Related Experiment Video
Updated: Dec 8, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Prognostic models integrating quantitative parameters from baseline and interim positron emission computed tomography
Emanuele Zucca1,2,3, Luciano Cascione2,4, Teresa Ruberto5
1Medical Oncology Clinic, Oncology Institute of Southern Switzerland, Bellinzona, Switzerland.
Abstract:
Positron emission computed tomography (PET/CT) in patients with diffuse large B-cell lymphoma (DLBCL) enrolled in a prospective clinical trial were reviewed to test the impact of quantitative parameters from interim PET/CT scans on overall (OS) and progression-free (PFS) survival. We centrally reviewed baseline and interim PET/CT scans of 138 patients treated with rituximab plus cyclophosphamide, doxorubicin, vincristine and prednisone given every 14 days (R-CHOP14) in the SAKK38/07 trial (ClinicalTrial.gov identifier: NCT00544219). Cutoff values for maximum standardized uptake value (SUVmax ), metabolic tumor volume (MTV), total lesion glycolysis (TLG) and metabolic heterogeneity (MH) were defined by receiver operating characteristic analysis. Responses were scored using the Deauville scale (DS). Patients with DS 5 at interim PET/CT (defined by uptake >2 times higher than in normal liver) had worse PFS (P = 0.014) and OS (P < 0.0001). A SUVmax reduction (Δ) greater than 66% was associated with longer PFS (P = 0.0027) and OS (P < 0.0001). Elevated SUVmax , MTV, TLG, and MH at interim PET/CT also identified patients with poorer outcome. At multivariable analysis, ΔSUVmax and baseline MTV appeared independent outcome predictors. A prognostic model integrating ΔSUVmax and baseline MTV discriminated three risk groups with significantly (log-rank test for trend, P < 0.0001) different PFS and OS. Moreover, the integration of MH and clinical prognostic indices could further refine the prediction of OS. PET metrics-derived prognostic models perform better than the international indices alone. Integration of baseline and interim PET metrics identified poor-risk DLBCL patients who might benefit from alternative treatments.
More Related Videos
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
09:32Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells
Published on: February 8, 2018