Frontiers in aging neuroscience · 2025
Systemic inflammation versus clinical demographics: patient age surpasses the platelet-to-lymphocyte ratio in differentiating secondary trigeminal neuralgia.
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Zhang Zihao, Hao Qingpei, Wang Tao, Peng Shijun, Chang Xin, Wang Yuepeng, Ouyang Jia, Liu Ruen
Аннотация
BACKGROUND: Objective biomarkers to differentiate trigeminal neuralgia (TN) subtypes are lacking. This study aimed to evaluate the utility of the platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) for distinguishing primary TN from secondary TN caused by meningiomas (STN-M) or epidermoid cysts (STN-E).
METHODS: In this retrospective study of 53 patients, analysis of covariance (ANCOVA) was used to compare adjusted biomarker levels while controlling for confounders. The diagnostic performance of these hematological markers and patient age was assessed using receiver operating characteristic (ROC) curve analysis, and their independent predictive values were determined by multivariable logistic regression to differentiate the two secondary TN types.
RESULTS: After adjusting for confounders, the mean PLR was significantly lower in the STN-M group compared to the STN-E group (p = 0.036), while NLR showed no significant difference. Notably, when comparing diagnostic performance for the secondary etiologies, patient age demonstrated a higher area under the curve (AUC = 0.962; 95% CI: 0.897-1.000) than PLR (AUC = 0.793; 95% CI: 0.614-0.972). Multivariable regression identified age as the most influential variable, showing a strong trend toward significance (p = 0.051), while PLR was not an independent predictor (p = 0.197).
CONCLUSION: While this study identified PLR as a potential auxiliary biomarker, its most crucial finding is that the simple demographic feature of patient age is the primary and more powerful discriminator for differentiating STN-M from STN-E. This highlights that while novel biomarkers should be explored, the foundational importance of basic clinical parameters must not be overlooked in the pursuit of diagnostic precision.
METHODS: In this retrospective study of 53 patients, analysis of covariance (ANCOVA) was used to compare adjusted biomarker levels while controlling for confounders. The diagnostic performance of these hematological markers and patient age was assessed using receiver operating characteristic (ROC) curve analysis, and their independent predictive values were determined by multivariable logistic regression to differentiate the two secondary TN types.
RESULTS: After adjusting for confounders, the mean PLR was significantly lower in the STN-M group compared to the STN-E group (p = 0.036), while NLR showed no significant difference. Notably, when comparing diagnostic performance for the secondary etiologies, patient age demonstrated a higher area under the curve (AUC = 0.962; 95% CI: 0.897-1.000) than PLR (AUC = 0.793; 95% CI: 0.614-0.972). Multivariable regression identified age as the most influential variable, showing a strong trend toward significance (p = 0.051), while PLR was not an independent predictor (p = 0.197).
CONCLUSION: While this study identified PLR as a potential auxiliary biomarker, its most crucial finding is that the simple demographic feature of patient age is the primary and more powerful discriminator for differentiating STN-M from STN-E. This highlights that while novel biomarkers should be explored, the foundational importance of basic clinical parameters must not be overlooked in the pursuit of diagnostic precision.