药学学报

Characteristic	Mean ± SD	Median (range)
Number of patients (male/female)	100 (75/25)	-
Number of tacrolimus samplings	357	-
Age/years	7.7 ±3.4	7.8 (1.3 15.9)
Body weight/kg	27.4 ± 12.3	23.3 (10.0 68.0)
Height/cm	115.0 ± 19.1	112.0 (76.0 171)
Tacrolimus daily dose/ μg·kg ^-1	57.6 ± 22.7	53.6 (8.6 125)
Tacrolimus daily dose/mg	1.4 ± 0.6	1.5 (0.25 3.5)
Tacrolimus concentration/μg·mL ^-1	6.3 ± 3.7	5.3 (2.0 29.2)
Sampling time after last dose/h	11.97 ± 0.3	11.97 (11.5 12.25)
Hemoglobin/g·L ^-1	136.7 ± 13.4	138.0 (87.0 173)
Haematocrit/%	41.2 ± 4.2	41.2 (26.1 52.4)
Albumin/g·L ^-1	28.2 ± 10.0	28.2 (9.3-48.1)
Total protein/g·L ^-1	48.0 ± 11.1	48.0 (21.1 79.2)
Aspartate transaminase/U·L ^-1	42.2 ± 22.5	38.0 (11.0 171)
Total bilirubin/μmolL ^-1	4.4 ± 4.8	3.2 (0.3 43.3)
Serum creatinine/μmol·L ^-1	36.5 ± 14.9	35.0 (4.0 107)
Urea nitrogen/mmol·L ^-1	4.0 ± 1.8	3.6 (1.5 18.1)
Creatinine clearance	179.3 ± 96.6	162.1 (56.8 1 164)
/mL_min i_1.73 m ^-2
Co-therapy medications
Corticosteroid^a	100 (315)	88.2%
Corticosteroid daily dose ^b/mg	15.0 ± 10.8	15.0 (0.0 50.0)
Calcium channel blockers
Diltiazem^a	28 (98)	27.5%
Amlodipine^a	10 (30)	8.4%
Azole antifungal agent
Ketoconazole^a	6 (18)	5.0%
Fluconazole^a	1 (5)	1.4%

Characteristic

Mean ± SD

Median (range)

Number of patients (male/female)

100 (75/25)

Number of tacrolimus samplings

357

Age/years

7.7 ±3.4

7.8 (1.3 15.9)

Body weight/kg

27.4 ± 12.3

23.3 (10.0 68.0)

Height/cm

115.0 ± 19.1

112.0 (76.0 171)

Tacrolimus daily dose/ μg·kg ^-1

57.6 ± 22.7

53.6 (8.6 125)

Tacrolimus daily dose/mg

1.4 ± 0.6

1.5 (0.25 3.5)

Tacrolimus concentration/μg·mL ^-1

6.3 ± 3.7

5.3 (2.0 29.2)

Sampling time after last dose/h

11.97 ± 0.3

11.97 (11.5 12.25)

Hemoglobin/g·L ^-1

136.7 ± 13.4

138.0 (87.0 173)

Haematocrit/%

41.2 ± 4.2

41.2 (26.1 52.4)

Albumin/g·L ^-1

28.2 ± 10.0

28.2 (9.3-48.1)

Total protein/g·L ^-1

48.0 ± 11.1

48.0 (21.1 79.2)

Aspartate transaminase/U·L ^-1

42.2 ± 22.5

38.0 (11.0 171)

Total bilirubin/μmolL ^-1

4.4 ± 4.8

3.2 (0.3 43.3)

Serum creatinine/μmol·L ^-1

36.5 ± 14.9

35.0 (4.0 107)

Urea nitrogen/mmol·L ^-1

4.0 ± 1.8

3.6 (1.5 18.1)

Creatinine clearance

179.3 ± 96.6

162.1 (56.8 1 164)

/mL_min i_1.73 m ^-2

Co-therapy medications

Corticosteroid^a

100 (315)

88.2%

Corticosteroid daily dose ^b/mg

15.0 ± 10.8

15.0 (0.0 50.0)

Calcium channel blockers

Diltiazem^a

28 (98)

27.5%

Amlodipine^a

10 (30)

8.4%

Azole antifungal agent

Ketoconazole^a

6 (18)

5.0%

Fluconazole^a

1 (5)

1.4%

Characteristic	Mean ± SD	Median (range)
Number of patients (male/female)	100 (75/25)	-
Number of tacrolimus samplings	357	-
Age/years	7.7 ±3.4	7.8 (1.3 15.9)
Body weight/kg	27.4 ± 12.3	23.3 (10.0 68.0)
Height/cm	115.0 ± 19.1	112.0 (76.0 171)
Tacrolimus daily dose/ μg·kg ^-1	57.6 ± 22.7	53.6 (8.6 125)
Tacrolimus daily dose/mg	1.4 ± 0.6	1.5 (0.25 3.5)
Tacrolimus concentration/μg·mL ^-1	6.3 ± 3.7	5.3 (2.0 29.2)
Sampling time after last dose/h	11.97 ± 0.3	11.97 (11.5 12.25)
Hemoglobin/g·L ^-1	136.7 ± 13.4	138.0 (87.0 173)
Haematocrit/%	41.2 ± 4.2	41.2 (26.1 52.4)
Albumin/g·L ^-1	28.2 ± 10.0	28.2 (9.3-48.1)
Total protein/g·L ^-1	48.0 ± 11.1	48.0 (21.1 79.2)
Aspartate transaminase/U·L ^-1	42.2 ± 22.5	38.0 (11.0 171)
Total bilirubin/μmolL ^-1	4.4 ± 4.8	3.2 (0.3 43.3)
Serum creatinine/μmol·L ^-1	36.5 ± 14.9	35.0 (4.0 107)
Urea nitrogen/mmol·L ^-1	4.0 ± 1.8	3.6 (1.5 18.1)
Creatinine clearance	179.3 ± 96.6	162.1 (56.8 1 164)
/mL_min i_1.73 m ^-2
Co-therapy medications
Corticosteroid^a	100 (315)	88.2%
Corticosteroid daily dose ^b/mg	15.0 ± 10.8	15.0 (0.0 50.0)
Calcium channel blockers
Diltiazem^a	28 (98)	27.5%
Amlodipine^a	10 (30)	8.4%
Azole antifungal agent
Ketoconazole^a	6 (18)	5.0%
Fluconazole^a	1 (5)	1.4%

