Journal Article
Research Support, Non-U.S. Gov't
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Interim-treatment quantitative PET parameters predict progression and death among patients with Hodgkin's disease.

Radiation Oncology 2012 January 20
PURPOSE: We hypothesized that quantitative PET parameters may have predictive value beyond that of traditional clinical factors such as the International Prognostic Score (IPS) among Hodgkin's disease (HD) patients.

METHODS: Thirty HD patients treated at presentation or relapse had staging and interim-treatment PET-CT scans. The majority of patients (53%) had stage III-IV disease and 67% had IPS ≥ 2. Interim-treatment scans were performed at a median of 55 days from the staging PET-CT. Chemotherapy regimens used: Stanford V (67%), ABVD (17%), VAMP (10%), or BEACOPP (7%). Hypermetabolic tumor regions were segmented semiautomatically and the metabolic tumor volume (MTV), mean standardized uptake value (SUV mean), maximum SUV (SUV max) and integrated SUV (iSUV) were recorded. We analyzed whether IPS, absolute value PET parameters or the calculated ratio of interim- to pre-treatment PET parameters were associated with progression free survival (PFS) or overall survival (OS).

RESULTS: Median follow-up of the study group was 50 months. Six of the 30 patients progressed clinically. Absolute value PET parameters from pre-treatment scans were not significant. Absolute value SUV max from interim-treatment scans was associated with OS as determined by univariate analysis (p < 0.01). All four calculated PET parameters (interim/pre-treatment values) were associated with OS: MTV int/pre (p < 0.01), SUV mean int/pre (p < 0.05), SUV max int/pre (p = 0.01), and iSUV int/pre (p < 0.01). Absolute value SUV max from interim-treatment scans was associated with PFS (p = 0.01). Three calculated PET parameters (int/pre-treatment values) were associated with PFS: MTV int/pre (p = 0.01), SUV max int/pre (p = 0.02) and iSUV int/pre (p = 0.01). IPS was associated with PFS (p < 0.05) and OS (p < 0.01).

CONCLUSIONS: Calculated PET metrics may provide predictive information beyond that of traditional clinical factors and may identify patients at high risk of treatment failure early for treatment intensification.

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