Evidence map›Paper›PMID 26798053›Full record

ArticleDrug safety2016

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

Izyan A Wahab, Nicole L Pratt, Lisa Kalisch Ellett, Elizabeth E Roughead

Abstract read
PubMed Publisher
In one paragraph

Article in Drug safety, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
2.6field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Izyan A WahabFaculty of Pharmacy, Cyberjaya University College of Medical Sciences, 3410, Jalan Teknokrat 3, Cyber 4, 63000, Cyberjaya, Selangor, Malaysia. izyan@cybermed.edu.my.
Nicole L PrattSchool of Pharmacy and Medical Sciences, Quality Use of Medicines and Pharmacy Research Centre, Sansom Institute, University of South Australia, Adelaide, SA, Australia.
Lisa Kalisch EllettSchool of Pharmacy and Medical Sciences, Quality Use of Medicines and Pharmacy Research Centre, Sansom Institute, University of South Australia, Adelaide, SA, Australia.
Elizabeth E RougheadSchool of Pharmacy and Medical Sciences, Quality Use of Medicines and Pharmacy Research Centre, Sansom Institute, University of South Australia, Adelaide, SA, Australia.
University of South Australia · AUUniversity of Cyberjaya · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe potential for routine sequence symmetry analysis (SSA) signal detection in health claims databases to detect new safety signals of medicines is unknown.

objectiveOur objective was to assess the potential utility of SSA as a signal detection tool in health claims data for detecting medicines with potential heart failure (HF) adverse event signals.

methodsWe applied the SSA method to all subsidized single-ingredient medicines in Australia. The source of data was the Australian Government Department of Veterans' Affairs (DVA) administrative claims database using data collected between 2002 and 2011. We used first ever HF hospitalization and frusemide initiation as indicators for HF. A signal was considered to be present if the lower limit of the 95 % confidence interval for the adjusted sequence ratio was greater than one. To identify potential new signals of HF, we excluded medicines where HF or edema was listed in the product information (PI) of that medicine or for any other medicine in the same class. We also excluded medicines that were used in HF treatment and medicines indicated for diseases that may contribute to the development of HF.

resultsWe tested 691 medicines. HF signals were detected for 12 % (80/691) using the hospitalization event and 22 % (153/691) using frusemide initiation. Among medicines that did not have HF listed in the PI, SSA found 11 % (44/397) associated with HF hospitalization and 15 % (60/397) associated with frusemide initiation. Of the medicines tested in which no other medicine in the same class had HF or edema in the PI, and where the medicine was not indicated for a disease that is a risk factor for HF, potential new signals were generated for 2-3 % of these medicines tested (12 of 397 medicines using HF hospitalization and 9 of 397 medicines using frusemide initiation).

conclusionSSA generated potential new signals of HF for some anti-glaucoma and anti-dyspepsia medicines. For some of the potential signals, the event is biologically plausible and some have pre-marketing and post-marketing case reports to support the finding. Confirmation of these signals using cohort studies is required.

Indexed as

Administrative Claims, HealthcareAdverse Drug Reaction Reporting SystemsDatabases, PharmaceuticalHeart FailureHumans

Identifiers

PMID26798053
OpenAlexW2281081990

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.