Prognostic predictive value of baseline 18F-FDG PET/CT metabolic parameters in Hodgkin′s lymphoma
10.3760/cma.j.cn321828-20240816-00295
- VernacularTitle:基线 18F-FDG PET/CT代谢参数对霍奇金淋巴瘤预后的预测价值
- Author:
Haoan ZHANG
1
;
Yue TENG
;
Jingyan XU
;
Chongyang DING
Author Information
1. 中国药科大学南京鼓楼医院血液内科，南京 210008
- Publication Type:Journal Article
- Keywords:
Hodgkin disease;
Positron-emission tomography;
Tomography, X-ray computed;
Fluorodeoxyglucose F18;
Prognosis
- From:
Chinese Journal of Nuclear Medicine and Molecular Imaging
2025;45(10):589-594
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the prognostic value of a combined model of baseline 18F-FDG PET/CT tumor metabolic parameters and clinical factors for predicting progression-free survival (PFS) in Hodgkin′s lymphoma (HL). Methods:From January 2014 to May 2023, 171 HL patients (102 males, 69 females; median age 40 years) who underwent 18F-FDG PET/CT before treatment at the First Affiliated Hospital of Nanjing Medical University and Nanjing Drum Tower Hospital were retrospectively collected. HL patients from the First Affiliated Hospital of Nanjing Medical University were classified as the training set (101 patients) and HL patients from Nanjing Drum Tower Hospital were classified as the validation set (70 patients). Clinical factors and tumor metabolic parameters associated with PFS were determined by multivariate Cox regression analysis, and then the combined model and the independent model of each factor were constructed respectively. The consistency index (C-index) and AUC were used to evaluate the predictive efficacy of models, and nomogram was constructed based on the optimal model, and calibration curves were used to assess the goodness of fit of the models. The differences in Kaplan-Meier survival curves of the high-risk and low-risk groups were compared using log-rank test. Results:The multivariate Cox regression analysis indicated that the independent prognostic factors associated with PFS were the Lugano staging (hazard ratio ( HR)=3.10, 95% CI: 1.17-8.23, P=0.023), total metabolic tumor volume (TMTV) ( HR=2.65, 95% CI: 1.23-5.74, P=0.014), and maximum distance between tumors ( Dmax) ( HR=2.23, 95% CI: 1.02-4.85, P=0.044). These factors were used to construct the combined model, with the highest prognostic efficacy of the C-index for the training and validation sets of 0.692 and 0.653, and the AUC of 0.732 and 0.697, respectively. The calibration curves demonstrated that the predictions made by the combined model were in high agreement with the actual results in both the training and validation sets. The Kaplan-Meier analysis revealed a significantly lower PFS rate in the high-risk group compared to the low-risk group both in training and validation sets ( χ2 values: 5.88 and 4.52, P values: 0.015 and 0.033). Conclusion:The combined model incorporating tumor metabolic parameters and clinical factors improves prognostic efficacy in predicting PFS in HL patients.
