PMID- 23412832
OWN - NLM
STAT- MEDLINE
DCOM- 20131112
LR  - 20220330
IS  - 1099-1557 (Electronic)
IS  - 1053-8569 (Linking)
VI  - 22
IP  - 5
DP  - 2013 May
TI  - The validity of sequence symmetry analysis (SSA) for adverse drug reaction signal 
      detection.
PG  - 496-502
LID - 10.1002/pds.3417 [doi]
AB  - 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.
CI  - Copyright (c) 2013 John Wiley & Sons, Ltd.
FAU - Wahab, Izyan A
AU  - Wahab IA
AD  - School of Pharmacy and Medical Sciences, Quality Use of Medicines and Pharmacy 
      Research Centre, Sansom Institute, University of South Australia, Adelaide, South 
      Australia, Australia.
FAU - Pratt, Nicole L
AU  - Pratt NL
FAU - Wiese, Michael D
AU  - Wiese MD
FAU - Kalisch, Lisa M
AU  - Kalisch LM
FAU - Roughead, Elizabeth E
AU  - Roughead EE
LA  - eng
PT  - Journal Article
PT  - Validation Study
DEP - 20130214
PL  - England
TA  - Pharmacoepidemiol Drug Saf
JT  - Pharmacoepidemiology and drug safety
JID - 9208369
SB  - IM
MH  - Adverse Drug Reaction Reporting Systems/*statistics & numerical data
MH  - Databases, Factual/*statistics & numerical data
MH  - *Drug-Related Side Effects and Adverse Reactions
MH  - Humans
MH  - *Pharmacovigilance
MH  - Predictive Value of Tests
MH  - Randomized Controlled Trials as Topic
MH  - Sensitivity and Specificity
MH  - Time Factors
MH  - United States
MH  - United States Food and Drug Administration
EDAT- 2013/02/16 06:00
MHDA- 2013/11/13 06:00
CRDT- 2013/02/16 06:00
PHST- 2012/09/27 00:00 [received]
PHST- 2012/12/19 00:00 [revised]
PHST- 2013/01/11 00:00 [accepted]
PHST- 2013/02/16 06:00 [entrez]
PHST- 2013/02/16 06:00 [pubmed]
PHST- 2013/11/13 06:00 [medline]
AID - 10.1002/pds.3417 [doi]
PST - ppublish
SO  - Pharmacoepidemiol Drug Saf. 2013 May;22(5):496-502. doi: 10.1002/pds.3417. Epub 
      2013 Feb 14.