ArticleQuantitative imaging in medicine and surgery2021
Value of total lesion glycolysis and cell-of-origin subtypes for prognostic stratification of diffuse large B-cell lymphoma patients.
Article in Quantitative imaging in medicine and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Prognostic value ofQuantitative imaging in medicine and surgery · 2024Article
- Predicting diffuse large B-cell lymphoma outcomes with lesion-to-liver maximum standardized uptake value for interim-treatment and end-of-treatment positron emission tomography-computed tomography.Quantitative imaging in medicine and surgery · 2023Article
- Precision of quantitative parameters ofQuantitative imaging in medicine and surgery · 2023Article
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5 authors.
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Abstract
backgroundThis study aimed to explore the added prognostic value of baseline metabolic volumetric parameters and cell of origin subtypes to the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) in nodal diffuse large B-cell lymphoma (DLBCL) patients.
methodsA total of 184 consecutive
resultsWith a median follow-up of 35 months, the 3-year PFS and OS were 65.2% and 73.0%, respectively. In univariate analysis, total lesion glycolysis (TLG), cell-of-origin subtypes, and NCCN-IPI were both PFS and OS predictors. High TLG (≥1,852), non-germinal center B (non-GCB), as well as high NCCN-IPI (≥4), were shown to be independently significantly associated with inferior PFS and OS after multivariate analysis. Based on the number of risk factors (high TLG, non-GCB, and high NCCN-IPI), a revised risk model was designed, and the participants were divided into four risk groups with very different outcomes, in which the PFS rates were 89.7%, 66.2%, 51.7%, and 26.7% (χ
conclusionsThe TLG, cell-of-origin subtypes, and NCCN-IPI are independent prognostic survival factors in DLBCL patients. Moreover, the revised risk model composed of the number of risk factors (high TLG, non-GCB, and high NCCN-IPI) can stratify patients better than the NCCN-IPI, especially for patients at high risk, which suggests its potential integration into decision making for personalized medicine.
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