書誌事項
- タイトル別名
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- Analysis of Risk Factors for Ganciclovir-Induced Thrombocytopenia and Construction of Risk-Prediction Models Using a Decision Tree Analysis
- ガンシクロビル ユウハツセイ ケッショウバン ゲンショウショウ ノ ヨウイン ブンセキ ト Decision tree カイセキ オ モチイタ リスク スイテイ モデル ノ コウチク
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抄録
<p>Objective: Hematological toxicity, including neutropenia and thrombocytopenia, is a typical side effect of ganciclovir (GCV). We previously developed a risk-prediction model for GCV-induced neutropenia using decision tree (DT) analysis. By employing the DT model, which is a flowchart-like framework, users can predict the combination of factors that may increase neutropenia risk. However, a risk-prediction model for thrombocytopenia has not been established. Here, we aimed to identify the risk factors associated with GCV-induced thrombocytopenia and construct risk-prediction models.</p><p>Method: We retrospectively evaluated the medical records of 386 patients who received GCV between April 2008 and March 2018 at Hokkaido University Hospital. Thrombocytopenia is defined as a decrease in the platelet count (PLT) to <50,000 cells/mm3 and to a <75% decrease. Risk factors of thrombocytopenia were extracted from the medical records using a multiple logistic regression analysis. Moreover, we employed chi-squared automatic interaction detection (CHAID) and classification and regression tree (CRT) algorithms to develop the DT models. The accuracies of the established models were evaluated to assess their reliability.</p><p>Results: Thrombocytopenia occurred in 47 (12.2%) patients. In the multiple logistic regression analysis, data of patients with white blood cells <7,000 cells/mm3,PLT<101,000 cells/mm3 and total bilirubin ≥ 0.8 mg/dL were extracted. Two risk-prediction models were constructed, and patients were divided into six and seven subgroups. In both algorithms, data on hematopoietic stem cell transplantations, PLT <101,000 cells/mm3, serum albumin < 2.8 g/dL, total bilirubin ≥ 0.8 mg/dL, and residence in intensive care unit were extracted. The predictive accuracy of both the CHAID algorithm and the logistic regression models was 87.8% and that of the CRT algorithm was 88.3%, indicating they were reliable.</p><p>Conclusion: We successfully identified the factors associated with GCV-induced thrombocytopenia and constructed useful flowchartlike risk-prediction models.</p>
収録刊行物
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- 医薬品情報学
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医薬品情報学 21 (1), 9-19, 2019-05-31
一般社団法人 日本医薬品情報学会
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詳細情報 詳細情報について
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- CRID
- 1390282763124004224
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- NII論文ID
- 130007666032
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- NII書誌ID
- AA11916144
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- ISSN
- 1883423X
- 13451464
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- NDL書誌ID
- 029787158
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可