clinical and survival impact of fdg pet in patients with suspicion of recurrent ovarian cancer: a 6-year follow-up

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ID: 175273
2015
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Abstract
Background: The aim of this retrospective study was to evaluate the contribution of FDG PET to the clinical management and survival outcome of patients (pts) suspected of recurrent ovarian carcinoma, with the hypothesis that early diagnosis of recurrent ovarian cancer may improve overall survival. Methods: 53 FDG PET/CT scans were retrospectively analyzed for 42 pts. CT and PET/CT findings were confirmed by imaging and clinical follow-up, and/or pathology which was considered as the gold standard diagnosis. The treatment plan based on CT staging was compared with that based on PET/CT findings. Medical records were reviewed for pts characteristics, progression free survival (PFS) and overall survival (OS). Progression-free survival (PFS) and overall survival (OS) were analyzed using the Cox proportional hazards regression model. Results: The final diagnosis of recurrence was established pathologically (n=16), or by a median clinical follow-up of 6.5 years (range 0.5-7.5) after the PET/CT (n=37). PET/CT provided a higher detection sensitivity (92.2%, 47/51) than CT (60.8%, 31/51) (p<0.001). Globally, PET/CT modified the treatment plan in 56.6% (30/53) of and in 65,2% (14/23) when the CT was negative prior to PET/CT. In 30 cases, that benefited from a modified treatment plan, these changes led to the intensification of a previous treatment procedure in 83.3% (25/30), and to a reduction in the previous treatment procedure in 16.6% of cases (5/30). The Cox regression multivariate analysis showed that the number of lesions visualized by CT, and presence of lung lesions detected by PET/CT, were significantly associated with PFS (p=0.002 and p = 0.035, respectively). Conclusion: On account of its impact on treatment planning, and especially patient outcome, FDG PET is a valuable diagnostic tool for cases of suspected ovarian cancer recurrence.
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erusu2015frontiersclinical Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Daniela eRusu;Thomas eCarlier;Thomas eCarlier;Mathilde eColombié;Dorothée eGoulon;Vincent eFleury;Nicolas eRousseau;Dominique eBerton-Rigaud;Isabelle eJaffre;Françoise eKraeber-Bodéré;Françoise eKraeber-Bodéré;Loic eCampion;Loic eCampion;Caroline eRousseau;Caroline eRousseau
Journal Stroke
Year 2015
DOI
10.3389/fmed.2015.00046
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