Literature DB >> 23412832

The validity of sequence symmetry analysis (SSA) for adverse drug reaction signal detection.

Izyan A Wahab1, Nicole L Pratt, Michael D Wiese, Lisa M Kalisch, Elizabeth E Roughead.   

Abstract

PURPOSE: To determine the validity of sequence symmetry analysis (SSA) method to detect adverse drug reactions from an administrative claims database.
METHODS: Published randomised controlled trials (RCTs) of 19 medicines were identified through search databases, product information (PI) or the US Food and Drug Administration Web site. All adverse events (AEs) in the RCTs and the PI for the medicines were extracted. AEs were considered 'gold standard positive events' if they were reported as being statistically significant events in adequately powered RCTs. The remaining AEs were considered 'gold standard negative events' if the event was not listed as an AE in the PI for that medicine or any other medicine in its class. Indicators of AEs were identified by consensus from two clinical researchers. SSA was run for each medicine-indicator pair using four different time windows: 3, 6, 9 and 12 months.
RESULTS: A total of 120 randomised placebo controlled trials were reviewed for the 19 tested medicines. A total of 165 medicine-indicator pairs (44 positive and 121 negative events) were identified and tested by SSA. At the 12-month time window, the sensitivity, specificity, positive and negative predictive values of SSA were 61% (95%CI 0.46-0.74), 93% (95%CI 0.87-0.96), 77% (95%CI 0.61-0.88) and 87% (95%CI 0.80-0.92), respectively. Using a 3-month time window, the SSA had a lower sensitivity (52%).
CONCLUSIONS: The SSA technique was found to have moderate sensitivity and high specificity for detecting ADRs. These results suggest that SSA is a potential tool for detecting ADRs using administrative claims data that could complement existing pharmacosurveillance methods.
Copyright © 2013 John Wiley & Sons, Ltd.

Mesh:

Year:  2013        PMID: 23412832     DOI: 10.1002/pds.3417

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  29 in total

1.  Sequence Symmetry Analysis as a Signal Detection Tool for Potential Heart Failure Adverse Events in an Administrative Claims Database.

Authors:  Izyan A Wahab; Nicole L Pratt; Lisa Kalisch Ellett; Elizabeth E Roughead
Journal:  Drug Saf       Date:  2016-04       Impact factor: 5.606

2.  Comparing time to adverse drug reaction signals in a spontaneous reporting database and a claims database: a case study of rofecoxib-induced myocardial infarction and rosiglitazone-induced heart failure signals in Australia.

Authors:  Izyan A Wahab; Nicole L Pratt; Lisa M Kalisch; Elizabeth E Roughead
Journal:  Drug Saf       Date:  2014-01       Impact factor: 5.606

Review 3.  Sequence symmetry analysis in pharmacovigilance and pharmacoepidemiologic studies.

Authors:  Edward Chia-Cheng Lai; Nicole Pratt; Cheng-Yang Hsieh; Swu-Jane Lin; Anton Pottegård; Elizabeth E Roughead; Yea-Huei Kao Yang; Jesper Hallas
Journal:  Eur J Epidemiol       Date:  2017-07-11       Impact factor: 8.082

4.  Increased risk of mycotic infections associated with sodium-glucose co-transporter 2 inhibitors: a prescription sequence symmetry analysis.

Authors:  Sruthi Adimadhyam; Glen T Schumock; Gregory S Calip; Daphne E Smith Marsh; Brian T Layden; Todd A Lee
Journal:  Br J Clin Pharmacol       Date:  2018-11-08       Impact factor: 4.335

5.  Hypothesis-free screening of large administrative databases for unsuspected drug-outcome associations.

Authors:  Jesper Hallas; Shirley V Wang; Joshua J Gagne; Sebastian Schneeweiss; Nicole Pratt; Anton Pottegård
Journal:  Eur J Epidemiol       Date:  2018-03-31       Impact factor: 8.082

6.  An Automated System Combining Safety Signal Detection and Prioritization from Healthcare Databases: A Pilot Study.

Authors:  Mickael Arnaud; Bernard Bégaud; Frantz Thiessard; Quentin Jarrion; Julien Bezin; Antoine Pariente; Francesco Salvo
Journal:  Drug Saf       Date:  2018-04       Impact factor: 5.606

7.  Using the Symmetry Analysis Design to Screen for Adverse Effects of Non-vitamin K Antagonist Oral Anticoagulants.

Authors:  Maja Hellfritzsch; Lotte Rasmussen; Jesper Hallas; Anton Pottegård
Journal:  Drug Saf       Date:  2018-07       Impact factor: 5.606

8.  The Uncertainty of the Association Between Proton Pump Inhibitor Use and the Risk of Dementia: Prescription Sequence Symmetry Analysis Using a Korean Healthcare Database Between 2002 and 2013.

Authors:  Sun-Kyeong Park; Yeon-Hee Baek; Nicole Pratt; Lisa Kalisch Ellett; Ju-Young Shin
Journal:  Drug Saf       Date:  2018-06       Impact factor: 5.606

9.  Association of statin use with sleep disturbances: data mining of a spontaneous reporting database and a prescription database.

Authors:  Mitsutaka Takada; Mai Fujimoto; Kohei Yamazaki; Masashi Takamoto; Kouichi Hosomi
Journal:  Drug Saf       Date:  2014-06       Impact factor: 5.606

10.  Metabolic events associated with the use of antipsychotics in children, adolescents and young adults: a multinational sequence symmetry study.

Authors:  Kenneth K C Man; Shih-Chieh Shao; Nathorn Chaiyakunapruk; Piyameth Dilokthornsakul; Kiyoshi Kubota; Junqing Li; Nobuhiro Ooba; Nicole Pratt; Anton Pottegård; Lotte Rasmussen; Elizabeth E Roughead; Ju-Young Shin; Chien-Chou Su; Ian C K Wong; Yea-Huei Kao Yang; Edward Chia-Cheng Lai
Journal:  Eur Child Adolesc Psychiatry       Date:  2020-11-13       Impact factor: 4.785

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