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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 --

项目摘要

项目成果

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中文摘要
翻译
药物的安全性可能很难调查,通常唯一的可能性是进行观察性研究,看看接受药物的人是否比不接受药物的人更容易出现副作用。最近,越来越多的研究已经完成,他们的结果往往具有重大的公共卫生重要性(例如,MMR疫苗和自闭症之间缺乏关联)。重要的是,这些研究的结果是可靠的,但其基础方法受到许多可能的偏见。我计划调查其中的一些方法,并探索它们的偏差,目的是提高药物安全性研究的可靠性。这将通过使用匿名患者病历电子数据库的至少4项研究来实现。这些研究将调查SSRI抗抑郁药与脑出血、噻托溴铵(一种治疗慢性阻塞性肺病的药物)与中风、依折麦布(一种降脂药)与癌症以及格列酮抗糖尿病药物与心肌梗死之间的可能联系。因此,该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,并将改善未来药物安全性研究的方法。
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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