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Prediction of Thiopurine Metabolite Levels Based on Haematological and Biochemical Parameters

O. Hradsky, K. Potuznikova, J. Siroka, T. Lerchova, L. Urbanek, V. Mihal, M. Spenerova, M. Velganova-Veghova, E. Karaskova, J. Bronsky,

. 2019 ; 69 (4) : e105-e110. [pub] -

Jazyk angličtina Země Spojené státy americké

Typ dokumentu hodnotící studie, časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc20028806

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

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$a OBJECTIVES: Therapeutic drug monitoring of thiopurine erythrocyte levels is not available in all centers and it usually requires quite a long time to obtain the results. The aims of this study were to build a model predicting low levels of 6-thioguanine and 6-methylmercaptopurine in pediatric inflammatory bowel disease (IBD) patients and to build a model to predict nonadherence in patients treated with azathioprine (AZA). METHODS: The study consisted of 332 observations in 88 pediatric IBD patients. Low AZA dosing was defined as 6-thioguanine levels <125 pmol/8 × 10 erythrocytes and 6-methylmercaptopurine levels <5700 pmol/8 × 10 erythrocytes. Nonadherence was defined as undetectable levels of 6-thioguanine and 6-methylmercaptopurine <240 pmol/8 × 10 erythrocytes. Data were divided into training and testing part. To construct the model predicting low 6-thioguanine levels, nonadherence, and the level of 6-thioguanine, the modification of random forest method with cross-validation and resampling was used. RESULTS: The final models predicting low 6-thioguanine levels and nonadherence had area under the curve, 0.87 and 0.94; sensitivity, 0.81 and 0.82; specificity, 0.80 and 86; and distance, 0.31 and 0.21, respectively, when applied on the testing part of the dataset. When the final model for prediction of 6-thioguanine values was applied on testing dataset, a root-mean-square error of 110 was obtained. CONCLUSIONS: Using easily obtained laboratory parameters, we constructed a model with sufficient accuracy to predict patients with low 6-thioguanine levels and a model for prediction of AZA treatment nonadherence (web applications: https://hradskyo.shinyapps.io/6TG_prediction/ and https://hradskyo.shinyapps.io/Non_adherence/).
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$a Potuznikova, Kristyna $u Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and Motol University Hospital, Prague.
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