Fgfr4 combined with inflammatory cytokines improves recurrence risk prediction in differentiated thyroid carcinoma: A retrospective cohort study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: This study aimed to evaluate the synergistic role of fibroblast growth factor receptor 4 (FGFR4) and inflammatory cytokines (ICs) (interleukin-6 [IL-6], tumor necrosis factor-a [TNF-a], and C-reactive protein [CRP]) in predicting recurrence of differentiated thyroid carcinoma (DTC) after radical surgery, and to develop a combined predictive model for improved postoperative risk stratification. Methods: We enrolled 102 DTC patients treated between February 2022 and January 2024, along with 98 healthy controls. Serum levels of FGFR4, IL-6, TNF-a, and CRP were measured preoperatively and postoperatively using ELISA. Independent risk factors were identified through logistic regression, diagnostic performance was assessed using ROC analysis, and correlations of FGFR4 and ICs with postoperative recurrence were evaluated. Results: Preoperative levels of FGFR4, IL-6, TNF-a, and CRP were significantly elevated in DTC patients compared to healthy controls (P<0.05). A diagnostic model integrating these four markers demonstrated superior performance (AUC=0.931; sensitivity 94.12%, specificity 79.59%) over individual biomarkers (P<0.05). Among DTC patients, those with recurrence (n = 26) exhibited significantly higher FGFR4 and inflammatory cytokine levels than the non-recurrent group (P<0.05). The combined model predicted 1-year recurrence with an AUC of 0.864 (sensitivity 73.08%, specificity 93.42%). Conclusions: The synergistic interaction between FGFR4 and ICs plays a critical role in DTC. Their combined detection enhances postoperative recurrence risk prediction, offering a valuable tool for clinical risk stratification.
Source: Journal of Medical Biochemistry
DOI: 10.5937/jomb0-59084
Authors: Yongjie Hu, Peifei Huang, Yingying Sha
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4411499249