Drabik Attyla, Sturm Andreas, Blömacher Margit, Helwig Ulf
Clinical Trial Support, Münster, Germany.
JMIR Res Protoc. 2016 Jun 28;5(2):e124. doi: 10.2196/resprot.5791.
The treatment of ulcerative colitis (UC) patients with moderate to severe inflammatory activity with anti-tumor necrosis factor alpha (TNFα) antibodies leads to a clinical remission rate of 10% after 8 weeks of therapy. However, it must be taken into account that patient selection in clinical trials clearly influences both response and remission rates. An unsatisfactory response to anti-TNFα medication after week 12 often leads to a discontinuation of treatment. The early prediction of clinical response could therefore help optimize therapy and potentially avoid ineffective treatments.
The aim of this study is to develop an algorithm for optimizing golimumab administration in patients with moderate to severe UC by calculating the probability of clinical response in Week 26 based on data from Week 6.
The study is designed as a prospective, single-arm, multicenter, non-interventional observational study with no interim analyses and a sample size of 58 evaluable patients. The primary outcome is the prediction of clinical response in Week 26 based on a 50% reduction in fecal calprotectin and a positive golimumab trough level in Week 6.
Enrollment started in October 2014 and was still open at the date of submission. The study is expected to finish in December 2016.
The early identification of patients who are responding to an anti-TNFα antibody is therapeutically beneficial. At the same time, patients who are not responding can be identified earlier. The development of a therapeutic algorithm for identifying patients as responders or non-responders can thus help prescribing physicians to both avoid ineffective treatments and adjust dosages when necessary. This in turn promotes a higher degree of treatment tolerance and patient safety in the case of anti-TNFα antibody administration.
German Clinical Trials Register, Deutsches Register Klinischer Studien DRKS00005940; https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00005940 (Archived by WebCite at http://www.webcitation.org/6i4Xoo1sH).
使用抗肿瘤坏死因子α（TNFα）抗体治疗中度至重度炎症活动的溃疡性结肠炎（UC）患者，治疗8周后的临床缓解率为10%。然而，必须考虑到临床试验中的患者选择明显影响反应率和缓解率。治疗12周后对抗TNFα药物反应不佳通常会导致治疗中断。因此，临床反应的早期预测有助于优化治疗并可能避免无效治疗。
本研究的目的是通过根据第6周的数据计算第26周临床反应的概率，开发一种优化中度至重度UC患者戈利木单抗给药的算法。
本研究设计为前瞻性、单臂、多中心、非干预性观察性研究，无中期分析，样本量为58例可评估患者。主要结局是根据第6周粪便钙卫蛋白降低50%和戈利木单抗谷浓度为阳性来预测第26周的临床反应。
入组于2014年10月开始，在提交本文时仍在进行。该研究预计于2016年12月完成。
早期识别对抗TNFα抗体有反应的患者具有治疗益处。同时，可以更早地识别无反应的患者。因此，开发一种用于识别反应者或无反应者的治疗算法可以帮助开处方的医生避免无效治疗并在必要时调整剂量。这反过来又提高了抗TNFα抗体给药情况下的治疗耐受性和患者安全性。
德国临床试验注册中心，德国临床研究注册DRKS00005940；https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00005940（由WebCite存档于http://www.webcitation.org/6i4Xoo1sH）