Characteristic

Mean ± SD

Median (range)

Number of patients (male/female)

100 (75/25)

Number of tacrolimus samplings

357

Age/years

7.7 ±3.4

7.8 (1.3 15.9)

Body weight/kg

27.4 ± 12.3

23.3 (10.0 68.0)

Height/cm

115.0 ± 19.1

112.0 (76.0 171)

Tacrolimus daily dose/ μg·kg ^-1

57.6 ± 22.7

53.6 (8.6 125)

Tacrolimus daily dose/mg

1.4 ± 0.6

1.5 (0.25 3.5)

Tacrolimus concentration/μg·mL ^-1

6.3 ± 3.7

5.3 (2.0 29.2)

Sampling time after last dose/h

11.97 ± 0.3

11.97 (11.5 12.25)

Hemoglobin/g·L ^-1

136.7 ± 13.4

138.0 (87.0 173)

Haematocrit/%

41.2 ± 4.2

41.2 (26.1 52.4)

Albumin/g·L ^-1

28.2 ± 10.0

28.2 (9.3-48.1)

Total protein/g·L ^-1

48.0 ± 11.1

48.0 (21.1 79.2)

Aspartate transaminase/U·L ^-1

42.2 ± 22.5

38.0 (11.0 171)

Total bilirubin/μmolL ^-1

4.4 ± 4.8

3.2 (0.3 43.3)

Serum creatinine/μmol·L ^-1

36.5 ± 14.9

35.0 (4.0 107)

Urea nitrogen/mmol·L ^-1

4.0 ± 1.8

3.6 (1.5 18.1)

Creatinine clearance

179.3 ± 96.6

162.1 (56.8 1 164)

/mL_min i_1.73 m ^-2

Co-therapy medications

Corticosteroid^a

100 (315)

88.2%

Corticosteroid daily dose ^b/mg

15.0 ± 10.8

15.0 (0.0 50.0)

Calcium channel blockers

Diltiazem^a

28 (98)

27.5%

Amlodipine^a

10 (30)

8.4%

Azole antifungal agent

Ketoconazole^a

6 (18)

5.0%

Fluconazole^a

1 (5)

1.4%

Parameter	NONMEM		Bootstrap	Bias/%
k_a/h^-1	4.48	-		4.48	-	-
CL/F/L·h^-1	6.54	13.3%	6.73	5.20 -8.94	2.91
The impact of DD	-0.293	21.8%	-0.296	-0.433 --0.165	1.02
The impact of Azole	0.657	6.6%	0.667	0.574 -0.850	1.52
Y	-30.9	41.4%	-31.53	-95.68 --4.242	2.04
k₅₀	10.4	1.2%	10.38	1.54 -11.97	-0.19
V/F /L	86.2	34.2%	93.44	51.12 -244.99	8.40
Inter-individual variability
CL/F/%	27.5	20.3	27.4	25.2 -46.4	-0.15
Residual variability
Proportional error /%	35.9	10.8	35.6	30.3 -44.2	-0.84

Parameter

NONMEM

Bootstrap

Bias/%

Estimate

RSE

Median

2.5%-97.5%

k_a/h^-1

4.48

CL/F/L·h^-1

6.54

13.3%

6.73

5.20 -8.94

2.91

The impact of DD

-0.293

21.8%

-0.296

-0.433 --0.165

1.02

The impact of Azole

0.657

6.6%

0.667

0.574 -0.850

1.52

-30.9

41.4%

-31.53

-95.68 --4.242

2.04

k₅₀

10.4

1.2%

10.38

1.54 -11.97

-0.19

V/F /L

86.2

34.2%

93.44

51.12 -244.99

8.40

Inter-individual variability

CL/F/%

27.5

20.3

27.4

25.2 -46.4

-0.15

Residual variability

Proportional error /%

35.9

10.8

35.6

30.3 -44.2

-0.84

Parameter	NONMEM		Bootstrap	Bias/%
k_a/h^-1	4.48	-		4.48	-	-
CL/F/L·h^-1	6.54	13.3%	6.73	5.20 -8.94	2.91
The impact of DD	-0.293	21.8%	-0.296	-0.433 --0.165	1.02
The impact of Azole	0.657	6.6%	0.667	0.574 -0.850	1.52
Y	-30.9	41.4%	-31.53	-95.68 --4.242	2.04
k₅₀	10.4	1.2%	10.38	1.54 -11.97	-0.19
V/F /L	86.2	34.2%	93.44	51.12 -244.99	8.40
Inter-individual variability
CL/F/%	27.5	20.3	27.4	25.2 -46.4	-0.15
Residual variability
Proportional error /%	35.9	10.8	35.6	30.3 -44.2	-0.84

