中国组织工程研究

中国组织工程研究 ›› 2025, Vol. 29 ›› Issue (24): 5071-5078.doi: 10.12307/2025.743

• 骨组织构建 bone tissue construction • 上一篇    下一篇

绝经后骨质疏松症与控制性营养状况评分及系统性免疫炎症指数的关系

陈小晴1，宫云昭1，2，陈  巍1，2   

  1. 1辽宁中医药大学，辽宁省沈阳市  110847；2辽宁中医药大学附属第二医院，辽宁省沈阳市  110034
  • 收稿日期:2024-07-27 接受日期:2024-09-21 出版日期:2025-08-28 发布日期:2025-01-22
  • 通讯作者: 陈巍，博士，主任医师，硕士生导师，辽宁中医药大学，辽宁省沈阳市 110847；辽宁中医药大学附属第二医院，辽宁省沈阳市 110034
  • 作者简介:陈小晴，女，1996年生，广东省清远市人，汉族，辽宁中医药大学在读硕士，主要从事糖尿病和骨质疏松症的研究。 并列第一作者：宫云昭，男，1981年生，辽宁省朝阳市人，汉族，硕士，主任医师，主要从事骨与关节损伤的研究。
  • 基金资助:
    辽宁省教育厅高等学校基本科研项目(LJKMZ20221327)，项目负责人：宫云昭

Association of the controlling nutritional status score and systemic immune-inflammation index with postmenopausal osteoporosis

Chen Xiaoqing1, Gong Yunzhao1, 2, Chen Wei1, 2   

  1. 1Liaoning University of Traditional Chinese Medicine, Shenyang 110847, Liaoning Province, China; 2The Second Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang 110034, Liaoning Province, China
  • Received:2024-07-27 Accepted:2024-09-21 Online:2025-08-28 Published:2025-01-22
  • Contact: Chen Wei, MD, Chief physician, Master’s supervisor, Liaoning University of Traditional Chinese Medicine, Shenyang 110847, Liaoning Province, China; The Second Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang 110034, Liaoning Province, China
  • About author:Chen Xiaoqing, Master candidate, Liaoning University of Traditional Chinese Medicine, Shenyang 110847, Liaoning Province, China Gong Yunzhao, MS, Chief physician, Liaoning University of Traditional Chinese Medicine, Shenyang 110847, Liaoning Province, China; The Second Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang 110034, Liaoning Province, China Chen Xiaoqing and Gong Yunzhao contributed equally to this work.
  • Supported by:
    Basic Research Project for Higher Education Institutions of the Liaoning Provincial Department of Education, No. LJKMZ20221327 (to GYZ)

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摘要：


文题释义：
倾向性评分匹配：是一种统计方法，被广泛应用于观察性临床研究中，旨在减少或消除研究对象之间的基线差异，以模拟随机对照试验的条件。倾向性评分匹配通过匹配倾向性评分相近的个体，减少组间选择偏倚的影响，从而提高研究结果的可靠性。
控制性营养状况评分：该评分通过血清白蛋白水平、总胆固醇水平和淋巴细胞计数来量化个体营养不良的风险，是一种反映个体营养状态的客观工具。在临床研究中，控制性营养状况评分被用于定量评估患者营养状况对疾病进程及治疗反应的影响，特别是在慢性疾病和恶性肿瘤的管理中。

背景：控制性营养状况评分和系统性免疫炎症指数作为评估个体营养和炎症状态的工具，已被证实与多种慢性疾病的风险和预后相关，然而它们在预测绝经后骨质疏松症方面的应用价值尚未得到充分研究。
目的：探讨控制性营养状况评分和系统性免疫炎症指数在预测绝经后骨质疏松症的应用价值。
方法：回顾性分析2022年1月至2024年4月于辽宁中医药大学附属第二医院及康平分院接受治疗的420例绝经后女性患者的临床资料，其中骨质疏松组205例、骨量正常组215例。选取年龄、绝经年限、体质量指数、骨折史、吸烟史和饮酒史作为协变量，通过倾向性评分匹配将两组患者以1∶1的比例匹配，以平衡两组间的协变量。匹配后两组患者各142例，检测两组患者血清中Ⅰ型前胶原氨基端前肽、β-胶原降解产物、甲状旁腺激素和25-羟基维生素D水平，通过血清白蛋白、总胆固醇水平及中性粒细胞计数、淋巴细胞计数、血小板计数评估控制性营养状况评分与系统性免疫炎症指数，应用受试者工作特征曲线分析控制性营养状况评分和系统性免疫炎症指数的最佳截断值和预测效能。利用皮尔逊或斯皮尔曼相关性分析控制性营养状况评分、系统性免疫炎症指数及骨密度之间的关系，使用Logistic回归模型分析女性绝经后骨质疏松症的影响因素。
结果与结论：①匹配后，骨质疏松组患者血清Ⅰ型前胶原氨基端前肽、β-胶原降解产物、甲状旁腺激素水平均高于骨量正常组(P < 0.001)，25-羟基维生素D水平低于骨量正常组(P < 0.001)，营养不良率和免疫炎症指数均高于骨量正常组(P < 0.001)；②相关性分析显示，控制性营养状况评分与系统性免疫炎症指数呈正相关(r=0.462，P < 0.001)，控制性营养状况评分、系统性免疫炎症指数与股骨颈骨密度、腰椎L1-L4骨密度呈负相关(r=-0.322，P < 0.001；r=-0.362，P < 0.001；r=-0.322，P < 0.001；r=-0.340，P < 0.001)；③倾向性评分匹配前后的多因素Logistic回归分析结果显示，控制性营养状况评分和系统性免疫炎症指数均为绝经后骨质疏松症的危险因素；④匹配后的受试者工作特征曲线显示，控制性营养状况评分和系统性免疫炎症指数的曲线下面积分别为0.758和0.754，两者最佳截断值分别为2.5和694.62，提示两者在预测绝经后女性骨质疏松方面的预测性能良好。结果表明：控制性营养状况评分和系统性免疫炎症指数为有效预测绝经后骨质疏松症的工具，可用于临床预防及早期识别高风险的绝经后女性，同时也提示机体营养状况及炎症指标可能是绝经后骨质疏松症的发病机制之一。
https://orcid.org/0009-0005-3784-9600(陈小晴)

