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Prognostic Value of Metabolic Tumor Volume and Lesion Dissemination from Baseline PET/CT in Patients with Diffuse Large B-cell Lymphoma: Further Risk Stratification of the Group with Low-risk and High-risk NCCN-IPI

Overview
Journal Eur J Radiol
Specialty Radiology
Date 2023 Apr 8
PMID 37030099
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Abstract

Purpose: The purpose of this study was to determine the prognostic value of metabolic tumor volume and lesion dissemination from baseline PET/CT in patients with diffuse large B-cell lymphoma (DLBCL) and the prognostic value of them in the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) subgroups.

Methods: A total of 113 patients who underwent F-FDG PET/CT examination in our institution were retrospectively collected. The MTV was measured by iterative adaptive algorithm. The location of the lesion was obtained according to its three-dimensional coordinates, and Dmax was obtained. SDmax is derived from Dmax standardized by body surface area (BSA). The X-tile method was used to determine the optimal cut-off values for MTV, Dmax and SDmax. Cox regression analysis was used to perform univariate and multivariate analyses. Patient survival rates were derived from Kaplan-Meier curves and compared using the log-rank test.

Results: The median follow-up time was 24 months. The median of MTV was 196.86 cm (range 2.54-2925.37 cm), and the optimal cut-off value was 489 cm. The median of SDmax was 0.25 m (range 0.12-0.51 m), and the best cut-off value was 0.31 m. MTV and SDmax were independent prognostic factors of PFS (all P < 0.001). Combined with MTV and SDmax, the patients were divided into three groups, and the difference of PFS among the groups was statistically significant (P < 0.001), and was able to stratify the risk of NCCN-IPI patients in the low-risk (NCCN-IPI < 4) and high-risk (NCCN-IPI ≥ 4) groups (P = 0.001 and P = 0.031).

Conclusion: MTV and SDmax are independent prognostic factors for PFS in DCBCL patients, which describe tumor burden and tumor dissemination characteristics, respectively. The combination of the two could facilitate risk stratification between the low-risk and high-risk NCCN-IPI groups.

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