PET/CT-Based prognostic model enhances early survival prediction in angioimmunoblastic t-cell lymphoma

PET/CT-Based prognostic model enhances early survival prediction in angioimmunoblastic t-cell lymphoma

BackgroundTo develop and validate a new prognostic model using baseline PET parameters and clinical indicators for predicting early overall survival (OS) in Angioimmunoblastic T-cell lymphoma (AITL) patients.MethodsWe conducted a retrospective cohort study from December 2009 to December 2023 (n=124)...

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Bibliographic Details
Main Authors: Xiaoxia Xu, Xiangxiang Ding, Xiao Jin, Yunfei Shi, Zhi Yang, Nan Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Immunology
Subjects:
angioimmunoblastic T-cell lymphoma
PET/CT
overall survival
prediction model
cox regression model
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2025.1607177/full
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Summary:BackgroundTo develop and validate a new prognostic model using baseline PET parameters and clinical indicators for predicting early overall survival (OS) in Angioimmunoblastic T-cell lymphoma (AITL) patients.MethodsWe conducted a retrospective cohort study from December 2009 to December 2023 (n=124) at a single center. The model’s predictors included baseline clinical characteristics, pathological indicators, laboratory metrics, and PET/CT parameters. Independent prognostic factors were identified using Cox regression and presented as nomograms. The C-index assessed predictive accuracy, while calibration plots and decision curve analysis evaluated prediction accuracy and discrimination ability. The model’s accuracy was compared with existing prognostic systems using C-index, NRI, ROC, and Kaplan-Meier survival curves.ResultsSUVmax, β2MG, platelet, and albumin were identified as independent risk factors. The C-index for OS was 0.78 (95% CI: 0.70-0.85); for 1000 bootstrap samples, it was 0.76 (95% CI: 0.61-0.93). Calibration curves showed excellent agreement between predictions and actual observations. The AUC for 6-month and 1-year OS were 0.91(95% CI: 0.82-1.00) and 0.85 (95% CI: 0.77–0.94), respectively. The model outperformed PIAI, IPI, and PIT in predictive capacity.ConclusionThe new prediction model reliably estimates outcomes for AITL patients, demonstrating high discrimination and calibration.
ISSN:1664-3224

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