老年健康志愿者及老年冠心病人群应用阿司匹林的群体药代动力学及药效学研究
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摘要
背景和目的:
     阿司匹林是心脑血管病的一级及二级预防中应用最广泛的一种抗血小板药物。在老年人群中,多器官功能减退及合并药物的增多,使阿司匹林的个体差异增加,阿司匹林出血副作用及阿司匹林抵抗的发生率较高,如何建立一种评估体系及预警机制显得非常重要。群体药代/药效动力学(population pharmacokinetics/population pharmacodynamics, PPK/PPD)可通过收集患者稀疏数据建立数学模型,定量考察各种固定效应因素(身高、年龄、体重、合并疾病、合并用药等)对药物药动学/药效学参数的影响,进而指导个体化用药。本研究考察了老年健康志愿者及老年冠心病患者服用肠溶阿司匹林的群体药代动力学特征,着重分析了年龄、体重指数、性别、合并疾病、合并用药等固定效应对阿司匹林药代动力学的影响。同时考察了老年健康志愿者服用肠溶阿司匹林的群体药效学特征及其受固定效应的影响,对老年群体药效学指标AA、ADP、PAC-1和CD62P的进行相关性分析,并且对阿司匹林抵抗的概念提出了新的认识及研究方向,从而更好地指导个体化用药。
     方法:
     河北社区抽取老年健康志愿者23人,年龄≥60岁,分别给予拜阿司匹林肠溶片100mg,口服1/日,服用时间7天以上。于第8天服药前、服药后1h、2h、3h、4h、5h、6h、8h、9h、10h、12h各采血一次。解放军总医院心研所一、二病区收集老年冠心病患者210例,年龄≥60岁,均服用拜阿司匹林肠溶片100mg大于等于7天,于服药的0-24小时随机取点,每个患者1-4点,液相色谱串联质谱法检测主要活性代谢产物水杨酸的浓度。光比浊法测定AA、ADP,流式法测定PAC-1和CD62P。将患者基础特征、合并疾病、合并用药等作为协变量应用NONMEN法建立群体药代动力学模型,VPC法进行内部验证,并将药效指标与血浆水杨酸盐浓度进行群体药效动力学的模型拟合。应用偏相关、Logistic分析等方法对所有入选病例进行药效学相关性分析。
     结果:
     口服100mg阿司匹林肠溶片在健康老年志愿者及老年冠心病患者中呈一房室模型,个体间变异符合乘法模型。最终模型参数分别为:清除率6.69L/h(5.15-8.23),吸收速率常数1.05/h(0.83-28.6),分布容积41.2L(26.0-56.4)。年龄、体重指数、性别、合并疾病均未纳入模型,合并用药中,ACEI对水杨酸的清除率有显著的影响,水杨酸在健康老年志愿者的表观分布容积较小,为冠心病老年群体的0.646倍。VPC验证结果与模型计算相符。
     老年健康志愿者的群体药效动力学分析中,AA诱导的血小板聚集率、ADP诱导的血小板聚集率、PAC-1活化程度与水杨酸血药浓度值呈线性相关,相关系数分别为-1.46,-0.379,-0.059,CD62P活化程度与水杨酸血药浓度呈指数相关,相关系数为-e0.398;偏相关法分析老年健康志愿者服用阿司匹林的药效学指标,ADP诱导的血小板聚集率与PAC-1活化度与水杨酸血药浓度呈负相关;将药效学指标进行二分类分析,健康老年志愿者中AA诱导的血小板聚集率、ADP诱导的血小板聚集率、CD62p活化度与各因素无明显相关,水杨酸浓度为PAC-1活化度的保护性因素;社区及病房老年群体的药效学指标进行偏相关分析,四个药效学指标都与对应药物浓度无明显相关性;社区及病房老年群体的药效学指标进行二分类分析,AA≥20%的危险因素是合并糖尿病和脑梗死病史。在ADP≥70%中,氯吡格雷是保护性因素。PAC-1≥40%的保护性因素是氯吡格雷,合并应用他汀是危险因素;CD62P≥20%的危险因素是年龄和合并服用中药,氯吡格雷是保护性因素。在社区老年志愿者群体中,经不同时间多次测量药效指标,阿司匹林抵抗发生率为4.35%,半抵抗的发生率分别为4.35%(AA≥20%),73.91%(ADP≥70%)
     结论:1.阿司匹林肠溶片在健康老年志愿者的表观分布容积为冠心病老年人群体的
     0.646倍2.合并应用ACEI对清除率有显著影响,即当合用药物ACEI时,阿司匹林肠
     溶片的清除率为不使用ACEI时的0.668倍;3.老年健康志愿者的群体药效动力学分析中,AA、ADP诱导的血小板聚集、
     PAC-1的活化与水杨酸血药浓度呈弱线性相关,CD62P的活化与水杨酸血
     药浓度呈指数相关;4.在老年人群中,阿司匹林半抵抗(AA≥20%)的危险因素是合并糖尿病和脑
     梗死病史。阿司匹林半抵抗(ADP≥70%)的保护性因素是氯吡格雷。PAC-1
     ≥40%的保护性因素是氯吡格雷,合并应用他汀是危险因素;CD62P≥20%的
     危险因素是年龄及合并服用中药,氯吡格雷是保护性因素;5.生化阿司匹林抵抗的定义需要更进一步的完善,仅仅依靠单次的血小板聚集
     率的测定就判断是否为阿司匹林抵抗并改变抗栓策略,不仅缺乏循征医学证据且带有一定风险。
Background and Objective:
     Aspirin is one of the most widely used antiplatelet drugs. The clinicaleffectiveness of aspirin in the first and secondary prevention of cardiovascular eventshas been well established. In the elderly, there is a high incidence of aspirin resistanceand bleeding. It is necessary to establish an early warning system. Populationpharmacokinetics/population pharmacodynamics (PPK/PPD), was proposed as a wayto utilize sparse data and investigate the fixed effect factors(eg.height, weight, age,comorbidities, and drug combination) which affect the pharmacokinetics orpharmacodynamics parameters. In this study, we explored the populationpharmacokinetics (PPK) of aspirin in healthy elderly volunteers and elderly patientswith coronary heart disease. The fixed effect factors(Age, gender, body weight index,comorbidities) were analysed. Meanwhile, the pharmacodynamics of aspirin and theeffects of covariates were determined. In addition, the understanding of aspirinresistance was improved.
     Methods:
