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利用预测风险监测I期试验中的迟发性毒性。

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

作者信息

Bekele B Nebiyou, Ji Yuan, Shen Yu, Thall Peter F

机构信息

Department of Biostatistics, MD Anderson Cancer Center, Houston, TX 77030, USA.

出版信息

Biostatistics. 2008 Jul;9(3):442-57. doi: 10.1093/biostatistics/kxm044. Epub 2007 Dec 14.

Abstract

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.

摘要

迟发性(LO)毒性在许多I期试验中是一个严重问题。由于大多数剂量限制性毒性在治疗开始后不久就会出现,大多数剂量探索方法使用在初始短时间内出现毒性的二元指标。然而,如果一种药物会导致迟发性毒性,那么在观察到任何毒性之前,可能会有大量患者接受毒性剂量的治疗。一种解决这个问题的方法是事件发生时间连续重新评估方法(TITE-CRM,Cheung和Chappell,2000年)。我们提出一种类似于TITE-CRM的贝叶斯剂量探索方法,其中使用毒性发生时间数据来选择剂量。我们方法的新特点是一组基于预测概率的规则,如果未来患者接受预期剂量时的毒性风险高得不可接受,则暂时停止入组。如果额外的随访数据将预测的毒性风险降低到可接受水平,则重新开始入组,并且在试验期间这个过程可能会重复几次。一项模拟研究表明,所提出的方法比TITE-CRM提供了更高的安全性,同时仍然能够可靠地选择最佳剂量。这种优势随着入组率的增加而增加,但这种额外安全性的代价是试验平均完成时间会更长。

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本文引用的文献

1
Bayesian inference on order-constrained parameters in generalized linear models.
Biometrics. 2003 Jun;59(2):286-95. doi: 10.1111/1541-0420.00035.
2
Sequential ordinal modeling with applications to survival data.
Biometrics. 2001 Sep;57(3):829-36. doi: 10.1111/j.0006-341x.2001.00829.x.
3
A solution to the problem of monotone likelihood in Cox regression.
Biometrics. 2001 Mar;57(1):114-9. doi: 10.1111/j.0006-341x.2001.00114.x.
4
Sequential designs for phase I clinical trials with late-onset toxicities.
Biometrics. 2000 Dec;56(4):1177-82. doi: 10.1111/j.0006-341x.2000.01177.x.
5
Accrual strategies for phase I trials with delayed patient outcome.
Stat Med. 1999 May 30;18(10):1155-69. doi: 10.1002/(sici)1097-0258(19990530)18:10<1155::aid-sim114>3.0.co;2-h.
6
Cancer phase I clinical trials: efficient dose escalation with overdose control.
Stat Med. 1998 May 30;17(10):1103-20. doi: 10.1002/(sici)1097-0258(19980530)17:10<1103::aid-sim793>3.0.co;2-9.
7
Design and analysis of phase I clinical trials.
Biometrics. 1989 Sep;45(3):925-37.

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