Parameter

NONMEM

Bootstrap

Bias/%

Estimate

RSE

Median

2.5%-97.5%

k_a/h^-1

4.48

CL/F/L·h^-1

6.54

13.3%

6.73

5.20 -8.94

2.91

The impact of DD

-0.293

21.8%

-0.296

-0.433 --0.165

1.02

The impact of Azole

0.657

6.6%

0.667

0.574 -0.850

1.52

-30.9

41.4%

-31.53

-95.68 --4.242

2.04

k₅₀

10.4

1.2%

10.38

1.54 -11.97

-0.19

V/F /L

86.2

34.2%

93.44

51.12 -244.99

8.40

Inter-individual variability

CL/F/%

27.5

20.3

27.4

25.2 -46.4

-0.15

Residual variability

Proportional error /%

35.9

10.8

35.6

30.3 -44.2

-0.84

儿童原发性肾病综合征患者中他克莫司的群体药动学研究

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黄凌斐 ¹^,² , 赵晨妍 ² , 焦正 ²^,^* , 刘艺茜 ²^,³ , 张慧芬 ¹ , 王珏 ¹ , 毛建华 ⁴

药学学报 | 研究论文 2018,53(2): 263-270

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药学学报 | 研究论文 2018, 53(2): 263-270

儿童原发性肾病综合征患者中他克莫司的群体药动学研究

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黄凌斐¹^,², 赵晨妍², 焦正²^,^*, 刘艺茜²^,³, 张慧芬¹, 王珏¹, 毛建华⁴

作者信息

1.浙江大学医学院附属儿童医院药剂科, 浙江杭州 310003

2.复旦大学附属华山医院药剂科, 上海 200040

3.中国药科大学基础医学与临床药学学院, 江苏南京 211198

4.浙江大学医学院附属儿童医院肾内科, 浙江杭州 310003

通讯作者:

* 焦正, Tel:86-21-52888712, E-mail:zjiao@fudan.edu.cn

Population pharmacokinetic study of tacrolimus in pediatric patients with primary nephrotic syndrome

Ling-fei HUANG¹^,², Chen-yan ZHAO², Zheng JIAO²^,^*, Yi-xi LIU²^,³, Hui-fen ZHANG¹, Jue WANG¹, Jian-hua MAO⁴

Affiliations

1. Department of Pharmacy, Children's Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China

2. Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai 200040, China

3. School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211198, China

4. Department of Nephrology, Children's Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China

出版时间: 2018-02-12 doi: 10.16438/j.0513-4870.2017-0639

文章导航

摘要

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他克莫司是治疗儿童难治性原发性肾病综合征（PNS）的常用药物。本研究回顾性收集了2010年5月至2016年3月间儿童PNS患者100例、357次常规监测的谷浓度数据，以及患儿的年龄、性别、体重、他克莫司日剂量、合用药物、肝肾功能等实验室指标，采用非线性混合效应模型（NONMEM）建立了他克莫司的群体药动学（PPK）模型。结果显示：具有一级吸收和消除的一房室模型能很好地拟合数据，他克莫司的表观清除率（CL/F）为6.54 L·h^-1，表观分布容积（V/F）为86.2 L，患儿的体重（WT，kg）、他克莫司日剂量（DD，mg·day^-1）、合用唑类抗真菌药对CL/F有显著影响。CL/F的最终模型为：CL/F=6.54×${\left( {\frac{{{\rm{WT}}}}{{25}}} \right)^k}$×${\left( {\frac{{{\rm{DD}}}}{{1.5}}} \right)^{0.293}}$×0.657^Azole，K=$\frac{{{\rm{W}}{{\rm{T}}^{ - 30.9}}}}{{{\rm{W}}{{\rm{T}}^{ - 30.9}} + {{10.4}^{ - 30.9}}}}$。其中合并使用唑类抗真菌药物时Azole为1，反之为0。本研究为国内外首次在儿童PNS患者中开展的他克莫司的PPK研究，可为该药的个体化给药方案设计提供参考。

关键词

他克莫司 / 儿童 / 原发性肾病综合征 / 群体药动学 / 非线性混合效应模型

Abstract

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Tacrolimus is commonly used in the treatment for the refractory primary nephrotic syndrome (PNS) in the pediatric patients. Data were retrospectively obtained from 100 children with 357 tacrolimus trough concentrations in our center between May 2010 and March 2016. Information of age, sex, body weight, drug dose, co-therapy medications, laboratory tests and sampling time were collected. The population pharmacokinetic model was developed using nonlinear mixed effect modeling (NONMEM) software. A one-compartment model with first-order absorption and elimination best described the data. The population estimate of apparent clearance (CL/F) and apparent volume of distribution (V/F) was 6.54 L·h^-1 and 86.2 L, respectively. Body weight (WT, kg), daily dose of tacrolimus (DD, mg·day^-1) and co-therapy azole antifungal agent have a significant impact on the CL/F. The final PPK model of CL/F was:CL/F=6.54×${\left( {\frac{{{\rm{WT}}}}{{25}}} \right)^k}$×${\left( {\frac{{{\rm{DD}}}}{{1.5}}} \right)^{0.293}}$×0.657^Azole, K=$\frac{{{\rm{W}}{{\rm{T}}^{ - 30.9}}}}{{{\rm{W}}{{\rm{T}}^{ - 30.9}} + {{10.4}^{ - 30.9}}}} $. When combined with azole antifungal agents, Azole was 1, whereas vice versa was 0. This is the first PPK study of tacrolimus conducted in pediatric patients with PNS, which may facilitate individualized drug therapy of tacrolimus.

