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. 2019 Jun;40(6):632-638.
doi: 10.1097/MNM.0000000000001006.

Combining fluorine-18 fluorodeoxyglucose positron emission tomography and pathological risk factors to predict postoperative recurrence in stage I lung adenocarcinoma

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Combining fluorine-18 fluorodeoxyglucose positron emission tomography and pathological risk factors to predict postoperative recurrence in stage I lung adenocarcinoma

Chien-Chin Hsu et al. Nucl Med Commun. 2019 Jun.

Abstract

Objective: The aim of this study was to investigate the predictive value of qualitative assessment of tumor fluorine-18 fluorodeoxyglucose (F-FDG) uptake on PET and pathological risk factors for postoperative tumor recurrence in patients with stage I lung adenocarcinoma.

Patients and methods: Eighty-seven patients with stage I lung adenocarcinoma who had undergone F-FDG-PET and sequential surgical treatment without adjuvant chemotherapy were enrolled into this retrospective study. Qualitative assessment visually compared tumor F-FDG uptake with liver uptake. Tumors with one or more risk factors of tumor size of at least 4 cm, poorly differentiated, visceral pleural invasion, and lymphovascular invasion were defined as pathological high-risk tumors.

Results: Patients with pathological high-risk tumors had a significantly (P=0.015) higher standardized uptake value. A multivariable Cox's proportional hazard analysis showed that tumor F-FDG uptake>liver uptake (adjusted hazard ratio: 3.54; 95% confidence interval: 1.36-9.21, P=0.010) and pathological high-risk tumors (adjusted hazard ratio: 2.34; 95% confidence interval: 1.13-4.87, P=0.023) were significant independent predictors of postoperative tumor recurrence. Patients with tumor F-FDG uptake>liver uptake and pathological high-risk tumors had significantly (P=0.001) worse 5-year disease-free survival (38.8%) and significantly (P=0.011) worse overall survival (68.5%).

Conclusion: Tumor F-FDG uptake>liver uptake and pathological high-risk tumors were significant independent predictors of postoperative tumor recurrence in stage I lung adenocarcinoma. Combining the two factors improves the prediction of disease-free and overall survivals, which could offer a feasible prediction model for clinically recommending adjuvant chemotherapy.

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