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

基于PET/CT的预后模型可提高血管免疫母细胞性T细胞淋巴瘤的早期生存预测准确性

阅读:2

Abstract

BACKGROUND: To 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. METHODS: We 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. RESULTS: SUVmax, 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. CONCLUSION: The new prediction model reliably estimates outcomes for AITL patients, demonstrating high discrimination and calibration.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。