early reports, review articles, editorials and correspondence covering the prevention, epidemiology and etiology, basic biology, pathology, clinical assessment, surgery, chemotherapy, radiotherapy, combined treatment modalities, other treatment modalities and outcomes of lung cancer are welcome.