目的 探讨预后营养指数(PNI)联合中性粒细胞/ 淋巴细胞比值(NLR)、C 反应蛋白/ 白蛋白比值(CAR)在骨转移瘤 患者中的表达及对患者预后的预测价值。 方法 选取 2020 年 1 月至 2023 年 6 月于中国人民解放军联勤保障部队第九一〇医 院诊治且随访至 2023 年 12 月的 200 例骨转移瘤患者作为研究对象,设立为骨转移瘤组,同期选取 102 例健康体检者设立为 对照组。 对比两组 PNI、NLR、CAR 变化;并观察骨转移瘤组不同病理特征患者中 PNI、NLR、CAR 的变化;采用 Spearman 法分 析 PNI、NLR、CAR 与骨转移瘤患者临床特征的相关性;采用多因素 Cox 回归风险模型分析 PNI、NLR、CAR 对骨转移瘤患者总 生存时间的影响;绘制受试者操作特征曲线(ROC 曲线)模型分析 PNI、NLR、CAR 及三项联合预测骨转移瘤患者预后的预测 效能。 结果 骨转移瘤组的 PNI 低于对照,NLR、CAR 高于对照组(P<0. 05)。 不同骨转移类型、合并其他部位转移、骨性改变、 东部肿瘤协作组(ECOG)评分、骨相关事件(SREs)患者的 PNI、NLR、CAR 比较,差异具有统计学意义(P<0. 05)。 相关性分析 显示,PNI 与骨转移类型、合并其他部位转移、ECOG 评分、SREs 呈负相关(P<0. 05);NRI、CAR 与骨转移类型、合并其他部位 转移、骨性改变、ECOG 评分、SREs 呈正相关(P<0. 05)。 Cox 回归风险模型分析显示,PNI 下降和 NLR、CAR 升高为骨转移瘤 患者总生存时间的独立影响因素(P<0. 05)。 ROC 曲线分析显示,PNI、NLR、CAR 及三项联合预测骨转移瘤患者预后的曲线 下面积(AUC)值分别为 0. 915、0. 766、0. 759 及 0. 951。 结论 PNI 下降和 NLR、CAR 升高与骨转移瘤患者预后显著相关,监测 PNI、NLR、CAR 水平变化有利于为指导临床治疗提供参考。

Objective To investigate the expression of prognostic nutrition index PNI combined with neutrophil / lymphocyte ratio NLR and C-reactive protein / albumin ratio CAR in patients with bone metastases and its effect on prognosis. Method A total of 200 patients with bone metastases diagnosed and treated in our hospital from January 2020 to June 2023 and followed up to December 2023 were selected as the study subjects and set as the bone metastases group while 102 healthy subjects were selected as the control group during the same period. The changes of PNI NLR and CAR in the two groups were compared. The changes of PNI NLR and CAR in different pathological features of bone metastases were observed. Spearman method was used to analyze the correlation between PNI NLR CAR and clinical features of patients with bone metastases. Multivariate Cox regression risk model was used to analyze the effects of PNI NLR and CAR on the overall survival time of patients with bone metastases. ROC curve model was drawn to analyze the predictive efficacy of PNI NLR CAR and the three combinations in predicting the prognosis of patients with bone metastases. Result PNI in bone metastatic tumor group was lower than that in control group NLR and CAR were higher than that in control group P< 0. 05 . There were statistically significant differences among different bone metastasis types combined with other site metastasis bone changes ECOG score PNI NLR and CAR of SREs P<0. 05 . Correlation analysis showed that PNI was negatively correlated with bone metastasis type combined with other site metastasis ECOG score and SREs P<0. 05 . NRI and CAR were positively correlated with bone metastasis type other site metastasis bone changes ECOG score and SREs P<0. 05 . Cox regression risk model analysis showed that decreased PNI and increased NLR and CAR were independent influencing factors for overall survival of patients with bone metastases P<0. 05 . ROC curve analysis showed that the AUC values of PNI NLR CAR and the combination in predicting the prognosis of patients with bone metastases were 0. 915 0. 766 0. 759 0. 951. Conclusion The decrease of PNI and the increase of NLR and CAR are significantly correlated with the prognosis of patients with bone metastases. Monitoring the changes of PNI NLR and CAR levels is conducive to providing references for clinical treatment.