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预测炎症性肠病患者硫嘌呤诱导肝毒性的算法。

Predictive Algorithm for Thiopurine-Induced Hepatotoxicity in Inflammatory Bowel Disease Patients.

机构信息

Department of Pharmacy, Jeroen Bosch Hospital, 's-Hertogenbosch, the Netherlands.

Department of Clinical Pharmacy, Bernhoven Hospital, Uden, the Netherlands.

出版信息

Ther Drug Monit. 2022 Dec 1;44(6):747-754. doi: 10.1097/FTD.0000000000001031.

DOI:10.1097/FTD.0000000000001031
PMID:36070763
Abstract

BACKGROUND

Approximately 25% of patients with inflammatory bowel disease (IBD) discontinue azathioprine (AZA) or mercaptopurine (MP) therapy within 3 months of treatment initiation because of adverse drug reactions. Of these side-effects, about half are because of hepatotoxicity. The aim of this study was to validate and (subsequently) optimize a previously reported predictive algorithm for thiopurine-associated hepatotoxicity by increasing the number of patients with IBD benefitting from conventional thiopurine therapy.

METHODS

This multicenter observational study included consecutive thiopurine-naive patients with IBD who received AZA or MP treatment. The primary outcome was hepatotoxicity within 12 weeks. The patients with and without hepatotoxicity were compared. Four determinants, namely, age, sex, body mass index (BMI), and 6-methylmercaptopurine ribonucleotide concentrations 1 week after treatment initiation (T = 1) were used to validate and optimize 2 (1 dichotomous and 1 continuous) algorithms using multivariable logistic regression analysis.

RESULTS

Of 229 patients, 21 (9%) developed hepatotoxicity and 93% of the patients received MP with a median dose of 0.7 mg/kg (95% confidence interval 0.3-1.4 mg/kg). A difference in BMI was found between with and without hepatotoxicity groups (median 27.6 versus 24.2, P = 0.022). Specificities of 68% (Algorithm 1) and 77% (Algorithm 2) and sensitivities of 56% (Algorithm 1) and 50% (Algorithm 2) were obtained.

CONCLUSIONS

Both algorithms demonstrated limited predictive accuracy for thiopurine-induced hepatotoxicity in the validation cohort. Relevant factors contributing to this outcome were changes in thiopurine prescription behavior over time, with more MP prescriptions at relatively lower dosages of MP.

摘要

背景

大约 25%的炎症性肠病(IBD)患者在开始治疗后 3 个月内停止使用巯嘌呤(AZA)或巯基嘌呤(MP)治疗,因为出现药物不良反应。这些副作用中,大约一半是因为肝毒性。本研究的目的是通过增加受益于传统巯嘌呤治疗的 IBD 患者数量来验证和(随后)优化先前报道的预测巯嘌呤相关肝毒性的算法。

方法

这是一项多中心观察性研究,纳入了接受 AZA 或 MP 治疗的初治 IBD 巯嘌呤-naive 患者。主要结局是 12 周内的肝毒性。比较有肝毒性和无肝毒性的患者。使用多变量逻辑回归分析,使用 4 个决定因素(年龄、性别、体重指数(BMI)和治疗开始后 1 周时的 6-甲基巯基嘌呤核糖核苷酸浓度(T = 1))来验证和优化 2 个(1 个二项式和 1 个连续)算法。

结果

在 229 例患者中,21 例(9%)发生肝毒性,93%的患者接受 MP 治疗,中位数剂量为 0.7mg/kg(95%置信区间 0.3-1.4mg/kg)。有肝毒性和无肝毒性组之间的 BMI 存在差异(中位数 27.6 与 24.2,P = 0.022)。算法 1 的特异性为 68%,敏感性为 56%;算法 2 的特异性为 77%,敏感性为 50%。

结论

验证队列中,两种算法对巯嘌呤诱导的肝毒性的预测准确性均有限。导致这一结果的相关因素是随着时间的推移,巯嘌呤处方行为发生变化,MP 处方相对较低剂量。

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