中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程

关键词: 绝经后骨质疏松症, 倾向性评分匹配, 控制性营养状况评分, 系统性免疫炎症指数, 绝经后女性, 工程化组织构建

Abstract: BACKGROUND: The controlling nutritional status score and systemic immune-inflammation index, as tools to assess individual nutritional and inflammatory states, have been proven to be related to the risk and prognosis of various chronic diseases. However, their value in predicting postmenopausal osteoporosis has not yet been fully explored.
OBJECTIVE: To explore the applicative value of the controlling nutritional status score and systemic immune-inflammation index in predicting postmenopausal osteoporosis. 
METHODS: A retrospective analysis was conducted on the clinical data of 420 postmenopausal patients treated from January 2022 to April 2024 at the Second Affiliated Hospital of Liaoning University of Traditional Chinese Medicine and its Kangping branch. There were 205 cases in osteoporosis group and 215 in normal bone mass group. Age, years of menopause, body mass index, history of fracture, smoking history and alcohol consumption were selected as covariates. Patients were matched at a 1:1 ratio using the nearest neighbor method of propensity score matching to balance covariates between the two groups. Therefore, there were 142 patients in each of the two groups after matching. Serum levels of type I precollagen amino-terminal prepeptide, β-collagen degradation products, parathyroid hormone, and 25-hydroxyvitamin D were measured in both groups. The controlling nutritional status score and systemic immune-inflammation index were assessed by serum albumin, total cholesterol levels, neutrophil counts, lymphocyte counts, and platelet counts. The receiver operating characteristic curve was employed to analyze the optimal cutoff values and predictive effectiveness of the controlling nutritional status score and systemic immune-inflammation index. Pearson or Spearman correlations were used to analyze the relationships among the controlling nutritional status score, systemic immune-inflammation index, and bone mineral density. A multivariable logistic regression model was utilized to identify factors influencing postmenopausal osteoporosis.
RESULTS AND CONCLUSION: (1) After matching, compared with the normal bone mass group, the osteoporosis group had higher serum pre-collagen type I amino-terminal prepeptide, β-collagen degradation products, and parathyroid hormone levels (P < 0.001), lower 25-hydroxyvitamin D levels (P < 0.001), and higher malnutrition rates and immunoinflammatory indices (P < 0.001). (2) Correlation analysis showed a positive correlation between the controlling nutritional status score and systemic immune-inflammation index (r=0.462, P < 0.001), and both were negatively correlated with femoral neck bone density and lumbar spine L1-L4 bone mineral density (r=-0.322, P < 0.001; r=-0.362, P < 0.001; r=-0.322, P < 0.001; r=-0.340, P < 0.001). (3) Multivariable logistic regression analyses, before and after propensity score matching, indicated that both the controlling nutritional status score and systemic immune-inflammation index were risk factors for osteoporosis in postmenopausal patients. (4) The receiver operating characteristic curves post-matching showed that the areas under the curve for the controlling nutritional status score and systemic immune-inflammation index were 0.758 and 0.754, respectively, and the two best cutoff values were 2.50 and 694.62, respectively, suggesting that both tools perform well in predicting postmenopausal osteoporosis. To conclude, the controlling nutritional status score and systemic immune-inflammation index are effective tools for predicting postmenopausal osteoporosis, suitable for clinical use in prevention and early identification of high-risk individuals. These findings also suggest that nutritional status and inflammatory markers may be part of the pathogenesis of postmenopausal osteoporosis.

中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程

Key words: postmenopausal osteoporosis, propensity score matching, controlling nutritional status score, systemic inflammation index, postmenopausal women, engineered tissue construction

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