Key words

tacrolimus / children / primary nephrotic syndrome / population pharmacokinetic / nonlinear mixed effect model

引用本文

黄凌斐, 赵晨妍, 焦正, 刘艺茜, 张慧芬, 王珏, 毛建华. 儿童原发性肾病综合征患者中他克莫司的群体药动学研究. 药学学报, 2018 , 53 (2) : 263 -270 . DOI: 10.16438/j.0513-4870.2017-0639

Ling-fei HUANG, Chen-yan ZHAO, Zheng JIAO, Yi-xi LIU, Hui-fen ZHANG, Jue WANG, Jian-hua MAO. Population pharmacokinetic study of tacrolimus in pediatric patients with primary nephrotic syndrome[J]. Acta Pharmaceutica Sinica, 2018 , 53 (2) : 263 -270 . DOI: 10.16438/j.0513-4870.2017-0639

正文

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他克莫司(tacrolimus)为常用钙调磷酸酶抑制剂(calcineurin inhibitors, CNIs)。该药通过抑制T淋巴细胞的活化增殖而发挥免疫抑制效应, 是肝、肾、心脏等器官移植术后的常用免疫抑制剂。在儿童常见的肾小球疾病—原发性肾病综合征(primary nephrotic syndrome, PNS)中, 该药作为常用的二线治疗药物, 用于频繁复发、激素依赖或耐药等难治性患者^[1-4]。与另一CNIs药物环孢素相比, 该药的免疫抑制作用更强、不良反应更少, 已逐渐取代了环孢素在难治性PNS中的地位^[5-7]。该药口服生物利用度低, 血浆蛋白结合率高, 广泛分布在红细胞内, 主要经肝脏代谢, 具有治疗窗窄、药动学个体差异大等特点^[8-10], 需要进行治疗药物监测(therapeutic drug monitoring, TDM)和个体化给药, 以避免药物浓度过低导致治疗失败或浓度过高而致不良反应发生率增加^[9-12]。

群体药动学(population pharmacokinetics, PPK)结合最大后验贝叶斯估算(maximum a posteriori Bayesian estimation, MAPB)是目前制定个体化给药方案的经典方法之一。相较于传统药动学, PPK可分析稀疏数据和不均一设计的实验数据, 定量研究影响药物体内过程的因素, 预测患者在特定给药剂量下的血药浓度、或者根据目标血药浓度推算所需的给药剂量^[13-16]。尽管国内外已有他克莫司在儿童患者中的PPK研究, 但均集中在肝移植^[17-20]、肾移植^[21-25]等器官移植领域, 未见有关儿童PNS群体的报道。而儿童PNS群体具有特殊的病理和生理特征, 如低蛋白血症会导致药物蛋白结合率下降, 胃肠壁水肿可影响药物的吸收, PNS合并高凝状态可致红细胞压积上升等^{[3, 26]}。以上因素都可导致他克莫司在儿童PNS中的药动学特征异于移植患者。

因此, 本研究旨在通过收集儿童PNS患者的他克莫司血药浓度常规监测数据, 应用非线性混合效应模型(nonlinear mixed effect model, NONMEM)建立他克莫司的PPK模型、筛选影响药动学的相关因素, 为儿童PNS患者中该药的个体化给药奠定基础。

方法

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患者和样本收集 本研究回顾性分析2010年5月至2016年3月间于浙江大学医学院附属儿童医院确诊PNS、并口服他克莫司(普乐可复^®, Astellas Ireland Co., Ltd.)的患者资料。入选患者的年龄 < 18周岁且性别不限。排除标准:新生儿或早产儿; 依从性不佳者; 胃肠道疾病者; 发生严重感染、深静脉血栓等并发症者; 他克莫司血药浓度低于最低检测浓度者。本研究方案经浙江大学医学院附属儿童医院伦理委员会批准。

他克莫司起始给药日剂量为50~100 μg·kg^-1, 分2次, 每12 h口服一次, 随后根据全血谷浓度(目标范围5~10 ng·mL^-1)调整给药剂量。患儿连续服用他克莫司同一剂量至少3天后, 采集清晨服药前的静脉全血2 mL置于乙二胺四乙酸(ethylene diamine tetraacetic acid, EDTA)抗凝管中。同时收集当天患儿的年龄、性别、身高、体重、他克莫司日剂量、合用药物以及肝肾功能等实验室检查结果。其中肾小球滤过率(eGFR)采用Schwartz公式^[27] (式1)估算:

(1) ${\rm{eGFR}}\left( {{\rm{mL \times mi}}{{\rm{n}}^{{\rm{-1}}}}{\rm{ \times 1}}{\rm{.73}}{{\rm{m}}^{{\rm{-2}}}}} \right){\rm{ = }}\frac{{\mathit{k}{\rm{ \times 身高}}\left( {{\rm{cm}}} \right)}}{{{\rm{血肌酐}}\left( {{\rm{ \mathit{ μ} mol \times }}{{\rm{L}}^{{\rm{-1}}}}} \right)}}$

式1中k为常数, ≤2岁时, k = 40; > 2岁女性及2~12岁男性, k = 49; ≥13岁男性, k = 62。

他克莫司的血药浓度检测采用酶放大免疫测定法(enzyme multiplied immunoassay technique, EMIT); 测定仪器为Viva-E自动生化分析仪(Siemens Healthcare Diagnostics Inc., Germany); 测定试剂为EMIT^® 2000检测试剂(Siemens Healthcare Diagnostics Inc., Germany)。检测时严格按照厂商说明书执行。方法的定量范围为2.0~30.0 ng·mL⁻¹, 日间精密度和日内精密度均小于20%。

数据分析软件 采用非线性混合效应模型软件NONMEM^® (Version 7.3, Icon Inc, PA, USA)和gFortran编译器(Version 4.60, http://gcc.gnu.org/ fortran/)进行群体药动学分析。R软件(Version 3.4.0, http://www.r-project.org)和Xpose (Version 4.5.0, Uppsala University, Sweden, http://xpose.sourceforge.net)进行绘图和可视化评价。群体药动学建模中采用个体间变异与残差变异有交互作用的一阶条件算法(first order conditional estimation with ƞ−ε interaction, FOCE-I)。

