Interim PET in Diffuse Large B-Cell Lymphoma.

J Nucl Med

Institut für Medizinische Informatik, Statistik und Epidemiologie, Universität Leipzig, Leipzig, Germany.

Published: August 2021

In diffuse large B-cell lymphoma, early assessment of treatment response by F-FDG PET may trigger treatment modification. Reliable identification of good and poor responders is important. We compared 3 competing methods of interim PET evaluation. Images from 449 patients participating in the "PET-Guided Therapy of Aggressive Non-Hodgkin Lymphomas" trial were reanalyzed by applying the visual Deauville score and the SUV-based qPET (q = quantitative) and ΔSUV scales to interim PET scans performed after 2 cycles of chemotherapy. qPET relates residual lymphoma F-FDG uptake to physiologic liver uptake, converting the ordinal Deauville scale into a continuous scale and permitting a direct comparison with the continuous ΔSUV scale, which is based on SUV changes between baseline and interim scans. Positive and negative predictive values were calculated for progression-free survival. When established thresholds were used to distinguish between good and poor responders (visual Deauville score 1-3 vs. 4-5; ΔSUV > 66% vs. ≤ 66%), the positive predictive value was significantly lower with Deauville than ΔSUV (38.4% vs. 56.6%; = 0.03). qPET and ΔSUV were strongly correlated on the log scale (Pearson = 0.75). When plotted along corresponding percentiles, the positive predictive value curves for qPET and ΔSUV were superimposable, with low values up to the 85th percentile and a steep rise thereafter. The recommended threshold of 66% SUV reduction for the identification of poor responders was equivalent to qPET = 2.26, corresponding to score 5 on the visual Deauville scale. The negative predictive value curves were also superimposable but remained flat between 80% and 70%. Continuous scales are better suited for interim PET-based outcome prediction than the ordinal Deauville scale. qPET and ΔSUV essentially carry the same information. The proportion of poor-risk patients identified is less than 15%.

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http://dx.doi.org/10.2967/jnumed.120.255034DOI Listing

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