The Predictive Value of Serum miR-141-3p, Fibrinogen, and Prostate-Specific Antigen Levels for Bone Metastasis in Prostate Cancer.

Abstract

Aims/Background Prostate cancer is a prevalent malignancy among men that frequently progresses to bone metastasis, significantly affecting prognosis and quality of life. Serum biomarkers such as miR-141-3p, fibrinogen (FIB), and prostate-specific antigen (PSA) are emerging as promising tools for early detection and personalised interventions for bone metastasis. This study investigated their predictive value for bone metastasis in prostate cancer. Methods Conducted from March 2018 to March 2023, this study included 100 prostate cancer patients monitored over time. All participants underwent radionuclide bone imaging combined with positron emission tomography-computed tomography (PET-CT). Patients who developed bone metastasis (32 cases) were classified as the metastasis group, while those without (68 cases) were categorised as the non-metastasis group. Additionally, a control group of 50 healthy volunteers was established for comparison. A retrospective analysis assessed serum miR-141-3p, FIB, and PSA levels across the three groups. Clinical data were analysed to identify factors influencing bone metastasis using univariate and multivariate analyses, after which a prediction model was created to evaluate its prognostic value. Results Serum levels of miR-141-3p, FIB, and PSA were significantly different among the three groups, with the highest levels in the metastasis group, followed by the non-metastasis group, and the lowest in the control group (p < 0.05). Both univariate and multivariate analyses confirmed that these serum biomarkers significantly influenced the occurrence of bone metastasis. The combined predictive model demonstrated high clinical value for assessing the risk of bone metastasis in prostate cancer, with an area under the curve (AUC) of 0.923 (95% confidence interval [CI]: 0.868-0.979, p < 0.05). Conclusion Serum levels of miR-141-3p, FIB, and PSA are elevated in prostate cancer patients, particularly those with bone metastasis. The predictive model utilising these biomarkers effectively forecasts the likelihood of bone metastasis.