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A new self-controlled case series method for analyzing spontaneous reports of adverse events after vaccination. | LitMetric

AI Article Synopsis

Article Abstract

In this paper, we propose new methods for analyzing cases of vaccine adverse events spontaneously reported to a surveillance database. The methods use the self-controlled case series approach, extended in several ways with parametric and nonparametric assumptions to account for the specific features of the data (large amount of underreporting and variation of reporting with time since vaccination). This work was motivated by the documented risk of intussusception after RotaShield vaccination (Wyeth-Lederle Vaccines, Radnor, Pennsylvania) and used worldwide spontaneous reports of intussusception occurring after Rotarix vaccination (GlaxoSmithKline Biologics, Research Triangle Park, North Carolina) collected between January 2004 and February 2010. The estimated risk during the 3- to 7-day period after vaccination was approximately 5 times higher after dose 1 of Rotarix than after dose 2, which is similar to published findings on the same topic. We undertook a large simulation study to evaluate the performance of the method in different scenarios, including its robustness to different sample sizes and time-dependent reporting functions. The bias was generally small, the type I error rate was correctly controlled, and the power to detect a risk ratio of 4 was satisfactory, provided that the sample size was over 100. The proposed methods are an effective way to explore and quantify vaccine safety signals from spontaneous reports.

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http://dx.doi.org/10.1093/aje/kwt128DOI Listing

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