术前炎症指标对乳腺癌患者腋窝淋巴结清扫术后疼痛影响及预测模型构建*

Preoperative Inflammatory Markers and Postoperative Pain in Breast Cancer Following Axillary Lymph Node Dissection: A Predictive Model

摘要:

目的：探讨术前炎症指标对乳腺癌患者腋窝淋巴结清扫术(Axillary Lymph Node Dissection, ALND)术后疼痛影响的影响,并构建预测模型。方法：回顾性分析2022年1月至2024年8月在山西省肿瘤医院接受ALND的乳腺癌患者的临床资料。通过对比不同疼痛程度患者的术前炎症指标水平,并结合Pearson相关性分析,探讨其与术后疼痛的关系。随后采用Lasso回归及多因素Logistic回归分析,以确定其对术后疼痛的独立影响因素。最后,构建Nomogram预测模型,并通过校准曲线和ROC曲线评估其预测效能。结果：共纳入177例乳腺癌患者。中重度疼痛组的中性粒细胞与淋巴细胞比值(neutrophil-to-lymphocyte ratio,NLR)、血小板与淋巴细胞比值(platelet-to-lymphocyte ratio,PLR)水平显著高于轻度疼痛组(P<0.05),而淋巴细胞与单核细胞比值(lymphocyte-to-monocyte ratio,LMR)水平显著低于轻度疼痛组(P<0.01),Pearson相关性分析结果显示PLR与术后疼痛的相关性最强(r=0.50)。Lasso回归及多因素Logistic回归分析结果显示,心情、是否留置引流管、PLR是术后疼痛的独立影响因素(P<0.05)。基于多因素Logistic回归分析结果构建的Nomogram模型,校准曲线显示该模型具有良好的预测准确性和一致性,其ROC曲线的0.882,表明模型具有良好的区分能力,DCA决策曲线显示模型曲线不接近两条参考线,说明具有一定的应用价值。结论：术前炎症指标对乳腺癌患者ALND术后疼痛具有显著影响,并在术后疼痛风险预测中展现出一定的临床应用价值。本研究构建的预测模型可为个体化诊疗提供参考,但其实际应用效果仍需通过进一步的大样本、多中心临床研究加以验证。

Abstract:

Objective: Objective: To investigate the impact of preoperative inflammatory markers on postoperative pain in breast cancer patients undergoing axillary lymph node dissection (ALND) and to develop a predictive model. Methods: A retrospective analysis was conducted on the clinical data of breast cancer patients who underwent ALND at Shanxi Cancer Hospital from January 2022 to August 2024. The levels of preoperative inflammatory markers were compared between patients with different pain severity, and Pearson correlation analysis was used to explore their relationship with postoperative pain. Lasso regression and multivariate logistic regression analysis were performed to identify independent predictors of postoperative pain. A nomogram predictive model was then constructed, and its predictive performance was evaluated using a calibration curve and ROC curve. Results: A total of 177 breast cancer patients were included in the study. The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were significantly higher in the moderate-to-severe pain group compared to the mild pain group (P<0.05), while the lymphocyte-to-monocyte ratio (LMR) was significantly lower in the mild pain group (P<0.01). Pearson correlation analysis indicated that PLR had the strongest correlation with postoperative pain (r=0.50). Lasso regression and multivariate logistic regression analysis identified mood, the presence of a drainage tube, and PLR as independent predictors of postoperative pain (P<0.05). The nomogram model constructed based on multivariate logistic regression analysis demonstrated good predictive accuracy and consistency, as shown by the calibration curve. The ROC curve yielded an AUC of 0.882, indicating good discriminatory ability. Decision curve analysis (DCA) showed that the model had practical clinical utility, as its curve did not approach the two reference lines. Conclusion: Preoperative inflammatory markers have a significant impact on postoperative pain in breast cancer patients undergoing ALND and exhibit potential clinical value in pain risk prediction. The predictive model developed in this study may provide a reference for individualized treatment, but its practical application requires further validation through large-scale, multicenter clinical studies.