Construction of a flow chart–like risk prediction model of ganciclovir‐induced neutropaenia including severity grade: A data mining approach using decision tree
| Autor: | Ken Iseki, Masaki Kobayashi, Kumiko Kasashi, Takehiro Yamada, Shungo Imai, Nobuhisa Ishiguro |
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| Rok vydání: | 2019 |
| Předmět: |
Adult
Male Neutropenia Adolescent Side effect Decision tree computer.software_genre Logistic regression Antiviral Agents Risk Assessment Severity of Illness Index 030226 pharmacology & pharmacy Young Adult 03 medical and health sciences 0302 clinical medicine Risk Factors Data Mining Humans Medicine Pharmacology (medical) 030212 general & internal medicine Adverse effect Ganciclovir Aged Retrospective Studies Aged 80 and over Pharmacology business.industry Medical record Incidence (epidemiology) Decision Trees Retrospective cohort study Middle Aged Logistic Models Absolute neutrophil count Female Data mining business computer |
| Zdroj: | Journal of Clinical Pharmacy and Therapeutics. 44:726-734 |
| ISSN: | 1365-2710 0269-4727 |
| Popis: | WHAT IS KNOWN AND OBJECTIVE Haematological toxicities such as neutropaenia are a common side effect of ganciclovir (GCV); however, risk factors for GCV-induced neutropaenia have not been well established. Decision tree (DT) analysis is a typical technique of data mining consisting of a flow chart-like framework that shows various outcomes from a series of decisions. By following the flow chart, users can estimate combinations of risk factors that may increase the probability of certain events. In our previous study, we demonstrated the usefulness of this approach in the evaluation of adverse drug reactions. Therefore, we aimed to construct a risk prediction model of GCV-induced neutropaenia including severity grade. METHODS We performed a retrospective study at the Hokkaido University Hospital and enrolled patients who received GCV between April 2008 and March 2018. Neutropaenia was defined as an absolute neutrophil count (ANC) |
| Databáze: | OpenAIRE |
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