| Title |
Assessment of the Utility of Social Media for Broad-Ranging Statistical Signal Detection in Pharmacovigilance: Results from the WEB-RADR Project
|
|---|---|
| Published in |
Drug Safety, July 2018
|
| DOI | 10.1007/s40264-018-0699-2 |
| Pubmed ID | |
| Authors |
Ola Caster, Juergen Dietrich, Marie-Laure Kürzinger, Magnus Lerch, Simon Maskell, G. Niklas Norén, Stéphanie Tcherny-Lessenot, Benoit Vroman, Antoni Wisniewski, John van Stekelenborg |
| Abstract |
Social media has been proposed as a possibly useful data source for pharmacovigilance signal detection. This study primarily aimed to evaluate the performance of established statistical signal detection algorithms in Twitter/Facebook for a broad range of drugs and adverse events. Performance was assessed using a reference set by Harpaz et al., consisting of 62 US Food and Drug Administration labelling changes, and an internal WEB-RADR reference set consisting of 200 validated safety signals. In total, 75 drugs were studied. Twitter/Facebook posts were retrieved for the period March 2012 to March 2015, and drugs/events were extracted from the posts. We retrieved 4.3 million and 2.0 million posts for the WEB-RADR and Harpaz drugs, respectively. Individual case reports were extracted from VigiBase for the same period. Disproportionality algorithms based on the Information Component or the Proportional Reporting Ratio and crude post/report counting were applied in Twitter/Facebook and VigiBase. Receiver operating characteristic curves were generated, and the relative timing of alerting was analysed. Across all algorithms, the area under the receiver operating characteristic curve for Twitter/Facebook varied between 0.47 and 0.53 for the WEB-RADR reference set and between 0.48 and 0.53 for the Harpaz reference set. For VigiBase, the ranges were 0.64-0.69 and 0.55-0.67, respectively. In Twitter/Facebook, at best, 31 (16%) and four (6%) positive controls were detected prior to their index dates in the WEB-RADR and Harpaz references, respectively. In VigiBase, the corresponding numbers were 66 (33%) and 17 (27%). Our results clearly suggest that broad-ranging statistical signal detection in Twitter and Facebook, using currently available methods for adverse event recognition, performs poorly and cannot be recommended at the expense of other pharmacovigilance activities. |
X Demographics
The data shown below were collected from the profiles of 33 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 10 | 30% |
| Colombia | 3 | 9% |
| United Kingdom | 2 | 6% |
| Sweden | 2 | 6% |
| United States | 2 | 6% |
| Belgium | 1 | 3% |
| Greece | 1 | 3% |
| Spain | 1 | 3% |
| Norway | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 10 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 31 | 94% |
| Scientists | 2 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 77 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 14% |
| Student > Master | 11 | 14% |
| Student > Bachelor | 10 | 13% |
| Researcher | 6 | 8% |
| Student > Doctoral Student | 3 | 4% |
| Other | 9 | 12% |
| Unknown | 27 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Pharmacology, Toxicology and Pharmaceutical Science | 12 | 16% |
| Medicine and Dentistry | 9 | 12% |
| Computer Science | 7 | 9% |
| Business, Management and Accounting | 5 | 6% |
| Nursing and Health Professions | 5 | 6% |
| Other | 8 | 10% |
| Unknown | 31 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 21. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 November 2023.
All research outputs
#1,781,281
of 25,657,205 outputs
Outputs from Drug Safety
#167
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Outputs of similar age
#35,794
of 341,533 outputs
Outputs of similar age from Drug Safety
#4
of 16 outputs
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