Usefulness of a decision tree model for the analysis of adverse drug reactions: Evaluation of a risk prediction model of vancomycin‐associated nephrotoxicity constructed using a data mining procedure
| Autor: | Shungo Imai, Takehiro Yamada, Kumiko Kasashi, Ken Iseki, Masaki Kobayashi |
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| Rok vydání: | 2017 |
| Předmět: |
Adult
Male 0301 basic medicine medicine.medical_specialty 030106 microbiology Decision tree Logistic regression Risk Assessment Cross-validation Nephrotoxicity Toxicology Young Adult 03 medical and health sciences chemistry.chemical_compound 0302 clinical medicine Vancomycin Internal medicine Data Mining Humans Medicine 030212 general & internal medicine Aged Retrospective Studies Aged 80 and over Creatinine business.industry Health Policy Decision Trees Public Health Environmental and Occupational Health Retrospective cohort study Middle Aged Anti-Bacterial Agents Logistic Models chemistry Concomitant Drug Therapy Combination Female Kidney Diseases business Algorithms medicine.drug |
| Zdroj: | Journal of Evaluation in Clinical Practice. 23:1240-1246 |
| ISSN: | 1365-2753 1356-1294 |
| Popis: | Objectives Several publications concerning decision tree (DT) analysis in medical fields have recently demonstrated its usefulness for defining prognostic factors in various diseases. However, there are minimal reports on the predictors of adverse drug reactions. We attempted to use DT analysis to discover combinations of multiple risk factors that would increase the risk of nephrotoxicity associated with vancomycin (VCM). To demonstrate the usefulness of DT analysis, we compared its predictive performance with that of multiple logistic regression analysis. Method A single-centre, retrospective study was conducted at Hokkaido University Hospital. A total of 592 patients, who received intravenous administrations of VCM between November 2011 and April 2016, were enrolled. Nephrotoxicity was defined as an increase in serum creatinine of ≥0.5 mg/dL or a ≥50% increase in serum creatinine from the baseline. Risk factors for VCM nephrotoxicity were extracted from previous reports. In the DT analysis, a chi-squared automatic interaction detection algorithm was constructed. For evaluating the established algorithms, a 10-fold cross validation method was adopted to calculate the misclassification risk of the model. Moreover, to compare the accuracy of the DT analysis, multiple logistic regression analysis was conducted. Results Eighty-seven (14.7%) patients developed nephrotoxicity. A VCM trough concentration of ≥15.0 mg/L, concomitant medication (vasopressor drugs and furosemide), and a duration of therapy ≥14 days were extracted to build the DT model, in which the patients were divided into 6 subgroups based on variable rates of nephrotoxicity, ranging from 4.6 to 69.6%. The predictive accuracies of the DT and logistic regression models were similar (87.3%, respectively), indicating that they were accurate. Conclusion This study suggests the usefulness of DT models for the evaluation of adverse drug reactions. |
| Databáze: | OpenAIRE |
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