Evidence map›Paper›PMID 23590252›Full record

Trial reportBritish journal of clinical pharmacology2013

Understanding the dose-response relationship of allopurinol: predicting the optimal dosage.

Garry G Graham, Diluk R W Kannangara, Sophie L Stocker, Ian Portek, Kevin D Pile, Praveen L Indraratna, Indira Datta, Kenneth M Williams, Richard O Day

Open access · bronzeAbstract readClinical Trial
In one paragraph

Trial report in British journal of clinical pharmacology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.6field-weighted citation impact, top 11% 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

20 citing papers in PubMed, 41 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Honorary Professor Garry Graham.Inflammopharmacology · 2021
    Article
  10. Better outcomes for patients with gout.Inflammopharmacology · 2020
    Article
  11. Review
  12. Individualising the dose of allopurinol in patients with gout.British journal of clinical pharmacology · 2017
    Observational
  13. Review
  14. Article
  15. Review: Gout: A Roadmap to Approaches for Improving Global Outcomes.Arthritis & rheumatology (Hoboken, N.J.) · 2017
    Review
  16. Article
  17. The management of gout.Australian prescriber · 2016
    Review
  18. Predicting allopurinol response in patients with gout.British journal of clinical pharmacology · 2016
    Article
  19. Review
  20. Editors' pick 2013.British journal of clinical pharmacology · 2014
    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

9 authors at 4 institutions in 2 countries.

Garry G GrahamDepartment of Clinical Pharmacology & Toxicology, St Vincent's Hospital, NSW, Australia; School of Medical Sciences, University of New South Wales, NSW, Australia.
Diluk R W Kannangara
Sophie L Stocker
Ian Portek
Kevin D Pile
Praveen L Indraratna
Indira Datta
Kenneth M Williams
Richard O Day
St Vincent's Hospital · AUCamden and Campbelltown Hospitals · AUSt George's Hospital · GBUNSW Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsThe aim of the study was to identify and quantify factors that control the plasma concentrations of urate during allopurinol treatment and to predict optimal doses of allopurinol.

methodsPlasma concentrations of urate and creatinine (112 samples, 46 patients) before and during treatment with various doses of allopurinol (50-600 mg daily) were monitored. Non-linear and multiple linear regression equations were used to examine the relationships between allopurinol dose (D), creatinine clearance (CLcr) and plasma concentrations of urate before (UP) and during treatment with allopurinol (UT).

resultsPlasma concentrations of urate achieved during allopurinol therapy were dependent on the daily dose of allopurinol and the plasma concentration of urate pre-treatment. The non-linear equation: UT = (1 - D/(ID50 + D)) × (UP - UR) + UR , fitted the data well (r(2) = 0.74, P < 0.0001). The parameters and their best fit values were: daily dose of allopurinol reducing the inhibitable plasma urate by 50% (ID50 = 226 mg, 95% CI 167, 303 mg), apparent resistant plasma urate (UR = 0.20 mmol l(-1), 95 % CI 0.14, 0.25 mmol l(-1)). Incorporation of CLcr did not significantly improve the fit (P = 0.09).

conclusionsA high baseline plasma urate concentration requires a high dose of allopurinol to reduce plasma urate below recommended concentrations. This dose is dependent on only the pre-treatment plasma urate concentration and is not influenced by CLcr .

Indexed as

AdolescentAdultAgedAged, 80 and overAllopurinolCreatinineDose-Response Relationship, DrugGout SuppressantsHumansLinear ModelsMiddle AgedPredictive Value of TestsProspective StudiesRetrospective StudiesUric AcidYoung AdultAllopurinolCreatinineGout SuppressantsUric Acidallopurinolcreatinine clearancegouturateuric acid

Identifiers

PMID23590252
PMCPMC3845316
OpenAlexW1526688071

What OpenQuestion holds

Textmetadata
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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.