基础模型由于数据均为谷浓度, 无吸收相信息, 因此根据文献报道, 将吸收速率常数(absorption rate constant, K_a)固定为4.48 h⁻¹ ^{[18, 19]}。此外, 采用一级吸收和消除的一房室模型, 估算表观清除率(apparent total clearance, CL/F)和表观分布容积(apparent volume of distribution, V/F)。

式中θ为协变量对参数的影响程度; COV为某个体的协变量值; COV_m为协变量的中位数值或群体典型值。

个体间变异模型采用指数模型(式2) :

(2) ${P_{\rm{i}}} = {\rm{TV}}\left( P \right){\rm{ \times }}{{\rm{e}}^\eta }$

式2中P_i为第i名受试者的PK参数值, TV(P)为该参数的群体典型值, η是呈正态分布、均数为0、方差为ω²的个体间变异。

残差模型均采用加法、比例或加法比例的混合模型。其中混合模型(式3)如下:

(3) $Y = F{\rm{ \times }}\left( {1 + {\varepsilon _1}} \right) + {\varepsilon _2}$

式3中Y为实测值, F为模型预测值, ε₁和ε₂分别为比例型和加和型的残差变异, 分别服从均数为0、方差为σ₁²和σ₂²的正态分布。

协变量筛选 筛选的变量包括:患儿的年龄、性别、身高、体重、血常规、肝肾功能、他克莫司日剂量。合并用药中仅考察患者使用率大于5%的药物。由于本研究仅收集了常规监测的谷浓度数据, 故仅对CL/F的协变量进行考察。

本研究采用了逐步法筛选协变量, 包括前向纳入(forward inclusion)和逆向剔除(backward elimination)两个过程。前向纳入时, 加入协变量后的模型与原模型相比, 目标函数值(objective function value, OFV)降低大于3.84时(χ²检验, P < 0.05, df =1), 视该变量为有意义的协变量。逆向剔除中, 减少模型中的协变量后与原模型相比较, OFV值的升高大于6.63时(χ²检验, P < 0.01, df = 1), 该协变量在模型中保留。判别协变量时, 还考虑参数估算值的精度和合理性。

连续型变量分别采用线性(式4、5)或指数(式6)模型逐一进行考察, 而分类型变量则采用比例模型(式7, 以性别为例)进行考察。

(4) ${P_{\rm{i}}} = {\rm{TV}}\left( P \right) + \theta {\rm{ \times }}\left( {\frac{{{\rm{COV}}}}{{{\rm{CO}}{{\rm{V}}_{\rm{m}}}}}} \right)$

(5) ${P_{\rm{i}}} = {\rm{TV}}\left( P \right) + \theta {\rm{ \times }}\left( {{\rm{COV}}-{\rm{CO}}{{\rm{V}}_{\rm{m}}}} \right)$

(6) ${P_{\rm{i}}} = {\rm{TV}}\left( P \right){\rm{ \times }}{\left( {\frac{{{\rm{COV}}}}{{{\rm{CO}}{{\rm{V}}_{\rm{m}}}}}} \right)^\theta }$

(7) $\left\{ \begin{array}{l}{P_{\rm{i}}} = {\rm{TV}}\left( P \right)\;\;\;\;\;\;{\rm{男性}}\\{P_{\rm{i}}} = {\rm{TV}}\left( P \right){\rm{ \times }}\theta \;\;{\rm{女性}}\end{array} \right.$

上式中θ为协变量对参数的影响程度; COV为某个体的协变量值; COV_m为协变量的中位数值或群体典型值。

此外, 由于儿童中年龄和体重常为药动学的影响因素, 故根据文献, 补充考察成熟度模型(式8)^[28]、体重依赖的指数模型(bodyweight dependent exponent model, BDE, 式9)^{[14, 29]}和年龄依赖的指数模型(age dependent exponent model, ADE, 式10)^[14]。

(8) $\begin{array}{l}{P_{\rm{i}}} = {\rm{TV}}\left( P \right){\rm{ \times }}{\left( {\frac{{{\rm{WT}}}}{{{\rm{W}}{{\rm{T}}_{\rm{m}}}}}} \right)^{0.75}}{\rm{ \times }}{F_{{\rm{mat}}}}, \\\;\;\;\;\;\;\;{F_{{\rm{mat}}}} = \frac{1}{{1 + {{\left( {\frac{{{\rm{Age}}}}{{{k_{50}}}}} \right)}^\gamma }}}\end{array}$

(9) $\begin{array}{l}{P_{\rm{i}}} = {\rm{TV}}\left( P \right){\rm{ \times }}{\left( {\frac{{{\rm{WT}}}}{{{\rm{W}}{{\rm{T}}_{\rm{m}}}}}} \right)^k}, \\\;\;\;\;\;\;\;K = \frac{{{\rm{W}}{{\rm{T}}^\gamma }}}{{{\rm{W}}{{\rm{T}}^\gamma } + k_{50}^\gamma }}\end{array}$

(10) $\begin{array}{l}{P_{\rm{i}}} = {\rm{TV}}\left( P \right){\rm{ \times }}{\left( {\frac{{{\rm{WT}}}}{{{\rm{W}}{{\rm{T}}_{\rm{m}}}}}} \right)^K}, \\\;\;\;\;\;\;\;K = \frac{{{\rm{Ag}}{{\rm{e}}^\gamma }}}{{{\rm{Ag}}{{\rm{e}}^\gamma } + k_{50}^\gamma }}\end{array}$

