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构建延长释放羟考酮片所致恶心的风险预测模型及预测因素的阐明。

Construction of a Risk Prediction Model of Extended Release Oxycodone Tablet-Induced Nausea and Clarification of Predictive Factors.

机构信息

Department of Pharmacy, Hokkaido University Hospital.

Cancer Center Palliative Care Team, Hokkaido University Hospital.

出版信息

Biol Pharm Bull. 2021;44(4):593-598. doi: 10.1248/bpb.b20-01028.

DOI:10.1248/bpb.b20-01028
PMID:33790110
Abstract

Nausea is a typical adverse event associated with opioids. In this study, we performed logistic regression analysis with the aim of clarifying the risk factors for nausea induced by extended-release oxycodone (ER-OXY). Furthermore, we constructed a decision tree (DT) model, a typical data mining method, to estimate the risk of oxycodone-induced nausea by combining multiple factors. A retrospective study was conducted on patients who newly received ER-OXY for cancer pain during hospitalization at Hokkaido University Hospital in Japan from April 2015 to March 2018. In logistic regression and DT analyses, the dependent variable was the presence or absence of nausea. Independent variables were the potential risk factors. First, univariate analyses were performed to screen potential factors associated with oxycodone-induced nausea. Then, multivariate and DT analyses were performed using factors with p-values <0.1 in the univariate analysis. Of 267 cases included in this study, nausea was observed in 30.3% (81/267). In multivariate logistic regression analysis, only female sex was extracted as an independent factor affecting nausea (odds ratio, 1.98). In the DT analysis, we additionally revealed that an age <50 years was a risk factor for nausea in female patients. Thus, our DT model indicated that the risk of ER-OXY-induced nausea was highest in the subgroup comprising females <50 years of age (66.7%) and lowest in male patients (25.1%). The DT model suggested that the factor of young women may be an increased risk of ER-OXY-induced nausea.

摘要

恶心是与阿片类药物相关的典型不良反应。在这项研究中,我们进行了逻辑回归分析,旨在阐明引起缓释羟考酮(ER-OXY)恶心的危险因素。此外,我们构建了决策树(DT)模型,这是一种典型的数据挖掘方法,通过结合多种因素来估计羟考酮引起恶心的风险。本研究对 2015 年 4 月至 2018 年 3 月期间在日本北海道大学医院新接受 ER-OXY 治疗癌症疼痛的住院患者进行了回顾性研究。在逻辑回归和 DT 分析中,因变量为是否存在恶心。自变量为潜在的危险因素。首先进行单变量分析,筛选与羟考酮引起恶心相关的潜在因素。然后,使用单变量分析中 p 值<0.1 的因素进行多变量和 DT 分析。本研究共纳入 267 例患者,81 例(81/267)出现恶心。在多变量逻辑回归分析中,仅女性被确定为影响恶心的独立因素(优势比,1.98)。在 DT 分析中,我们还发现年龄<50 岁是女性恶心的危险因素。因此,我们的 DT 模型表明,年龄<50 岁的女性患者中 ER-OXY 引起恶心的风险最高(66.7%),而男性患者的风险最低(25.1%)。DT 模型表明,年轻女性这一因素可能增加 ER-OXY 引起恶心的风险。

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