Year: 2025
Type: article
Study design: Observational Study
Abstract: Objective To explore whether uric acid (UR), neutrophil/lymphocyte ratio (NLR) and uric acid/albumin ratio (UAR) can predict bone metastasis in colorectal cancer (CRC). Methods A single-center retrospective study was conducted studying patients diagnosed with colorectal cancer attending The First Affiliated Hospital of Xian JiaoTong University between January 2016 and December 2021. Patients were categorized into groups with and without bone metastasis. Receiver operating characteristic (ROC) curve analysis assessed the diagnostic accuracy of CRC bone metastases, with subsequent combined ROC curve analysis. Differences among the AUCs were calculated and compared by Delong test. Logistic regression analysis was utilized to assess the impact of these parameters on CRC bone metastasis. Results A total of 156 patients (32%) exhibited bone metastases from CRC. In these patients, levels of uric acid (UA), uric acid ratio (UAR), neutrophil-to-lymphocyte ratio (NLR), carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA199), and carbohydrate antigen 724 (CA724) were significantly elevated. The diagnostic performance of UA, UAR and NLR is surpassed that of traditional colorectal cancer markers. The area under the curve (AUC) for the combination UA, UAR and NLR with colorectal cancer tumor markers was significantly more effective in predicting bone metastasis (P < 0.001) compared to the AUC without this combination. Multiple logistic regression analysis identified UA, NLR and CEA as independent risk factors for bone metastasis in colorectal cancer. Conclusions UA, UAR and NLR serve as valuable makers for predicting bone metastases in patients with colorectal cancer. The integration of UA, UAR, NLR, CEA, CA199 and CA724 may enhance the prediction of bone metastases in colorectal cancer.
Source: Frontiers in Oncology
Authors: Min Chen, Xuan Wang, Shuheng Bai, Ning Lan, Junyang Wang, YanKe Chen, Ying Gao, WenJuan Wang, Xiao Shang, Min Jiao, Xiangxiang Zhang, Wenyang Li, Fang Wu, Wanyi Liu, Fengyuan Hu, Ling Chen, Juan Ren
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
Award: G1077031112
OpenAlex ID: W4415388140
