Appl Clin Inform 2014; 05(01): 206-218
DOI: 10.4338/ACI-2013-11-RA-0097
Research Article
Schattauer GmbH

Simulating adverse event spontaneous reporting systems as preferential attachment networks

Application to the Vaccine Adverse Event Reporting System
J. Scott
1  Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, U. S. Food and Drug Administration
,
T. Botsis
1  Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, U. S. Food and Drug Administration
2  Department of Computer Science, University of Tromsø, Tromsø, Norway
,
R. Ball
1  Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, U. S. Food and Drug Administration
› Author Affiliations
Further Information

Correspondence to:

John Scott
Office of Biostatistics and Epidemiology, FDA/CBER
1401 Rockville Pike, HFM-215
Rockville, MD 20852
301–827–4608 (voice)
301–827–5218 (fax)

Publication History

received: 12 November 2013

accepted: 13 January 2014

Publication Date:
20 December 2017 (online)

 

Summary

Background: Spontaneous Reporting Systems [SRS] are critical tools in the post-licensure evaluation of medical product safety. Regulatory authorities use a variety of data mining techniques to detect potential safety signals in SRS databases. Assessing the performance of such signal detection procedures requires simulated SRS databases, but simulation strategies proposed to date each have limitations.

Objective: We sought to develop a novel SRS simulation strategy based on plausible mechanisms for the growth of databases over time.

Methods: We developed a simulation strategy based on the network principle of preferential attachment. We demonstrated how this strategy can be used to create simulations based on specific databases of interest, and provided an example of using such simulations to compare signal detection thresholds for a popular data mining algorithm.

Results: The preferential attachment simulations were generally structurally similar to our targeted SRS database, although they had fewer nodes of very high degree. The approach was able to generate signal-free SRS simulations, as well as mimicking specific known true signals. Explorations of different reporting thresholds for the FDA Vaccine Adverse Event Reporting System suggested that using proportional reporting ratio [PRR] > 3.0 may yield better signal detection operating characteristics than the more commonly used PRR > 2.0 threshold.

Discussion: The network analytic approach to SRS simulation based on the principle of preferential attachment provides an attractive framework for exploring the performance of safety signal detection algorithms. This approach is potentially more principled and versatile than existing simulation approaches.

Conclusion: The utility of network-based SRS simulations needs to be further explored by evaluating other types of simulated signals with a broader range of data mining approaches, and comparing network-based simulations with other simulation strategies where applicable.

Citation: Scott J, Botsis T, Ball R. Simulating adverse event spontaneous reporting systems as preferential attachment networks: Application to the Vaccine Adverse Event Reporting System. Appl Clin Inf 2014; 5: 206–218 http://dx.doi.org/10.4338/ACI-2013-11-RA-0097


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Conflict of Interest

The authors have no conflicts of interest to disclose.


Correspondence to:

John Scott
Office of Biostatistics and Epidemiology, FDA/CBER
1401 Rockville Pike, HFM-215
Rockville, MD 20852
301–827–4608 (voice)
301–827–5218 (fax)