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Developing methodologies for use in observational studies of drug effects using computerised clinical data.

Developing methodologies for use in observational studies of drug effects using computerised clinical data.
使用计算机化临床数据开发用于药物作用观察研究的方法。
批准号:
G0802403/1
负责人:
Ian Douglas
金额:
$55.08万
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2009
资助国家:
英国
项目状态:
已结题
起止时间:
2009 至 --

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中文摘要
翻译
药物的安全性很难调查,通常唯一的可能性是进行观察性研究,以确定接受药物治疗的人是否比未接受药物治疗的人更有可能出现副作用。最近进行了越来越多的此类研究,其结果往往具有重大的公共卫生重要性(例如,MMR疫苗与自闭症之间缺乏关联)。重要的是,这些研究的结果是可靠的,然而,它们的基础方法受到许多可能的偏见的影响。为了提高药物安全性研究的可靠性,我计划调查其中的一些方法并探索它们的偏差。这将通过使用匿名病人医疗记录电子数据库进行至少四项研究来实现。这些研究将调查SSRI类抗抑郁药物与脑出血、噻托溴铵(一种治疗慢性阻塞性肺病的药物)与中风、依折替米贝(一种降脂剂)与癌症、格列酮类抗糖尿病药物与心肌梗死之间的可能联系。因此,这一研究方案将回答与四种药物/药物类别的安全性直接相关的问题,并将在未来改进药物安全研究的方法学方法。
英文摘要
The safety of medicines can be difficult to investigate and often the only possibility is to conduct observational studies to see whether people receiving a drug are more likely to experience a side effect than people who do not receive the drug. Recently more and more of these studies have been done and frequently their results have been of major public health importance (e.g. the lack of association between MMR vaccine and autism). It is important that the results of these studies are reliable, and yet their underpinning methodologies are subject to many possible biases. I plan to investigate some of these methodologies and explore their biases, with the objective of increasing the reliability of drug safety studies. This will be achieved through at least four studies using an electronic database of anonymised patient medical records. The studies will investigate possible links between SSRI antidepressants and cerebral haemorrhage, tiotropium (a treatment for chronic obstructive pulmonary disease) and stroke, ezetimibe (a lipid lowering agent) and cancer and glitazone antidiabetics and myocardial infarction. This programme of research will therefore answer questions directly related to the safety of four drugs/drug classes and will improve methodological approaches to drug safety studies in the future.
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Evaluating and addressing the impact of COVID-19 restrictions on electronic health records in estimating causal effects
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