广西医学

目的基于美国国家健康与营养检查调查（NHANES）数据，探讨中性粒细胞百分比/白蛋白值（NPAR）与糖尿病和癌症共病患者全因死亡风险的关系。方法基于NHANES数据库1999—2018年收录的1 258例糖尿病和癌症共病患者的NHANES数据，采用受试者工作特征（ROC）曲线确定NPAR预测糖尿病癌症共病患者全因死亡的最佳截断值，以最佳截断值将患者分为高NPAR组664例和低NPAR组594例。通过Kaplan⁃Meier法绘制两组患者的生存曲线，采用log⁃rank检验比较两组生存曲线。采用多因素COX回归模型分析NPAR与全因死亡风险的关系，并进行亚组分析。采用限制性立方样条（RCS）和阈值效应分析NPAR与全因死亡风险的剂量⁃反应关系。结果 1 258例糖尿病和癌症共病患者的中位随访时间为89个月，有512例患者死亡，死亡率为40.7%。ROC曲线分析显示NPAR预测糖尿病和癌症共病患者全因死亡的最佳截断值为14.639。生存曲线分析显示，低NPAR组的全因死亡风险低于高NPAR组（P<0.05）。多因素COX回归模型结果显示，调整混杂因素后，高NPAR组患者全因死亡风险是低NPAR组的1.60倍（P<0.05）。RCS分析及阈值效应分析显示，NPAR与全因死亡风险呈“U”型非线性关系（P非线性<0.05），当NPAR≤12.819时，糖尿病和癌症共病患者的全因死亡风险随着NPAR的升高而降低，当NPAR>12.819时，糖尿病和癌症共病患者的全因死亡风险随着NPAR的升高而升高（P<0.05）。亚组分析显示，NPAR与糖尿病和癌症共病患者全因死亡风险的相关性在各亚组之间不存在交互作用（P交互作用>0.05）。结论糖尿病和癌症共病患者的NPAR与全因死亡风险呈“U”型非线性关系，NPAR可作为糖尿病和癌症共病患者全因死亡风险的独立预测指标。

Objective To investigate the relation of neutrophil percentage to albumin ratio (NPAR) with all⁃cause mortality risk in patients with diabetes and cancer comorbidities based on National Health and Nutrition Examination Survey (NHANES). Methods Based on the NHANES data of 1258 patients with diabetes and cancer comorbidities included from 1999 to 2018 in the NHANES database, the receiver operating characteristic (ROC) curve was adopted to determine the optimal cut⁃off value of NPAR in predicting all⁃cause mortality in patients with diabetes and cancer comorbidities. Patients were assigned to high NPAR group (664 cases) or low NPAR group (594 cases) based on the optimal cut⁃off value. The survival curves of the two groups were drawn by the Kaplan⁃Meier method, and the survival curves of the two groups were compared by the log⁃rank test. The multivariate COX regression model was adopted to analyze the relation between NPAR and all⁃cause mortality risk, and the subgroup analysis was conducted. The dose⁃response relation of NPAR with all⁃cause mortality risk was analyzed by employing restricted cubic spline (RCS) and threshold effects. Results The median follow⁃up time of 1258 patients with diabetes and cancer comorbidities was 89 months, and 512 patients died, with a mortality rate of 40.7%. The ROC curve analysis revealed that the optimal cut⁃off value of NPAR in predicting all⁃cause mortality in patients with diabetes and cancer comorbidities was 14.639. The survival curve analysis suggested that all⁃cause mortality risk in the low NPAR group was lower than that in the high NPAR group (P<0.05). The results of multivariate COX regression model expressed that all⁃cause mortality risk in the high NPAR group was 1.60 times higher than that in the low NPAR group after adjusting for confounding factors (P<0.05). The RCS analysis and threshold effect analysis interpreted that a U⁃shaped nonlinear relation between NPAR and all⁃cause mortality risk (Pnonlinear<0.05). When NPAR≤12.819, all⁃cause mortality risk of patients with diabetes and cancer comorbidities decreased with the increase of NPAR, whereas when NPAR>12.819, all⁃cause mortality risk of patients with diabetes and cancer comorbidities increased with the increase of NPAR (P<0.05). Subgroup analysis exhibited that there was no interaction effect of the correlation of NPAR with all⁃cause mortality risk in patients with diabetes and cancer comorbidities between various subgroups (Pinteraction effect>0.05). Conclusion There is a U⁃shaped non⁃linear relation between NPAR and all⁃cause mortality risk in patients with diabetes and cancer comorbidities. NPAR can be used as an independent predictor of all⁃cause mortality risk in patients with diabetes and cancer comorbidities.

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