The aims of the study were to 1) determine if a plasma oxypurinol concentration-response relationship or an allopurinol dose-response relationship best predicts the dose requirements of allopurinol in the treatment of gout; and, 2) to construct a nomogram for calculating the optimum maintenance dose of allopurinol to achieve target serum urate (SU) concentrations.
A non-linear regression analysis was used to examine the plasma oxypurinol concentration- and allopurinol dose-response relationships with serum urate. In 81 patients (205 samples), creatinine clearance (CLCR ), concomitant diuretic use and SU concentrations before (UP ) and during (UT ) treatment were monitored across a range of allopurinol doses (D, 50-700 mg daily). Plasma concentrations of oxypurinol (C) were measured in 47 patients (98 samples). Models (n = 47 patients) and predictions from each relationship were compared using F-tests, r(2) values and paired t-tests. The best model was used to construct a nomogram.
The final plasma oxypurinol concentration-response relationship (UT = UP - C * (UP - UR )/(ID50 + C), r(2) = 0.64) and allopurinol dose-response relationship (UT = UP - D * (UP - UR )/(ID50 + D),r(2) = 0.60) did not include CLCR or diuretic use as covariates. There was no difference (P = 0.87) between the predicted SU concentrations derived from the oxypurinol concentration- and allopurinol dose-response relationships. The nomogram constructed using the allopurinol dose-response relationship for all recruited patients (n = 81 patients) required pre-treatment SU as the predictor of allopurinol maintenance dose.
Plasma oxypurinol concentrations, CLCR and diuretic status are not required to predict the maintenance dose of allopurinol. Using the nomogram, the maintenance dose of allopurinol estimated to reach target concentrations can be predicted from UP .
Pharmacology, Toxicology and Pharmaceutical Science
6
19%
Environmental Science
1
3%
Biochemistry, Genetics and Molecular Biology
1
3%
Nursing and Health Professions
1
3%
Other
3
9%
Unknown
13
41%
Attention Score in Context
Attention Score in Context
This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 April 2024.
All research outputs
#3,252,925
of 34,217,933 outputs
Outputs from British Journal of Clinical Pharmacology
#857
of 6,948 outputs
Outputs of similar age
#45,053
of 361,388 outputs
Outputs of similar age from British Journal of Clinical Pharmacology
#12
of 41 outputs
Altmetric has tracked 34,217,933 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,948 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 361,388 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