以上式中WT为体重; WT_m为体重的中位数或典型值; F_mat是成熟度因子; γ为希尔指数, 曲线矫正斜率; Age为年龄; K是体重的幂函数, k₅₀为体重或年龄下降50%时的系数。

模型评价 采用三种方法对最终模型进行评价。首先, 绘制拟合优度图(goodness-of-fit, GOF)进行直观评价。拟合优度图主要包括:群体预测值—实测值(PRED-DV)、个体预测值—实测值(IPRED-DV)、条件权重残差—群体预测值(CWRES-PRED)和条件权重残差—时间(CWRES-TIME)的散点图。其次, 采用2 000次自举法(Bootstrap)考察模型参数估算的精度和模型稳定性。自举法是一种数据重采样技术。其过程为从n个原数据集中有放回地随机抽取n个观察值, 组成一个新样本; 然后用NONMEM程序对该样本进行参数估算。此过程重复2 000次后, 与原始计算结果值进行统计学比较以评价模型。最后, 采用基于模拟的正态预测分布误差法(normalized predictive distribution error, NPDE)评价模型。其过程如下:基于最终模型和参数估算值, 应用蒙特卡洛模拟(Monte Carlo Simulation)产生2 000套模拟数据集; 用作图和统计学检验考察标准化预测误差的分布。若模型良好, 则NPDE的均值为0 (Wilcoxon符号秩和检验)、方差为1 (Fisher方差检验)且符合正态分布(Shapiro-Wilks正态分布检验)。该法用R软件的NPDE包(Version 2.0, www.npde.biostat.fr)完成。

结果

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1 患者纳入

最终纳入100名PNS患儿及其357个他克莫司谷浓度点进行群体药动学分析。他克莫司给药剂量为57.6 ± 22.7 μg·kg^-1·day^-1, 平均谷浓度为6.3 ± 3.7 ng·mL^-1。具体人口学和实验室检查资料见表 1。

2 群体药动学模型

2.1 基础模型

由于混合模型的加法残差部分的估算精度不佳(362.2%), 且OFV值仅下降0.374 (P < 0.05)。故选择比例残差模型, CL/F和V/F的群体典型值分别为7.13 L·h^-1和132 L。

2.2 协变量筛选

本研究考察的协变量包括: ①人口学:性别(SEX)、年龄(AGE)、体重(WT)、他克莫司日剂量(DD); ②实验室指标:红细胞压积(HCT)、血浆白蛋白(ALB)、血浆总蛋白(TP)、天冬氨酸转氨酶(AST)、血肌酐(SCR)、肾小球滤过率(eGFR); ③合并用药:糖皮质激素、钙通道阻滞剂、唑类抗真菌药。

前向纳入分析表明体重、日剂量、合用唑类抗真菌药、红细胞压积为有意义的协变量。体重、年龄与清除率的关系筛查表明:相较于经典异速生长模型、成熟度模型和年龄依赖的指数模型, 体重依赖的指数模型的估算精度最佳且OFV值最低。逆向剔除法表明除了红细胞压积以外, 其他协变量均能保留在最终CL/F模型中。

2.3 最终模型

采用一级吸收和消除的一室模型可描述他克莫司在儿童PNS中的药动学特征。最终模型的CL/F和V/F的群体典型值分别为6.54 L·h^-1和86.2 L。最终模型的CL/F如下:

(11) $\left\{ \begin{array}{l}CL/F\left( {L \cdot {h^{-1}}} \right) = 6.54 \times {\left( {\frac{{{\rm{WT}}}}{{{\rm{25}}}}} \right)^K} \times {\left( {\frac{{{\rm{DD}}}}{{{\rm{1}}{\rm{.5}}}}} \right)^{0.293}} \times {0.657^{{\rm{Azole}}}}\\\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;K = \frac{{{\rm{W}}{{\rm{T}}^{-30.9}}}}{{{\rm{W}}{{\rm{T}}^{-30.9}} + {{10.4}^{ - 30.9}}}}\end{array} \right.$

式中DD为他克莫司日剂量, WT为患儿体重, 合用唑类抗真菌药时Azole为1, 反之为0。最终模型参数的群体典型值及参数变异估计值见表 2。此外, 上述结果表明, 当体重大于12 kg时, 体重对于CL/F已无显著影响。

2.4 模型评价

基础模型和最终模型的拟合优度图见图 1。由图可见:与基础模型相比, 最终模型的拟合优度有显著改善; 实测值对PRED和IPRED散点更均匀且紧密地分布在参考线(y = x)两侧, CWRES对PRED和时间的散点图中可见更多的点落在0 ± 2之间, 表明最终模型的拟合度更好。

NPDE的结果见图 2, 包括: ① Q-Q图:点分布在趋势线上或均匀分布在趋势线两边; ② NPDE的直方图呈正态分布; ③ NPDE对时间作图和④ NPDE对PRED图中, 散点都均匀落在± 1.96 NPDE中, 并在90%的区间内。统计学检验表明NPDE均值为0 (P = 0.927)、方差为1 (P = 0.187)符合正态分布(P = 0.137)表明最终模型的预测性良好。

此外, 模型条件数(condition number)为213, CL/F相关参数的估算精度除了希尔指数外均小于25%, Bootstrap计算的成功率为97.8%, 且估算值与NONMEM原始估算值的偏差均小于9% (表 2)。上述结果表明模型参数的估算结果可靠且稳定。

讨论

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近几年来, 他克莫司在儿童难治性PNS患者中的疗效及地位逐渐得到认可。但因该药具有治疗窗窄、药动学个体差异大、浓度与剂量相关性尚未明确等特点, 需要个体化给药。本研究首次考察了他克莫司在儿童PNS群体中的PPK特征, 为该药的个体化治疗提供基础。

