A Maximized Sequential Probability Ratio Test for Drug and Vaccine Safety Surveillance
A Maximized Sequential Probability Ratio Test for Drug and Vaccine Safety Surveillance
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DOI：
10.1080/07474946.2011.539924
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发表时间：
2011-01-01
影响因子：
0.8
通讯作者：
Platt, Richard
中科院分区：
文献类型：
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作者：
Kulldorff, Martin;Davis, Robert L.;Platt, Richard
由于罕见但严重的不良事件，药品和疫苗有时会被诸如美国食品和药物管理局（FDA）等政府机构或生产制药公司从市场上撤回。在其他情况下，一种药物可能总体上是安全的，但会增加某些亚人群（如孕妇或心脏病患者）发生严重不良事件的风险。由于样本量和选定的研究人群有限，在药物被批准普遍使用之前进行的三期试验中，通常不可能发现罕见的不良事件。因此，重要的是利用例如医疗保险索赔数据，进行批准后的药物安全监测。在这样的监测中，目标应该是尽可能早地发现严重的不良事件，而不会有太多的假警报，然后很自然地使用连续或接近连续的顺序测试程序，每天或每周重新评估数据。在本文中，我们首先证明了用于连续监测的Wald经典序列概率比检验（SPRT）对替代假设规范中所要求的相对风险的选择非常敏感，这使得它难以用于药物和疫苗安全监测。相反，我们建议使用基于复合替代假设的最大化序列概率比检验（MaxSPRT），它在一系列相对风险中都很有效。我们举例说明了这种方法在疫苗安全监测中的应用，并将其与经典的SPRT进行了比较。提供了MaxSPRT的临界值表，涵盖了与疫苗和药物安全监测相关的大多数参数选择。这些临界值是根据精确的数值计算得出的。我们还计算了统计功率，直到零假设被拒绝的预期时间，以及监视的平均长度。
Because of rare but serious adverse events, pharmaceutical drugs and vaccines are sometimes withdrawn from the market, either by a government agency such as the Food and Drug Administration (FDA) in the United States or by the manufacturing pharmaceutical company. In other cases, a drug may be generally safe but increase the risk for serious adverse events for certain subpopulations such as pregnant women or people with heart problems. Due to limited sample size and selected study populations, rare adverse events are often impossible to detect during phase 3 trials conducted before the drug is approved for general use. It is then important to conduct post-approval drug safety surveillance, using, for example, health insurance claims data. In such surveillance, the goal should be to detect serious adverse events as early as possible without too many false alarms, and it is then natural to use a continuous or near-continuous sequential test procedure that reevaluates the data on a daily or weekly basis.In this article, we first show that Wald's classical sequential probability ratio test (SPRT) for continuous surveillance is very sensitive to the choice of relative risk required in the specification of the alternative hypothesis, making it difficult to use for drug and vaccine safety surveillance. We instead propose the use of a maximized sequential probability ratio test (MaxSPRT) based on a composite alternative hypothesis, which works well across a range of relative risks. We illustrate the use of this method on vaccine safety surveillance and compare it with the classical SPRT.A table of critical values for the MaxSPRT is provided, covering most parameter choices relevant for vaccine and drug safety surveillance. The critical values are based on exact numerical calculations. We also calculate the statistical power, the expected time until the null hypothesis is rejected, and the average length of surveillance.