| Title |
HLA-B*57
|
|---|---|
| Published in |
Pharmacogenetics and Genomics, August 2016
|
| DOI | 10.1097/fpc.0000000000000229 |
| Pubmed ID | |
| Authors |
Cristina Ruiz-Iruela, Núria Padullés-Zamora, Daniel Podzamczer-Palter, Arnald Alonso-Pastor, Beatriz Candás-Estébanez, Pedro Alía-Ramos, Ariadna Padró-Miquel |
| Abstract |
Most of the cost-effectiveness analyses are based on estimations to make decisions on the future implementation of a test. However, the model should be verified with real data to prove that previous estimations have been successfully fulfilled. To study the economic impact of the systematic HLA-B*57:01 genotyping in preventing hypersensitivity reactions (HSRs) in the patient population of a tertiary-care hospital treated with abacavir (ABC) using retrospective data of 5 years of experience. A retrospective study was carried out with two cohorts including 780 and 473 patients before and after the implementation of the systematic HLA-B*57:01 genotyping before ABC treatment. Cost-effectiveness analysis was carried out by the parameter 'cost per HSR avoided'. The clinical utility of the test was verified by evaluating the differences in HSR incidence between both cohorts. Finally, a sensitivity analysis including all variables was carried out. In the population studied, systematic genotyping represents an additional cost of &OV0556;306 per HSR avoided. In the sensitivity analysis, pharmacological therapy cost is the major influencing factor found in the estimation of the 'cost per HSR avoided'. In terms of clinical utility, the incidence ratio was 0.040 (95% confidence interval 0.0009-0.2399) and statistically significant differences were found between both groups (P=1.40×10). Retrospective data from 5 years of experience have confirmed the cost-effectiveness of the systematic genotyping in candidate patients for ABC therapy, and have shown that cost-effectiveness is a dynamic parameter closely linked to allele prevalence and pharmacological therapy costs. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | 50% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 50% |
| Scientists | 1 | 25% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 30 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 10% |
| Student > Postgraduate | 3 | 10% |
| Researcher | 3 | 10% |
| Student > Ph. D. Student | 3 | 10% |
| Student > Doctoral Student | 2 | 7% |
| Other | 7 | 23% |
| Unknown | 9 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 33% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 13% |
| Biochemistry, Genetics and Molecular Biology | 3 | 10% |
| Agricultural and Biological Sciences | 3 | 10% |
| Business, Management and Accounting | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 9 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 22 May 2016.
All research outputs
#15,170,530
of 25,377,790 outputs
Outputs from Pharmacogenetics and Genomics
#723
of 1,236 outputs
Outputs of similar age
#215,650
of 381,031 outputs
Outputs of similar age from Pharmacogenetics and Genomics
#6
of 15 outputs
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