Prediction of Thiopurine Metabolite Levels Based on Haematological and Biochemical Parameters
Jazyk angličtina Země Spojené státy americké Médium print
Typ dokumentu hodnotící studie, časopisecké články, práce podpořená grantem
PubMed
31568041
DOI
10.1097/mpg.0000000000002436
PII: 00005176-201910000-00018
Knihovny.cz E-zdroje
- MeSH
- adherence k farmakoterapii * MeSH
- biologické modely MeSH
- dítě MeSH
- erytrocyty metabolismus MeSH
- idiopatické střevní záněty krev farmakoterapie metabolismus MeSH
- imunosupresiva aplikace a dávkování farmakokinetika terapeutické užití MeSH
- lidé MeSH
- merkaptopurin aplikace a dávkování analogy a deriváty farmakokinetika terapeutické užití MeSH
- mladiství MeSH
- monitorování léčiv MeSH
- plocha pod křivkou MeSH
- prediktivní hodnota testů MeSH
- senzitivita a specificita MeSH
- thioguanin metabolismus MeSH
- Check Tag
- dítě MeSH
- lidé MeSH
- mladiství MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- hodnotící studie MeSH
- práce podpořená grantem MeSH
- Názvy látek
- azathiopurine MeSH Prohlížeč
- imunosupresiva MeSH
- merkaptopurin MeSH
- thioguanin MeSH
OBJECTIVES: Therapeutic drug monitoring of thiopurine erythrocyte levels is not available in all centers and it usually requires quite a long time to obtain the results. The aims of this study were to build a model predicting low levels of 6-thioguanine and 6-methylmercaptopurine in pediatric inflammatory bowel disease (IBD) patients and to build a model to predict nonadherence in patients treated with azathioprine (AZA). METHODS: The study consisted of 332 observations in 88 pediatric IBD patients. Low AZA dosing was defined as 6-thioguanine levels <125 pmol/8 × 10 erythrocytes and 6-methylmercaptopurine levels <5700 pmol/8 × 10 erythrocytes. Nonadherence was defined as undetectable levels of 6-thioguanine and 6-methylmercaptopurine <240 pmol/8 × 10 erythrocytes. Data were divided into training and testing part. To construct the model predicting low 6-thioguanine levels, nonadherence, and the level of 6-thioguanine, the modification of random forest method with cross-validation and resampling was used. RESULTS: The final models predicting low 6-thioguanine levels and nonadherence had area under the curve, 0.87 and 0.94; sensitivity, 0.81 and 0.82; specificity, 0.80 and 86; and distance, 0.31 and 0.21, respectively, when applied on the testing part of the dataset. When the final model for prediction of 6-thioguanine values was applied on testing dataset, a root-mean-square error of 110 was obtained. CONCLUSIONS: Using easily obtained laboratory parameters, we constructed a model with sufficient accuracy to predict patients with low 6-thioguanine levels and a model for prediction of AZA treatment nonadherence (web applications: https://hradskyo.shinyapps.io/6TG_prediction/ and https://hradskyo.shinyapps.io/Non_adherence/).
Citace poskytuje Crossref.org