中国组织工程研究 ›› 2025, Vol. 29 ›› Issue (13): 2661-2668.doi: 10.12307/2024.148

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基于中医证候与精液质量相关参数构建精子DNA碎片预测模型与验证

周  超1,庾广聿1,阳绍华1,高磊磊2,金  珍2,蒋月园1,李  欢3   

  1. 1广西壮族自治区南溪山医院生殖中心,广西壮族自治区桂林市   541000;2浙江省人民医院生殖中心,浙江省杭州市   310000;3中国人民解放军联勤保障部队第九二四医院检验科,广西壮族自治区桂林市   541000
  • 收稿日期:2023-03-31 接受日期:2023-05-26 出版日期:2025-05-08 发布日期:2024-09-11
  • 通讯作者: 李欢,副主任技师,中国人民解放军联勤保障部队第九二四医院检验科,广西壮族自治区桂林市 541000
  • 作者简介:周超,男,1992年生,广西壮族自治区灵川县人,汉族,2014年右江民族医学院毕业,主管技师,主要从事辅助生殖胚胎实验室及男科实验室工作,现主要研究方向为辅助生殖临床相关预测模型。 共同第一作者:庾广聿,女,1982年生,广西壮族自治区桂林市人,汉族,2012年广西医科大学毕业,硕士,副主任医师,主要从事生殖内分泌方面的研究。 共同第一作者:阳绍华,男,1980年生,广西壮族自治区桂林市人,汉族,2003年广西中医学院毕业,硕士,副主任医师,主要从事中医男科方面的研究。
  • 基金资助:
    国家自然科学基金(82001539),项目负责人:高磊磊;广西科技计划项目(2022AC04004),项目参与人:蒋月园;广西壮族自治区卫生健康委员会自筹课题(Z20211100),项目负责人:周超

Prediction model and verification of sperm DNA fragments based on traditional Chinese medicine syndrome and semen quality-related parameters

Zhou Chao1, Yu Guangyu1, Yang Shaohua1, Gao Leilei2, Jin Zhen2, Jiang Yueyuan1, Li Huan3   

  1. 1Reproductive Center, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin 541000, Guangxi Zhuang Autonomous Region, China; 2Reproductive Center of Zhejiang Provincial People’s Hospital, Hangzhou 310000, Zhejiang Province, China; 3Laboratory Department of 924 Hospital of the Joint Logistics Support Force of the People’s Liberation Army of China, Guilin 541000, Guangxi Zhuang Autonomous Region, China
  • Received:2023-03-31 Accepted:2023-05-26 Online:2025-05-08 Published:2024-09-11
  • Contact: Li Huan, Associate chief technician, Laboratory Department of 924 Hospital of the Joint Logistics Support Force of the People’s Liberation Army of China, Guilin 541000, Guangxi Zhuang Autonomous Region, China
  • About author:Zhou Chao, Technician-in-charge, Reproductive Center, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin 541000, Guangxi Zhuang Autonomous Region, China; Yu Guangyu, Master, Associate chief physician, Reproductive Center, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin 541000, Guangxi Zhuang Autonomous Region, China; Yang Shaohua, Master, Associate chief physician, Reproductive Center, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin 541000, Guangxi Zhuang Autonomous Region, China
  • Supported by:
    National Natural Science Foundation of China, No. 82001539 (to GLL); Guangxi Science and Technology Plan Project, No. 2022AC04004 (to JYY); Self Funded Project by Health Commission of Guangxi Zhuang Autonomous Region, No. Z20211100 (to ZC)

摘要:

文题释义:

精子DNA碎片指数:通过反映男方精子核遗传物质的完整性与损伤程度,从基因层面为全面评估精液质量再增一个独立的生物学临床指标。研究证实,精子DNA碎片指数与男性不育、植入失败、妊娠丢失存在显著的相关性。
中医证候:通过反映疾病发生和演变过程中某阶段的本质特征,能多维度获取关于该疾病的病因、病机、病位、病势等丰富信息。但因中医证候缺乏定量指标与科学的统计学方法,因而其具有多变性、复杂性、模糊性、隐匿性。

