英夫利昔单抗
析因分析
医学
事后
药品
抗体
临床试验
相关性(法律)
内科学
药理学
免疫学
肿瘤坏死因子α
政治学
法学
作者
Thomas Van Stappen,Niels Vande Casteele,Gert Van Assche,Marc Ferrante,Séverine Vermeire,Ann Gils
出处
期刊:Gut
[BMJ]
日期:2017-04-27
卷期号:67 (5): 818-826
被引量:100
标识
DOI:10.1136/gutjnl-2016-313071
摘要
Objective To evaluate the clinical relevance of antidrug antibodies (ADAs) measured using a drug-tolerant assay in a post hoc analysis of the Trough Concentration (TC) Adapted Infliximab Treatment (TAXIT) randomised controlled trial. Design ADA in serum samples (n=221) of 76 patients enrolled in TAXIT, who presented with an infliximab TC <3 µg/mL at screening, were reanalysed after optimisation and at the end of the study using a drug-tolerant ADA assay. Patients underwent dose escalation to achieve therapeutic TCs between 3 µg/mL and 7 µg/mL prior to randomisation. Patients were grouped into quartiles (Q1–4) according to ADA concentration at screening. Results Using a drug-tolerant assay, the immunogenicity detection rate increased from 21% (drug-sensitive assay) to 63% at screening, from 0% to 51% after optimisation and from 3% to 42% at the end of TAXIT. Patients in ADA Q4 required a higher cumulative infliximab dose (2390 (880–2998) mg) to achieve target TCs, resulting in a higher drug cost (€10 712 (4120–13 596)) compared with ADA-negative patients (€2060 (1648–3296)) and patients in ADA Q1/Q2 (€2060 (1648–4120)/€2060 (1751–3296), p<0.001). However, all but one patient belonging to ADA Q4 were also ADA-positive using a drug-sensitive assay. Conclusions Upon dose intensification, low concentration ADAs, not detectable using a drug-sensitive assay, disappear in more than half of the patients over time and are clinically non-relevant. In contrast, high concentration ADAs which are typically also detected in a drug-sensitive assay, persist over time and necessitate a higher cumulative dose and drug cost. In the latter group, proactive drug switching may be more cost-efficient. Clinical Trials Register 2011-002061-38; Post-results.
科研通智能强力驱动
Strongly Powered by AbleSci AI