A decision support tool to find the best cyclosporine dose when switching from intravenous to oral route in pediatric stem cell transplant patients.
Purpose: Managing the pharmacokinetic variability of immunosuppressive drugs after pediatric hematopoietic stem cell transplantation (HSCT) is a clinical challenge. Thus, the aim of our study was to design and validate a decision support tool predicting the best first cyclosporine oral dose to give...
| Published in: | European Journal of Clinical Pharmacology Vol. 76; no. 10; pp. 1409 - 1417 |
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| Main Authors: | , , , , |
| Format: | pictorial research tables/charts Journal Article |
| Published: |
Springer Nature
Oct2020
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=145654881&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 145654881 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00316970 NP9 jtl: European Journal of Clinical Pharmacology issn: 00316970 maglogo: N pubinfo: dt: Oct2020 vid: 76 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 145654881 144050013 145654881 145654881 10.1007/s00228-020-02918-9 145654881 ppf: 1409 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A decision support tool to find the best cyclosporine dose when switching from intravenous to oral route in pediatric stem cell transplant patients. aug: au: Leclerc, Vincent Bleyzac, Nathalie Ceraulo, Antony Bertrand, Yves Ducher, Michel affil: EMR 3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine et de Maïeutique Lyon-Sud Charles Mérieux, Université Claude Bernard Lyon 1, 165 chemin du Grand Revoyet-BP 12, 69921 Oullins Cedex, Lyon, France sug: subj: Cyclosporine Administration and Dosage Drug Administration Routes Decision Making Hematopoietic Stem Cell Transplantation In Infancy and Childhood Infusion Pumps Evaluation Administration, Oral Evaluation Human Artificial Intelligence Models, Theoretical ROC Curve Validation Studies Descriptive Statistics Child Child: 6-12 years ab: Purpose: Managing the pharmacokinetic variability of immunosuppressive drugs after pediatric hematopoietic stem cell transplantation (HSCT) is a clinical challenge. Thus, the aim of our study was to design and validate a decision support tool predicting the best first cyclosporine oral dose to give when switching from intravenous route. Methods: We used 10-years pediatric HSCT patients' dataset from 2008 to 2018. A tree-augmented naïve Bayesian network model (method belonging to artificial intelligence) was built with data from the first eight-years, and validated with data from the last two. Results: The Bayesian network model obtained showed good prediction performances, both after a 10-fold cross-validation and external validation, with respectively an AUC-ROC of 0.89 and 0.86, a percentage of misclassified patients of 28.7% and 35.2%, a true positive rate of 0.71 and 0.65, and a false positive rate of 0.12 and 0.14 respectively. Conclusion: The final model allows the prediction of the most likely cyclosporine oral dose to reach the therapeutic target specified by the clinician. The clinical impact of using this model needs to be prospectively warranted. Respecting the decision support tool terms of use is necessary as well as remaining critical about the prediction by confronting it with the clinical context. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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