Monitoring late-onset toxicities in phase I trials using predicted risks

Monitoring late-onset toxicities in phase I trials using predicted risks
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DOI:
10.1093/biostatistics/kxm044
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发表时间:
2008-07-01
期刊:
影响因子:
2.1
通讯作者:
Thall, Peter F.
Thall, Peter F.
中科院分区:
数学2区
文献类型:
--
作者:
Bekele, B. Nebiyou;Ji, Yuan;Thall, Peter F.

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迟发性(LO)毒性是许多I期试验中的严重问题。由于大多数剂量限制性毒性在治疗开始后不久发生,因此大多数剂量确定方法使用在短的初始时间段内发生的毒性的二元指标。然而,如果药剂引起LO毒性,则在观察到任何毒性之前,可能以毒性剂量治疗不期望的大量患者。解决这个问题的一种方法是事件发生时间连续再评估方法(TITE-CRM,Cheung和Chappell,2000年)。我们提出了一个贝叶斯剂量发现方法类似于TITE-CRM中的剂量选择使用时间毒性数据。我们的方法的新方面是一组规则,基于预测概率,如果未来患者在预期剂量下的毒性风险高得不可接受,则暂时暂停累积。如果额外的随访数据将预测的毒性风险降低到可接受的水平,则重新开始累积,并且该过程可以在试验期间重复多次。模拟研究表明,所提出的方法提供了更大程度的安全性比TITE-CRM,同时仍然可靠地选择首选剂量。这种优势随着增加率而增加,但这种额外的安全性的代价是平均需要更长的时间才能完成试验。
Late-onset (LO) toxicities are a serious concern in many phase I trials. Since most dose-limiting toxicities occur soon after therapy begins, most dose-finding methods use a binary indicator of toxicity occurring within a short initial time period. If an agent causes LO toxicities, however, an undesirably large number of patients may be treated at toxic doses before any toxicities are observed. A method addressing this problem is the time-to-event continual reassessment method (TITE-CRM, Cheung and Chappell, 2000). We propose a Bayesian dose-finding method similar to the TITE-CRM in which doses are chosen using time-to-toxicity data. The new aspect of our method is a set of rules, based on predictive probabilities, that temporarily suspend accrual if the risk of toxicity at prospective doses for future patients is unacceptably high. If additional follow-up data reduce the predicted risk of toxicity to an acceptable level, then accrual is restarted, and this process may be repeated several times during the trial. A simulation study shows that the proposed method provides a greater degree of safety than the TITE-CRM, while still reliably choosing the preferred dose. This advantage increases with accrual rate, but the price of this additional safety is that the trial takes longer to complete on average.