ArticlePharmacogenomics2009
Predicting response to short-acting bronchodilator medication using Bayesian networks.
Article in Pharmacogenomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.
- Opportunities and challenges with artificial intelligence in allergy and immunology: a bibliometric study.Frontiers in medicine · 2025Pooled it
- Pharmacogenomic characterization of gemcitabine response--a framework for data integration to enable personalized medicine.Pharmacogenetics and genomics · 2014Trial
- Genome-wide association for smoking cessation success in a trial of precessation nicotine replacement.Molecular medicine (Cambridge, Mass.)Trial
- Artificial intelligence in pediatric allergy research.European journal of pediatrics · 2024Review
- Assessment of genetic factor and depression interactions for asthma symptom severity in cohorts of childhood and elderly asthmatics.Experimental & molecular medicine · 2018Article
- Asthma Pharmacogenomics: 2015 Update.Current allergy and asthma reports · 2015Review
- Asthma pharmacogenetics and the development of genetic profiles for personalized medicine.Pharmacogenomics and personalized medicine · 2015Review
- Gene-based association identifies SPATA13-AS1 as a pharmacogenomic predictor of inhaled short-acting beta-agonist response in multiple population groups.The pharmacogenomics journal · 2014Article
- Pharmacogenetics: implications of race and ethnicity on defining genetic profiles for personalized medicine.The Journal of allergy and clinical immunology · 2014Review
- Predicting inhaled corticosteroid response in asthma with two associated SNPs.The pharmacogenomics journal · 2013Article
- Integrative systems biology approaches in asthma pharmacogenomics.Pharmacogenomics · 2012Review
- The pharmacogenetics and pharmacogenomics of asthma therapy.The pharmacogenomics journal · 2011Review
- Systems biology data analysis methodology in pharmacogenomics.Pharmacogenomics · 2011Review
- The role of pharmacogenomics in improving the management of asthma.The Journal of allergy and clinical immunology · 2010Review
- Using systems approaches to address challenges for clinical implementation of pharmacogenomics.Wiley interdisciplinary reviews. Systems biology and medicineReview
- Marco Ramoni: an appreciation of academic achievement.Journal of the American Medical Informatics Association : JAMIAArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
aimsBronchodilator response tests measure the effect of beta(2)-agonists, the most commonly used short-acting reliever drugs for asthma. We sought to relate candidate gene SNP data with bronchodilator response and measure the predictive accuracy of a model constructed with genetic variants. MATERIALS &
methodsBayesian networks, multivariate models that are able to account for simultaneous associations and interactions among variables, were used to create a predictive model of bronchodilator response using candidate gene SNP data from 308 Childhood Asthma Management Program Caucasian subjects.
resultsThe model found that 15 SNPs in 15 genes predict bronchodilator response with fair accuracy, as established by a fivefold cross-validation area under the receiver-operating characteristic curve of 0.75 (standard error: 0.03).
conclusionBayesian networks are an attractive approach to analyze large-scale pharmacogenetic SNP data because of their ability to automatically learn complex models that can be used for the prediction and discovery of novel biological hypotheses.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.