本研究显示他克莫司在PNS患儿中的CL/F为6.54 L·h^-1, 与国内外儿童移植患者的报道有所不同。如近年报道:儿童肝移植患者CL/F为5.72~12.9 L·h^-1^[17-20]; 儿童肾移植患者CL/F为11.98~17.5 L·h^-1^[22-25]。该结果提示儿童PNS患者中他克莫司的平均清除率低于儿童肾移植患者, 儿童PNS患者只要使用较小剂量的他克莫司即可达到与肾移植患者相同的目标浓度。这与临床实践经验相符, 通常儿童器官移植后他克莫司需用100~150 μg·kg^-1·day^-1甚至更高剂量^{[17, 18, 25, 30-32]}, 而本次研究收集到的他克莫司日剂量为57.6 ± 22.7 μg·kg^-1·day^-1。此较低的剂量范围已在本中心的既往研究^{[33, 34]}中被证实有效。

本研究还表明, 体重是影响CL/F的重要因素之一:当体重≤12 kg时, CL/F随着体重的增大而增大。这种现象可能与儿童的生长发育过程有关。肝药酶的活性在新生儿中非常弱, 而后会逐渐增强, 在2~3岁左右(体重约12 kg)可达到成人水平^[35]。本研究结果还显示:体重 > 12 kg时, 对于CL/F已无显著影响。这与成人移植患者中的结果相近^[36], 可能与患儿使用他克莫司剂量较低所致。他克莫司日剂量与CL/F之间存在非线性的正相关, 日剂量越大, CL/F越高。这与一些成人移植患者中的研究结果一致^[36], 可能是由于他克莫司脂溶性大, 剂量增大时口服生物利用度降低所致^[37]。

他克莫司是CYP3A4/5的代谢底物, 也是肠道P-糖蛋白外排泵的底物。该药与诸多药物间的相互作用在成人及儿童的研究中已有报道, 如糖皮质激素^[38-40]、钙通道阻滞剂^{[41, 42]}、抗菌药物^{[20, 43, 44]}等。本研究显示合用唑类抗真菌药可显著降低他克莫司的清除, 合用酮康唑或氟康唑患者他克莫司的CL/F为未合用者的64.9%。酮康唑和氟康唑均为CYP3A4/5的强抑制剂, 使他克莫司肝代谢受到显著抑制。因建模数据中合用唑类抗真菌药物的病例较少, 研究过程中将酮康唑、氟康唑合并为一类药物进行分析, 可在未来的研究中进一步考察不同唑类抗真菌药物的影响。此外, 本研究未见糖皮质激素(泼尼松、甲泼尼龙)、钙通道阻滞剂(氨氯地平、地尔硫䓬)的影响, 可能是由于糖皮质激素用量较低(按泼尼松计15.2 ± 10.9 mg·day^-1)、钙通道阻滞剂在儿童PNS中使用比例相对较低所致。

他克莫司在血液中主要与红细胞结合, 因此在一些成人^{[45, 46]}、儿童^[17]移植患者研究中均认为红细胞压积是药动学的重要影响因素。在儿童PNS患者中, 因血中促凝因子增加、纤维蛋白原合成增加、糖皮质激素应用等原因, 常处于血液高凝状态, 红细胞压积可明显升高^[3]。因此本研究假设红细胞压积水平可影响他克莫司在儿童PNS中的CL/F。然而研究结果表明红细胞压积的影响不显著(P > 0.01)。可能的原因是本研究中PNS患儿的红细胞压积水平都处于正常上限、波动范围小(平均41.2% ± 4.2%), 明显异于器官移植后的儿童人群。如Musuamba等^[17]研究中, 82例儿童肝移植患者红细胞压积均值为28%, 波动在18%~44%。

本研究为单中心的回顾性研究, 纳入病例数有限, 所建模型的外推性有待进一步考察。其次, 有报道认为CYP3A5*3的基因多态性^{[20, 24]}对儿童移植患者的他克莫司药动学有显著影响, 在后续研究中将考察该因素的影响。

综上所述, 本研究首次对儿童PNS患者的他克莫司PPK特征进行了考察, 表明体重、他克莫司日剂量、合并用唑类抗真菌药是影响他克莫司在儿童PNS患者中药动学的重要因素, 为该药的个体化给药方案制定奠定了基础。

基金

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国家自然科学基金面上项目(81573505)
上海市卫生计生系统重要薄弱学科建设计划资助项目(2016ZB0301-01)

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文献

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2018年第53卷第2期

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doi: 10.16438/j.0513-4870.2017-0639

接收时间：2017-07-15
首发时间：2026-01-15
出版时间：2018-02-12

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出版历史

收稿日期：2017-07-15
录用日期：2017-08-30

基金

国家自然科学基金面上项目(81573505)

上海市卫生计生系统重要薄弱学科建设计划资助项目(2016ZB0301-01)

作者信息

1.浙江大学医学院附属儿童医院药剂科, 浙江杭州 310003

2.复旦大学附属华山医院药剂科, 上海 200040

3.中国药科大学基础医学与临床药学学院, 江苏南京 211198

4.浙江大学医学院附属儿童医院肾内科, 浙江杭州 310003

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* 焦正, Tel:86-21-52888712, E-mail:zjiao@fudan.edu.cn

