Evidence map›Paper›PMID 12071780›Full record

ArticleDrug safety2002

Signal generation in the New Zealand Intensive Medicines Monitoring Programme: a combined clinical and statistical approach.

David M Coulter

Abstract read
PubMed Publisher
In one paragraph

Article in Drug safety, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

  1. Article
  2. Review
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  5. Review
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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

1 author.

David M CoulterNew Zealand Intensive Medicines Monitoring Programme, Department of Preventive and Social Medicine, School of Medicine, University of Otago, Dunedin, New Zealand. david.coulter@stonebow.otago.ac.nz

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The New Zealand Intensive Medicines Monitoring Programme (IMMP) undertakes prospective observational cohort studies on selected new drugs in the early postmarketing period using prescription-event monitoring (PEM) methodology with the purpose of identifying signals of previously unrecognised ADRs and establishing risk profiles for each drug. Events are reviewed by a physician and a relationship is established between each event and the drug. The events are then sorted into reactions and incidents. The latter are used to assist signal detection and control for bias. Rates for reports, reactions and incidents are used to assess the adequacy of reporting, signal detection and identification of confounders. Most signals are identified by clinical evaluation of the reports at a stage when statistical analyses are unlikely to have the power to detect them with confidence. The incident group is used for signal detection and controlling for bias. A low reporting rate indicates that certain types of event are unlikely to be reported. A systematic review of the original case reports at the site of collection provides the best opportunity for early signal detection. More resources need to be invested in the training and support of clinical evaluators. Categorising events into reactions and incidents gives added value to the data. Rates of reporting should be quoted with the results of cohort studies to facilitate assessment of their power to detect new signals.

Indexed as

Adverse Drug Reaction Reporting SystemsCohort StudiesData Interpretation, StatisticalDrug InteractionsDrug MonitoringDrug PrescriptionsElectronic Data ProcessingHumansNew ZealandProduct Surveillance, PostmarketingRisk Assessment

Identifiers

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.