Abstract
8555 Background: Previous studies in cHL have demonstrated that conventional methods to risk stratify patients into various prognostic groups and predict PFS may not be sufficient to individualize therapy. Metabolic parameters using FDG-PET may be helpful for developing a prognostic algorithm and predict PFS. Objectives: To determine the best predictor of PFS among various variables of tm metabolic measurements at baseline and at interim PET/CT compared to conventional methods in cHL patients. Methods: Retrospective evaluation of prospectively acquired data in 58 cHL pts, all stages [IIB-IV:41%, >IPS-3:24%, unfavorable (UF):44%]. Eligibility: PET/CT prior to and after 1 cycle (PET1) ABVD therapy, imaging at 60min+15min, follow-up>24 mo. Baseline PET parameters including metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUVmax, and SULpeak were determined using gradient method (PETVCAR2, GE Healthcare, WI). Data were also evaluated at PET1 for %ΔMTV, %ΔSUVmax, %ΔTLG, PERCIST criteria and visually with Deauville 5-PS. Variables were correlated with PFS. Results: Median follow-up: 32.2 mo. Of 58 pts 14 relapsed (median PFS:6.5 mo). Results for PFS are displayed in the Table. No baseline conventional (stage, IPS, UF vs F) or PET variable was associated with PFS. The best predictor of PFS was Deauville 5-PS at PET1. PERCIST and %ΔTLG using gradient method trended toward significance. Conclusions: Deauville 5-PS best predicts PFS at PET1 in cHL. Neither baseline PET nor conventional prognostic factors correlated with PFS in this group of cHL pts. Risk-stratification of cHL using tumor metabolic volumetry and PERCIST criteria may require a larger sample size and further assessment of various methodologies. [Table: see text]
Published Version
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