459P - Comparison of predictive value betweenmetabolic tumor volume and RECIST 1.1 assessed by 18F-FDG PET-CT in patients with lung cancer
|Date||18 December 2016|
|Event||ESMO Asia 2016 Congress|
|Topics|| Non-Small-Cell Lung Cancer, Metastatic
Imaging, Diagnosis and Staging
|Citation||Annals of Oncology (2016) 27 (suppl_9): ix139-ix156. 10.1093/annonc/mdw594|
J. Lin1, Q. Hou2, Z. Dong1, W. Zhong1, Y. Li1, Y. Wu1
Metabolic tumor volume(MTV) measured by 18F-FDG PET-CT revealed the activity of cancer and may be a predictor of treatment response. We aimed to investigate the role of MTV in therapeutic response evaluation and its value asa surrogate marker when compared with RECIST 1.1.
A total of 90 cases with lung cancer underwent positron emission tomography-computed tomography(PET-CT) prior to(t0) and after(t1) initiation of treatment were enrolled. The response of treatment was determined according to response evaluation criteria in solid tumors 1.1(RECIST 1.1) and volume-based metabolic responseevaluation criteria in solid tumors(v-MECIST), respectively. Cutoff values of (MTV1-MTV0)/MTV0 were determined by receiver operating characteristic curves(ROC). Concordance betweenRECIST and v-MECIST was assessed by κcoefficient. Progression-free survival(PFS) and overall survival(OS) were compared according to RECIST and v-MECIST.
ROC curve analysis identified two cutoff values (-55% and +16%) to discriminatemetabolic partial response (MPR), metabolic stable disease (MSD) and metabolic progressive disease (MPD). The concordance rate between RECIST and v-MECISTwas 74.4% (κ = 0.602, P
In conclusion, change of MTV might be a useful PET-CT parameter for prognostication, the cutoff values determined by the change of MTV were effective in discriminating metabolic response.MTV based on v-MECIST isas suitable as RECIST in evaluating response of lung cancer, and maybe superior to RECIST in certain subset of lung cancer.
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With the submission of the abstract, I on behalf of myself, all co-authors, the first author (=presenter) undertakes the above items.
This work was supported by the Guangdong Provincial Key Laboratory of Lung Cancer Translational Medicine (Grant No. 2012A061400006), the Special Fund for Research in the Public Interest from the National Health and Family Planning Commission of PRC (Grant No. 201402031), and the Research Fund from Guangzhou Science and Technology Bureau (Grant No. 2011Y2–00014)
All authors have declared no conflicts of interest.