Construction of pharmacogenomics-guided individualized medication list for elderly patients
- VernacularTitle:药物基因组学指导的老年患者个体化用药目录构建
- Author:
Xinya LI
1
,
2
,
3
;
Jingjing WU
1
,
2
,
3
;
Liwei JI
4
;
Qingxia ZHANG
5
;
Li YANG
6
;
Hui LI
7
;
Shuang LIU
1
,
2
;
Ting LI
4
;
Rongsheng ZHAO
1
,
2
;
Zhanmiao YI
1
Author Information
1. Dept. of Pharmacy，Peking University Third Hospital，Beijing 100191，China
2. Drug Evaluation Center，Health Science Center，Peking University，Beijing 100191，China
3. Dept. of Pharmaceutical Management and Clinical Pharmacy，College of Pharmacy，Peking University，Beijing 100191，China
4. Dept. of Pharmacy/National Clinical Medical Research Center for Geriatrics，Beijing Hospital，Beijing 100730，China
5. Dept. of Pharmacy/National Clinical Medical Research Center for Geriatrics，Capital Medical University，Beijing 100053，China
6. Dept. of Pharmacy，the Affiliated Beijing Tiantan Hospital of Capital Medical University，Beijing 100070，China
7. Dept. of Pharmacy，the Affiliated Ruijin Hospital of Shanghai Jiaotong University School of Medicine，Shanghai 200025，China
- Publication Type:Journal Article
- Keywords:
elderly patients;
individualization;
pharmacogenomics;
medication list;
evidence-based pharmacy
- From:
China Pharmacy
2023;34(3):257-262
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE To develop an individualized medication list for elderly patients by evidence-based pharmacy method， and to support clinical decisions on rational use of METHODS Firstly， drugs with risk genetic information were screened out by systematically reviewing evidence-based pharmacy information. Secondly， researchers investigated the included drugs in lists from different data E- sources. Drugs included in three or more data sources and drugs proposed by the expert committee were then included in the medication list. Thirdly， for the drugs included in two data sources， researchers designed questionnaires to investigate the necessity of drug-related gene testing. According to the scoring results of the expert questionnaire， drugs with higher scores were included in the list. Data sources included real-world data （list of high frequency medication in hospitals， high frequency medication for elderly outpatients and inpatients in National Health Care Claims Data， drugs related to frequent medication errors and so on） and evidence-based pharmacy evidence （the websites of Clinical Pharmacogenomics Implementation Consortium， Dutch Pharmacogenetics Working Group， Food and Drug Administration and so on）. RESULTS The study obtain 68 drugs with risk genetic information which were included in three data sources. Combined with 23 drugs proposed by the expert committee， a list containing 74 drugs was preliminarily formed after de-duplication. A total of 37 drugs included in two databases with risk genetic information were scored through the questionnaire survey to form a supplementary list of 26 drugs. This is the final composition of the list of 100 drugs developed in this study. Among them， there are 43 drugs for the central nervous system， 15 drugs for the cardiovascular system， 12 anti-tumor drugs and so on. Twelve drugs were included in six or more data sources， which mainly consisted of drugs for digestive system， all proton pump inhibitors. CONCLUSION In this study， a list of 100 commonly used drugs which require individualized medication for the elderly was developed by evidence-based pharmacy method. The drug list will be updated in time as available evidence changes， and can provide guidance for rational use of medicines for elderly patients.
