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实施随机化的一些实际问题。

Some practical problems in implementing randomization.

机构信息

Statistics Collaborative Inc., Washington DC, USA.

出版信息

Clin Trials. 2010 Jun;7(3):235-45. doi: 10.1177/1740774510368300.

Abstract

BACKGROUND

While often theoretically simple, implementing randomization to treatment in a masked, but confirmable, fashion can prove difficult in practice.

PURPOSE

At least three categories of problems occur in randomization: (1) bad judgment in the choice of method, (2) design and programming errors in implementing the method, and (3) human error during the conduct of the trial. This article focuses on these latter two types of errors, dealing operationally with what can go wrong after trial designers have selected the allocation method.

RESULTS

We offer several case studies and corresponding recommendations for lessening the frequency of problems in allocating treatment or for mitigating the consequences of errors. Recommendations include: (1) reviewing the randomization schedule before starting a trial, (2) being especially cautious of systems that use on-demand random number generators, (3) drafting unambiguous randomization specifications, (4) performing thorough testing before entering a randomization system into production, (5) maintaining a dataset that captures the values investigators used to randomize participants, thereby allowing the process of treatment allocation to be reproduced and verified, (6) resisting the urge to correct errors that occur in individual treatment assignments, (7) preventing inadvertent unmasking to treatment assignments in kit allocations, and (8) checking a sample of study drug kits to allow detection of errors in drug packaging and labeling.

LIMITATIONS

Although we performed a literature search of documented randomization errors, the examples that we provide and the resultant recommendations are based largely on our own experience in industry-sponsored clinical trials. We do not know how representative our experience is or how common errors of the type we have seen occur.

CONCLUSIONS

Our experience underscores the importance of verifying the integrity of the treatment allocation process before and during a trial. Clinical Trials 2010; 7: 235-245. http://ctj.sagepub.com.

摘要

背景

虽然从理论上讲,以掩蔽但可确认的方式实施随机化治疗通常很简单,但在实践中却可能难以实现。

目的

随机化过程中至少会出现三类问题:(1)方法选择方面的判断失误,(2)实施方法过程中的设计和编程错误,以及(3)试验进行过程中的人为错误。本文重点关注后两种类型的错误,针对试验设计者选择分配方法后可能出现的问题进行操作层面上的讨论。

结果

我们提供了几个案例研究和相应的建议,以减少分配治疗方法或减轻错误后果的频率。建议包括:(1)在开始试验之前,对随机分组方案进行审查;(2)特别谨慎地对待使用按需随机数生成器的系统;(3)起草明确的随机化规范;(4)在将随机分组系统投入生产之前进行全面测试;(5)维护一个数据集,其中包含研究人员用于随机化参与者的数值,从而可以重现和验证治疗分配过程;(6)抵制纠正个别治疗分配中出现的错误的冲动;(7)防止试剂盒分配中对治疗分配的无意暴露;(8)检查一组研究药物试剂盒,以检测药物包装和标签中的错误。

局限性

尽管我们对有文献记录的随机化错误进行了文献检索,但我们提供的示例和由此产生的建议主要基于我们在工业赞助临床试验中的经验。我们不知道我们的经验有多具有代表性,也不知道我们所看到的那种类型的错误有多常见。

结论

我们的经验强调了在试验之前和进行期间验证治疗分配过程完整性的重要性。临床试验 2010;7:235-245. http://ctj.sagepub.com.

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