     23healthy elderly volunteers aged over60years who received aspirin100mgdaily more than7days were enrolled in Hebei community. Blood samples wereobtained at the eighth day before administration and1,2,3,4,5,6,8,9,10,12h afteradministration of aspirin.210senile patients with coronary heart disease who receivedaspirin were enrolled in Geriatric Cardiology unit. Blood samples were randomlyobtained at the0-24h after administration of aspirin,1-4point every patient.Salicylate concentration was measured using a validated high-performance liquidchromatographic–electrospray tandem mass spectrometry assay method. AA, ADP were measured by turbidimetric method. PAC-1, CD62P were detected by flowcytometry method. Population pharmacokinetics analysis was performed bynon-linear mixed-effect modelling and VPC method for internal validation. Partialcorrelation and Logistic methods were used in pharmacodynamics analysis.
     Results:
     The final pharmacokinetic model was a one-compartment model with first-orderabsorption and elimination. The population estimates (interindividual variability;coefficient of variation) for salicylic acid were: a clearance of6.69L/h (range5.15-8.23), a absorption rate constant of1.05h (range0.83-28.6) and a total volume ofdistribution of41.2(range26.0-56.4). The total volume of distribution in patients waslower than in healthy individuals(0.646times). Age, gender, body weight index,comorbidities has not been included in the model. However, the only covariateinfluencing the clearance was ACEI combination. VPC verification were consistentwith the model calculation.
     In PPD analysis, a linear correlation was found between AA、ADP、PAC-1andsalicylic acid concentration. The correlation coefficient is-1.46,-0.379,-0.059,respectively. A exponential correlation was found between CD62P and salicylic acidconcentration. ADP and PAC-1are negatively correlated with salicylic acidconcentration using partial correlation method. There was no significant correlationbetween AA, ADP, CD62p and other factors and salicylic acid concentration was theprotective factors of PAC-1in healthy elderly group. There was no significantcorrelation between the four pharmacodynamic index and salicylic acid concentrationin all enrolled cases using partial correlation analysis. Logistic regression analysesshowed diabetes and cerebral infarction history as significant predictors of AA≥20%;clopidogrel as protective factor of ADP≥70%, PAC-1≥40%and CD62P≥20%; ageand herbal drugs as risk factors of CD62P≥20%; statin as risk factors ofPAC-1≥40%. Aspirin resistance rate was4.35%, semi aspirin resistance rates were4.35%(AA≥20%),73.91%(ADP≥70%) by measuring at different time points inhealthy elderly group.
     Conclusion:
     1.The total volume of distribution in patients was lower than healthyindividuals(0.646times)
     2. ACEI was significantly affected aspirin clearance. Aspirin clearance is lower incombination with ACEI(0.668times)
     3. There was a weak linear correlation between AA、ADP、PAC-1and salicylic acidconcentration. A feeble exponential correlation was found between CD62P andsalicylic acid concentration.
     4. Diabetes and cerebral infarction history were the significant predictors of AA≥20%;clopidogrel was a protective factor of ADP≥70%, PAC-1≥40%and CD62P≥20%;Age and herbal drugs combination were the risk factors of CD62P≥20%; Statin wasthe risk factors of PAC-1≥40%.
     5.The definition of biochemical aspirin resistance needs to be furtherimproved. Single-point evaluation of platelet aggregation was unilateral. Accordingto this single-point result to change antithrombotic strategies was dangerous.
引文
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