摘要
背景:中医证候与精液质量相关参数相结合,共同预测精子DNA碎片指数(DNA fragmentation index,DFI)异常增高的发生并绘制列线图,能显著提高临床的实操性与应用效能,为临床全面评估精液质量,采取积极干预措施以改善临床结局及制定个体化医疗方案提供依据。
目的:探讨基于中医证候与精液质量相关参数构建精子DNA碎片的预测模型与验证。
方法:回顾性分析2019年7月至2021年7月在广西壮族自治区南溪山医院中医男科接受中医证候诊断及精子DNA碎片率检查的不育患者共420例,据《人类精液检查与处理实验室手册》(第6版),将其中137例精子DFI > 30%患者纳入精子DFI异常增高组,将283例精子DFI≤30%作为对照组;首先采用单因素分析筛选精子DFI异常增高的影响因素,然后采用套索算法(LASSO)校正因子共线性问题并筛选出最佳匹配因子后,将其纳入多因素向前逐步Logistic回归找出其独立影响因素并绘制列线图,最后采用受试者工作曲线、校准曲线、临床决策曲线、临床影响曲线对该预测模型进行区分度与准确度及临床应用效能验证。
结果与结论:①单因素分析结果显示,年龄、体质量指数、前向运动率、精子总活率、精子浓度、精子形态学、肾阳虚衰证、湿热下注证、肾精不足证为引发精子DFI异常增高的影响因子(P < 0.05);②通过LASSO回归进一步筛选出的最佳匹配因素为年龄、体质量指数、精子总活率、精子浓度、精子形态学、肾阳虚衰证、湿热下注证、肾精不足证(P < 0.05);③多因素向前逐步Logistic回归结果显示年龄、体质量指数、精子浓度、精子总活率、湿热下注证、肾阳虚衰证共6项为引发精子DFI异常增高的独立影响因素;④受试者工作曲线显示,模型组曲线下面积为0.760(0.713,0.806),验证组曲线下面积为0.745(0.714,0.776),说明该预测模型具有较好的区分度;⑤校准曲线平均绝对误差0.040,Hosmer-Lemeshow检验P > 0.05,表明该模型预测发生精子DFI异常增高的概率与实际发生精子DFI异常增高的概率无显著统计学差异,证实该模型具有较好的准确度;⑥临床决策曲线与临床影响曲线显示,模型组与验证组分别在阈概率值为0.08-0.84与0.09-0.78时具有临床最大净获益,且在该阈概率范围内具有较好的临床应用效能;⑦结果表明,年龄、体质量指数、精子浓度、精子总活率、湿热下注证、肾阳虚衰证为引发精子DFI异常增高的独立影响因素,通过其构建的临床预测模型列线图具有较好的临床预测价值与临床应用效能,可为临床全面评估精液质量、预后与干预及个体化医疗服务提供依据。

https://orcid.org/0000-0001-9843-6731 (周超) 

中国组织工程研究杂志出版内容重点:干细胞;骨髓干细胞;造血干细胞;脂肪干细胞;肿瘤干细胞;胚胎干细胞;脐带脐血干细胞;干细胞诱导;干细胞分化;组织工程

关键词: 精子DNA碎片, 精子DNA完整性, 中医证候, 精子DNA碎片指数, 预测模型

Abstract: BACKGROUND: The combination of traditional Chinese medicine syndrome and semen quality-related parameters can jointly predict the occurrence of abnormal increase in sperm DNA fragmentation index (DFI) and draw a column chart, which can significantly improve clinical practicality and application efficiency, provide a basis for comprehensive evaluation of semen quality in clinical practice, take active intervention measures to improve clinical outcomes, and formulate personalized medical plans.
OBJECTIVE: To explore the prediction model and verification of sperm DNA fragments based on traditional Chinese medicine syndrome and semen quality-related parameters.  
METHODS: Retrospective analysis was made on 420 infertile patients who received traditional Chinese medicine syndrome diagnosis and sperm DNA fragment rate examination in the Department of Traditional Chinese Medicine Andrology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region from July 2019 to July 2021. According to the Manual of Human Semen Examination and Treatment Laboratories (6th Edition), 137 patients with sperm DFI>30% were included in the group of abnormally high sperm DFI, and 283 patients with sperm DFI ≤ 30% were taken as the control group. First, univariate analysis was used to screen the influencing factors of the abnormal increase of sperm DFI. Then, the best matching factor was selected by using the collinearity problem of LASSO correction factors. Then, it was included in the multifactor forward stepwise logistic regression to find out its independent influencing factors and draw a nomogram. Finally, the receiver operating characteristic curve, calibration curve, decision curve analysis and clinical impact curve were used to verify the differentiation and accuracy of the prediction model and its clinical application effectiveness. 
RESULTS AND CONCLUSION: (1) The results of the univariate analysis showed that age, body mass index, forward motion rate, total sperm motility, sperm concentration, sperm morphology, kidney yang deficiency syndrome, damp heat downpour syndrome, and kidney sperm deficiency syndrome were the influencing factors for the abnormal increase of sperm DFI (P < 0.05). (2) The best matching factors further screened by LASSO regression were age, body mass index, total sperm motility, sperm concentration, sperm morphology, kidney yang deficiency syndrome, damp heat downpour syndrome, and kidney essence deficiency syndrome (P < 0.05). (3) Multifactor forward stepwise Logistic regression showed that age, body mass index, sperm concentration, total sperm motility, damp heat downpour syndrome, and kidney yang deficiency syndrome were six independent factors that caused the abnormal increase in sperm DFI. (4) Receiver operating characteristic curve showed that the area under the curve of the model group was 0.760(0.713,0.806), and the area under the curve of the validation group was 0.745(0.714,0.776). It showed that the prediction model had good discrimination. (5) The average absolute error of the calibration curve was 0.040, and the Hosmer Lemeshow test (P > 0.05), suggesting that there was no significant statistical difference between the probability of the abnormal increase in DFI of spermatozoa predicted by the model and the probability of the abnormal increase in DFI of spermatozoa actually occurred, which confirmed that the model had good accuracy. (6) Decision curve analysis and clinical impact curve showed that the model group and validation group had the maximum clinical net benefit when the threshold probability values were (0.08-0.84) and (0.09-0.78) respectively, and had good clinical application efficiency within the threshold probability range. (7) These findings conclude that age, body mass index, sperm concentration, total sperm viability, damp heat downpour syndrome and kidney yang deficiency syndrome are independent factors that cause the abnormal increase in sperm DFI. The nomogram of the clinical prediction model constructed by them has good clinical prediction value and clinical application efficiency, and can provide the basis for comprehensive clinical evaluation of semen quality and individualized medical service.

Key words: sperm DNA fragment, sperm DNA integrity, traditional Chinese medicine syndromes, sperm DNA fragmentation index, prediction model

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