Recursive partitioning analysis model based on ¹⁸F-FDG PET/CT metabolic parameters for recurrent or metastatic nasopharyngeal carcinoma treated with PD-1 inhibitors and chemotherapy.

@article{zhang2026recursive,
  title = {{Recursive partitioning analysis model based on ¹⁸F-FDG PET/CT metabolic parameters for recurrent or metastatic nasopharyngeal carcinoma treated with PD-1 inhibitors and chemotherapy.}},
  author = {Huan Zhang and Ting Shen and Rongqin Fan and Fantong Xia and Siqi Cai and Jieying Yang and Jia Jiang and Yihong Hu and Yunchang Liu and Honglei Tu and Xin Zhang and Jiangdong Sui and Ying Wang},
  journal = {Cancer imaging : the official publication of the International Cancer Imaging Society},
  year = {2026},
  month = aug,
  doi = {10.1186/s40644-026-01102-z},
  url = {https://europepmc.org/article/MED/42972443},
  note = {CC BY-NC-ND},
}

TY  - JOUR
TI  - Recursive partitioning analysis model based on ¹⁸F-FDG PET/CT metabolic parameters for recurrent or metastatic nasopharyngeal carcinoma treated with PD-1 inhibitors and chemotherapy.
AU  - Huan Zhang
AU  - Ting Shen
AU  - Rongqin Fan
AU  - Fantong Xia
AU  - Siqi Cai
AU  - Jieying Yang
AU  - Jia Jiang
AU  - Yihong Hu
AU  - Yunchang Liu
AU  - Honglei Tu
AU  - Xin Zhang
AU  - Jiangdong Sui
AU  - Ying Wang
PY  - 2026
DA  - 2026/08/06
JO  - Cancer imaging : the official publication of the International Cancer Imaging Society
DO  - 10.1186/s40644-026-01102-z
UR  - https://europepmc.org/article/MED/42972443
AB  - Background  We aimed to evaluate the prognostic value of baseline ¹⁸F-FDG PET/CT metabolic parameters and to construct a risk stratification model for recurrent/metastatic nasopharyngeal carcinoma (rmNPC) patients receiving first-line PD-1 inhibitors plus chemotherapy.Methods  A total of 148 rmNPC patients from two centers were included. Whole-body total lesion glycolysis (wTLG), whole-body metabolic tumor volume (wMTV), and maximal standardized uptake values (SUVmax) were assessed. Predictive performance was evaluated via receiver operating characteristic (ROC) curve, while progression-free survival (PFS) and overall survival (OS) were identified using Kaplan-Meier and Cox regression analyses. A recursive partitioning analysis (RPA) model was subsequently developed and validated for risk stratification.Results  Lower baseline wTLG and wMTV were associated with better response and longer PFS and OS, with wTLG showing the highest predictive power (AUC = 0.776). The RPA model stratified patients into low-risk (low wTLG), medium-risk (high wTLG without liver metastasis), and high-risk (high wTLG with liver metastasis) groups, demonstrating significantly different median PFS (30.7, 15.9, 7.1 months) and OS (43.7, 29.9, 14.7 months; all p < 0.001), and achieving an AUC of 0.839 for predicting 3-year disease progression. Radiotherapy improved survival outcomes in the low-risk group but not in the high-risk group. Analysis of 213 individual lesions revealed heterogeneous responses, with lymph node metastases showing the best response and liver metastases the poorest.Conclusion  Baseline PET/CT metabolic parameters, particularly wTLG, serve as powerful predictors of survival in NPC patients receiving chemoimmunotherapy. The wTLG-based RPA model provides a robust tool for risk stratification and holds promise for guiding individualized clinical decision-making.
SN  - 1740-5025
SN  - 1470-7330
ER  -