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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Characteristic	Mean ± SD	Median (range)
Number of patients (male/female)	100 (75/25)	-
Number of tacrolimus samplings	357	-
Age/years	7.7 ±3.4	7.8 (1.3 15.9)
Body weight/kg	27.4 ± 12.3	23.3 (10.0 68.0)
Height/cm	115.0 ± 19.1	112.0 (76.0 171)
Tacrolimus daily dose/ μg·kg ^-1	57.6 ± 22.7	53.6 (8.6 125)
Tacrolimus daily dose/mg	1.4 ± 0.6	1.5 (0.25 3.5)
Tacrolimus concentration/μg·mL ^-1	6.3 ± 3.7	5.3 (2.0 29.2)
Sampling time after last dose/h	11.97 ± 0.3	11.97 (11.5 12.25)
Hemoglobin/g·L ^-1	136.7 ± 13.4	138.0 (87.0 173)
Haematocrit/%	41.2 ± 4.2	41.2 (26.1 52.4)
Albumin/g·L ^-1	28.2 ± 10.0	28.2 (9.3-48.1)
Total protein/g·L ^-1	48.0 ± 11.1	48.0 (21.1 79.2)
Aspartate transaminase/U·L ^-1	42.2 ± 22.5	38.0 (11.0 171)
Total bilirubin/μmolL ^-1	4.4 ± 4.8	3.2 (0.3 43.3)
Serum creatinine/μmol·L ^-1	36.5 ± 14.9	35.0 (4.0 107)
Urea nitrogen/mmol·L ^-1	4.0 ± 1.8	3.6 (1.5 18.1)
Creatinine clearance	179.3 ± 96.6	162.1 (56.8 1 164)
/mL_min i_1.73 m ^-2
Co-therapy medications
Corticosteroid^a	100 (315)	88.2%
Corticosteroid daily dose ^b/mg	15.0 ± 10.8	15.0 (0.0 50.0)
Calcium channel blockers
Diltiazem^a	28 (98)	27.5%
Amlodipine^a	10 (30)	8.4%
Azole antifungal agent
Ketoconazole^a	6 (18)	5.0%
Fluconazole^a	1 (5)	1.4%

Characteristic

Mean ± SD

Median (range)

Number of patients (male/female)

100 (75/25)

Number of tacrolimus samplings

357

Age/years

7.7 ±3.4

7.8 (1.3 15.9)

Body weight/kg

27.4 ± 12.3

23.3 (10.0 68.0)

Height/cm

115.0 ± 19.1

112.0 (76.0 171)

Tacrolimus daily dose/ μg·kg ^-1

57.6 ± 22.7

53.6 (8.6 125)

Tacrolimus daily dose/mg

1.4 ± 0.6

1.5 (0.25 3.5)

Tacrolimus concentration/μg·mL ^-1

6.3 ± 3.7

5.3 (2.0 29.2)

Sampling time after last dose/h

11.97 ± 0.3

11.97 (11.5 12.25)

Hemoglobin/g·L ^-1

136.7 ± 13.4

138.0 (87.0 173)

Haematocrit/%

41.2 ± 4.2

41.2 (26.1 52.4)

Albumin/g·L ^-1

28.2 ± 10.0

28.2 (9.3-48.1)

Total protein/g·L ^-1

48.0 ± 11.1

48.0 (21.1 79.2)

Aspartate transaminase/U·L ^-1

42.2 ± 22.5

38.0 (11.0 171)

Total bilirubin/μmolL ^-1

4.4 ± 4.8

3.2 (0.3 43.3)

Serum creatinine/μmol·L ^-1

36.5 ± 14.9

35.0 (4.0 107)

Urea nitrogen/mmol·L ^-1

4.0 ± 1.8

3.6 (1.5 18.1)

Creatinine clearance

179.3 ± 96.6

162.1 (56.8 1 164)

/mL_min i_1.73 m ^-2

Co-therapy medications

Corticosteroid^a

100 (315)

88.2%

Corticosteroid daily dose ^b/mg

15.0 ± 10.8

15.0 (0.0 50.0)

Calcium channel blockers

Diltiazem^a

28 (98)

27.5%

Amlodipine^a

10 (30)

8.4%

Azole antifungal agent

Ketoconazole^a

6 (18)

5.0%

Fluconazole^a

1 (5)

1.4%

Parameter	NONMEM		Bootstrap	Bias/%
k_a/h^-1	4.48	-		4.48	-	-
CL/F/L·h^-1	6.54	13.3%	6.73	5.20 -8.94	2.91
The impact of DD	-0.293	21.8%	-0.296	-0.433 --0.165	1.02
The impact of Azole	0.657	6.6%	0.667	0.574 -0.850	1.52
Y	-30.9	41.4%	-31.53	-95.68 --4.242	2.04
k₅₀	10.4	1.2%	10.38	1.54 -11.97	-0.19
V/F /L	86.2	34.2%	93.44	51.12 -244.99	8.40
Inter-individual variability
CL/F/%	27.5	20.3	27.4	25.2 -46.4	-0.15
Residual variability
Proportional error /%	35.9	10.8	35.6	30.3 -44.2	-0.84

Parameter

NONMEM

Bootstrap

Bias/%

Estimate

RSE

Median

2.5%-97.5%

k_a/h^-1

4.48

CL/F/L·h^-1

6.54

13.3%

6.73

5.20 -8.94

2.91

The impact of DD

-0.293

21.8%

-0.296

-0.433 --0.165

1.02

The impact of Azole

0.657

6.6%

0.667

0.574 -0.850

1.52

-30.9

41.4%

-31.53

-95.68 --4.242

2.04

k₅₀

10.4

1.2%

10.38

1.54 -11.97

-0.19

V/F /L

86.2

34.2%

93.44

51.12 -244.99

8.40

Inter-individual variability

CL/F/%

27.5

20.3

27.4

25.2 -46.4

-0.15

Residual variability

Proportional error /%

35.9

10.8

35.6

30.3 -44.2

-0.84