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自發性通報系統中藥名混亂與重複記錄對藥物不良反應訊號偵測的影響 = Ef...
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國立高雄大學資訊工程學系碩士班
自發性通報系統中藥名混亂與重複記錄對藥物不良反應訊號偵測的影響 = Effect of Drug Name Inconsistence and Duplicate Report in SRS Data to the Detection of ADR Signals
紀錄類型:
書目-語言資料,印刷品 : 單行本
並列題名:
Effect of Drug Name Inconsistence and Duplicate Report in SRS Data to the Detection of ADR Signals
作者:
黃楓雄,
其他團體作者:
國立高雄大學
出版地:
[高雄市]
出版者:
撰者;
出版年:
2015[民104]
面頁冊數:
58面圖,表 : 30公分;
標題:
藥物不良反應
標題:
Adverse drug reactions
電子資源:
http://handle.ncl.edu.tw/11296/ndltd/11579031761954876136
附註:
105年10月25日公開
附註:
參考書目:面44-48
摘要註:
世界衛生組織(World Health Organization, WHO)對於藥物不良反應(adverse drug reaction, ADR)的定義為「藥物使用於人體作為預防、診斷、治療疾病或調節生理功能時,在正常的劑量下,產生無預期性,且危害人體的反應」。雖然在藥物上市前有經過嚴格的臨床試驗程序可發現部份的不良反應,但由於藥物在上市前的臨床資料的樣本數有限,無法有效發現潛在的藥物不良反應,因而造成危害者仍時有所聞。為了了解藥品上市後廣泛使用於臨床中的藥品安全性問題,即時的採取必要的措施,有賴於一個有效的藥品安全監測制度(Pharmacogivilance) ,因此,多數的國家建立自主性通報系統(spontaneous reporting system, SRS),用於收集、分析、偵測出潛在的藥物安全的議題。自發性通報系統所通報資料來源的多樣性,造成資料的雜亂、錯誤,其中最主要為資料重複和藥名雜亂的問題,造成訊號判讀的誤差。本研究的主要目的在探討不良反應通報系統的資料中,重複記錄及藥名統一對不良反應信號偵測的影響。我們以美國FDA的SRS通報資料庫FAERS為例,發展了一套自動將藥名統一並排除重複資料的流程方法,並進行有系統的分析,比較排除重複記錄和藥名統一與否對藥物不良反應信號的影響程度,包括信號強度的變化、產生信號的精準度及召回率、以及信號預警的時間。 According to the definition by WHO, Adverse Drug Reaction (ADR) is defined as “noxious and unintended, and which occurs at doses normally used in man for the prophylaxis, diagnosis, or therapy of diseases, or for the modification of physiological function.” Although a new drug before approved for marketing has to undergo strict clinical trials to find possible ADRs, it is impossible to discover all potential adverse drug reactions due to very limit number of samples in clinical trials. News about harmful ADRs are not uncommon. An effective pharmacogivilance system is important to understand the safety issue of widely usage of marketing drugs and facilitate necessary actions in a timely fashion. Therefore, many countries have established various spontaneous reporting systems (SRSs) to collect, analyze and detect suspicious ADR signals. Due to many reporting sources, there are lots of data cleaning problems for SRS data, representatives of them including duplicate reports and inconsistent drug names, which will cause bias to the detected ADR signals. The main purpose of this thesis is to discuss the effect of existing duplicate reports and inconsistent drug names in SRS data to the detection of ADR signals. Using the FDA FAERS database as a case study, we developed an automatic process for unifying drug names and remove duplicate reports. We also conducted systematic analysis, comparing how duplicate reports and inconsistent drug names affect ADR signals, including variations in signal strength, precision and recall of ADR signals, and the time to generate alarms.
自發性通報系統中藥名混亂與重複記錄對藥物不良反應訊號偵測的影響 = Effect of Drug Name Inconsistence and Duplicate Report in SRS Data to the Detection of ADR Signals
黃, 楓雄
自發性通報系統中藥名混亂與重複記錄對藥物不良反應訊號偵測的影響
= Effect of Drug Name Inconsistence and Duplicate Report in SRS Data to the Detection of ADR Signals / 黃楓雄撰 - [高雄市] : 撰者, 2015[民104]. - 58面 ; 圖,表 ; 30公分.
105年10月25日公開參考書目:面44-48.
藥物不良反應Adverse drug reactions
自發性通報系統中藥名混亂與重複記錄對藥物不良反應訊號偵測的影響 = Effect of Drug Name Inconsistence and Duplicate Report in SRS Data to the Detection of ADR Signals
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世界衛生組織(World Health Organization, WHO)對於藥物不良反應(adverse drug reaction, ADR)的定義為「藥物使用於人體作為預防、診斷、治療疾病或調節生理功能時,在正常的劑量下,產生無預期性,且危害人體的反應」。雖然在藥物上市前有經過嚴格的臨床試驗程序可發現部份的不良反應,但由於藥物在上市前的臨床資料的樣本數有限,無法有效發現潛在的藥物不良反應,因而造成危害者仍時有所聞。為了了解藥品上市後廣泛使用於臨床中的藥品安全性問題,即時的採取必要的措施,有賴於一個有效的藥品安全監測制度(Pharmacogivilance) ,因此,多數的國家建立自主性通報系統(spontaneous reporting system, SRS),用於收集、分析、偵測出潛在的藥物安全的議題。自發性通報系統所通報資料來源的多樣性,造成資料的雜亂、錯誤,其中最主要為資料重複和藥名雜亂的問題,造成訊號判讀的誤差。本研究的主要目的在探討不良反應通報系統的資料中,重複記錄及藥名統一對不良反應信號偵測的影響。我們以美國FDA的SRS通報資料庫FAERS為例,發展了一套自動將藥名統一並排除重複資料的流程方法,並進行有系統的分析,比較排除重複記錄和藥名統一與否對藥物不良反應信號的影響程度,包括信號強度的變化、產生信號的精準度及召回率、以及信號預警的時間。 According to the definition by WHO, Adverse Drug Reaction (ADR) is defined as “noxious and unintended, and which occurs at doses normally used in man for the prophylaxis, diagnosis, or therapy of diseases, or for the modification of physiological function.” Although a new drug before approved for marketing has to undergo strict clinical trials to find possible ADRs, it is impossible to discover all potential adverse drug reactions due to very limit number of samples in clinical trials. News about harmful ADRs are not uncommon. An effective pharmacogivilance system is important to understand the safety issue of widely usage of marketing drugs and facilitate necessary actions in a timely fashion. Therefore, many countries have established various spontaneous reporting systems (SRSs) to collect, analyze and detect suspicious ADR signals. Due to many reporting sources, there are lots of data cleaning problems for SRS data, representatives of them including duplicate reports and inconsistent drug names, which will cause bias to the detected ADR signals. The main purpose of this thesis is to discuss the effect of existing duplicate reports and inconsistent drug names in SRS data to the detection of ADR signals. Using the FDA FAERS database as a case study, we developed an automatic process for unifying drug names and remove duplicate reports. We also conducted systematic analysis, comparing how duplicate reports and inconsistent drug names affect ADR signals, including variations in signal strength, precision and recall of ADR signals, and the time to generate alarms.
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