Evidence map›Paper›PMID 19539050›Full record

ArticleJournal of biomedical informatics2009

Computing with evidence Part II: An evidential approach to predicting metabolic drug-drug interactions.

Richard Boyce, Carol Collins, John Horn, Ira Kalet

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Adding evidence type representation to DIDEO.CEUR workshop proceedings · 2016
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Informatics confronts drug-drug interactions.Trends in pharmacological sciences · 2013
    Review
  12. Article
  13. Article
  14. Article
  15. High-priority drug-drug interactions for use in electronic health records.Journal of the American Medical Informatics Association : JAMIA
    Article
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.

Richard BoyceDepartment of Biomedical Informatics, University of Pittsburgh, VALE M, PA 15260, USA. boycerd@upmc.edu
Carol Collins
John Horn
Ira Kalet

Funding

University of Washington Biomedical Informatics and Data Science Research Training ProgramT15LM007442 · NLM · UNIVERSITY OF WASHINGTON · PI JOHN H. GENNARI, Andrea L. Hartzler · 2002 to 2026
$19.6M
A Resource for Biomedical Ontologies and Knowledge BasesP41LM007885 · NLM · STANFORD UNIVERSITY · PI MUSEN, MARK A · 2003 to 2010
$6.4M
NLM NIH HHS LM007885NLM NIH HHS P41 LM007885NLM NIH HHS T15 LM007442NLM NIH HHS T15 LM07442
6 · The paper itself

Abstract

We describe a novel experiment that we conducted with the Drug Interaction Knowledge-base (DIKB) to determine which combinations of evidence enable a rule-based theory of metabolic drug-drug interactions to make the most optimal set of predictions. The focus of the experiment was a group of 16 drugs including six members of the HMG-CoA-reductase inhibitor family (statins). The experiment helped identify evidence-use strategies that enabled the DIKB to predict significantly more interactions present in a validation set than the most rigorous strategy developed by drug experts with no loss of accuracy. The best-performing strategies included evidence types that would normally be of lesser predictive value but that are often more accessible than more rigorous types. Our experimental methods represent a new approach to leveraging the available scientific evidence within a domain where important evidence is often missing or of questionable value for supporting important assertions.

Indexed as

Drug InteractionsPharmacokineticsAlgorithmsArea Under CurveComputational BiologyDatabases, FactualEvidence-Based MedicineHumansHydroxymethylglutaryl-CoA Reductase InhibitorsMedical InformaticsPharmaceutical PreparationsReproducibility of ResultsHydroxymethylglutaryl-CoA Reductase InhibitorsPharmaceutical Preparations

Identifiers

PMID19539050
PMCPMC2783683

What OpenQuestion holds

Textmetadata
LicenceTDM
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.