Evidence map›Paper›PMID 40785934›Full record

ArticleQuantitative imaging in medicine and surgery2025

Prediction of PD-L1 expression and prognosis of mass-forming intrahepatic cholangiocarcinoma based on preoperative magnetic resonance imaging.

Jun Zhang, Jinpeng Liu, Xin Zhang, Feng Chen

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Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 authors.

Jun Zhang *Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Jinpeng Liu *Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Xin ZhangGE HealthCare, Shanghai, China.
Feng ChenDepartment of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Funding

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6 · The paper itself

Abstract

Background: In clinical practice, only a subset of patients with tumor respond to immune checkpoint inhibitors. Therefore, the primary challenge lies in identifying the subgroup of candidates who will derive the greatest benefit from this type of therapy. Previous studies have indicated that the positive expression of programmed cell death ligand 1 (PD-L1) in tumors is associated with treatment response. In this study, we aimed to investigate the predictive value of preoperative magnetic resonance imaging (MRI) for PD-L1 expression and the prognosis of patients with mass-forming intrahepatic cholangiocarcinoma (MICC). Methods: A total of 92 patients who were pathologically confirmed to have MICC from January 2017 to December 2018 were enrolled. Logistic regression was used to identify significant factors associated with PD-L1 expression. A predictive model for PD-L1 expression was developed, and its efficacy was evaluated via receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC). The clinical overall survival (OS) model was established based on clinical-radiologic factors via multivariate Cox regression analysis to categorize patients with MICC into high- and low-risk groups. Results: PD-L1 expression was significantly associated with enhancement patterns in the arterial phase of enhanced MR images [odds ratio (OR): 0.12; 95% confidence interval (CI): 0.04-0.37]. A predictive model for PD-L1 expression was established, with an AUC of 0.722 (95% CI: 0.632-0.811). Hepatic lobe atrophy [hazard ratio (HR): 2.036; 95% CI: 1.136-3.650], enhancement patterns (HR: 0.509; 95% CI: 0.295-0.877), lymph node metastasis (LNM) (HR: 1.715; 95% CI: 1.005-2.926), and carcinoembryonic antigen (CEA) (HR: 1.664; 95% CI: 1.007-2.750) were identified as prognostic factors for patients with MICC. The clinical OS model [concordance index (C-index): 0.875; 95% CI: 0.812-0.905] incorporating these independent predictors effectively stratified patients with MICC into high- and low-risk groups, with the 1-, 3-, and 5-year survival rates for the two groups being 56.5%, 17.4%, and 15.2%, respectively, and 89.1%, 58.7%, and 52.2%, respectively (P<0.001). Furthermore, the calibration curve of the clinical OS model demonstrated exceptional concordance between the predictions and actual observations. Conclusions: Preoperative MRI may be a noninvasive means to predicting PD-L1 expression and prognosis in patients with MICC.

Indexed as

Cholangiocarcinomadiagnosismagnetic resonance imaging (MRI)programmed cell death ligand 1 (PD-L1)

Identifiers

PMID40785934
PMCPMC12332643

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