医院抗肿瘤药使用的多变量监测方法研究  

Multivariate data analysis method for hospital antineoplastic drugs monitoring

作　　者：蒋程[1] 夏仲尼[1] 朱立[1] 郑造乾[1] 徐金波[1] 李功华[1] JIANG Cheng;XIA Zhongni;ZHU Li(Department of Pharmacy,Tongde Hospital of Zhejiang Province,Hangzhou 310012,China)

机构地区：[1]浙江省立同德医院药学部

出　　处：《浙江医学》2019年第19期2096-2099,共4页Zhejiang Medical Journal

基　　金：浙江省公益技术应用研究计划项目(2016C33127);浙江省医学会临床科研基金项目(2016ZYC-A10);浙江省立同德医院科研基金博士科研专项(TD2015B004)

摘　　要：目的探索医院抗肿瘤药使用的多变量监测方法,为临床合理使用抗肿瘤药提供指导。方法提取住院患者2010-2015年共24个季度70种抗肿瘤药的用量数据,建立主成分分析(PCA)模型。通过构建主成分得分图,结合主成分载荷图,对不同季度抗肿瘤药的用量进行监测,筛选变化较显著的品种。若某一季度的得分统计值超出了控制限,构建得分贡献图分析得分异常的原因。结果2010至2015年多种抗肿瘤药的用量呈现出增长的趋势,其中卡培他滨片0.5g、甲地孕酮分散片160mg、替吉奥胶囊20mg、比卡鲁胺片50mg用量增长较显著。2015年第3季度抗肿瘤药的用量存在异常,主要原因为替吉奥胶囊20mg、甲地孕酮分散片160mg、比卡鲁胺片50mg、羟基脲片0.5g的用量偏高。结论本研究证明了PCA算法在抗肿瘤药使用监测中的有效性,可为医院抗肿瘤药监测提供新的方法。Objective To develop a multivariate data analysis method for hospital antineoplastic drugs monitoring.Methods The original use of 70 antineoplastic drugs in 24 quarters from 2010 to 2015 in our hospital was extracted and the principal component analysis(PCA)model was established.The principal component scores plot in combination with the principal component loading plot was applied to monitor the application of antineoplastic drugs.The antineoplastic drugs showing the most significant change trend were screened.When the statistics value of a quarter deviated from the control limit,the causes of abnormalities were diagnosed according to the score contribution plot.Results The use of several antineoplastic drugs presented a growth trend from 2010 to 2015 in our hospital.Among these,the capecitabine tablets 0.5g,megestrol dispersible tablets 160mg,tegafur,gimeracil and oteracil porassium capsules 20mg and bicalutamide tablets 50mg showed the most significant upward trend.The 3rd quarter of 2015 was beyond the control limit,which was caused by the higher use of tegafur,gimeracil and oteracil porassium capsules 20mg,megestrol dispersible tablets 160mg,bicalutamide tablets 50mg and hydroxycarbamide tablets 0.5g.Conclusion This case study demonstrated that it was effective to employ PCA algorithm to monitor the application of antineoplastic drugs.This study provides a new method for the monitoring of antineoplastic drugs in hospital.

关 键 词：抗肿瘤药 主成分分析 主成分得分 主成分载荷 

分 类 号：R28[医药卫生—中药学]