Finnikin Samuel, Ryan Ronan, Marshall Tom
Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
BMJ Open. 2016 Nov 17;6(11):e013120. doi: 10.1136/bmjopen-2016-013120.
Risk scoring is an integral part of the prevention of cardiovascular disease (CVD) and should form the basis for the decision to offer medication to reduce cholesterol (statins). However, there is a suggestion in the literature that many patients are still initiated on statins based on raised cholesterol rather than a raised CVD risk. It is important, therefore, to investigate the role that lipid levels and CVD risks have in the decision to prescribe. This research will establish how cholesterol levels and CVD risk independently influence the prescribing of statins for the primary prevention of CVD in primary care.
The Health Improvement Network (THIN) is a database of coded primary care electronic patient records from over 500 UK general practices. From this resource, a historical cohort will be created of patients without a diagnosis of CVD, not currently receiving a prescription for statins and who had a lipid profile measured. A post hoc QRISK2 score will be calculated for these patients and they will be followed up for 60 days to establish whether they were subsequently prescribed a statin. Primary analysis will consist of predictive modelling using multivariate logistic regression with potential predictors including cholesterol level, calculated QRISK2 score, sociodemographic characteristic and comorbidities. Descriptive statistics will be used to identify trends in prescribing and further secondary analysis will explore what other factors may have influenced the prescribing of statins and the degree of interprescriber variability.
The THIN Data Collection Scheme was approved by the South-East Multicentre Research Ethics Committee in 2003. Individual studies using THIN require Scientific Review Committee approval. The original protocol for this study and a subsequent amendment have been approved (16THIN009A1). The results will be published in a peer review journal and presented at national and international conferences.
风险评分是预防心血管疾病(CVD)不可或缺的一部分,应作为决定是否使用药物降低胆固醇(他汀类药物)的依据。然而,文献表明,许多患者开始使用他汀类药物仍是基于胆固醇升高,而非心血管疾病风险升高。因此,研究血脂水平和心血管疾病风险在处方决定中的作用很重要。本研究将确定胆固醇水平和心血管疾病风险如何独立影响基层医疗中他汀类药物用于心血管疾病一级预防的处方。
健康改善网络(THIN)是一个来自英国500多家全科诊所的编码基层医疗电子患者记录数据库。利用该资源,将创建一个无心血管疾病诊断、目前未接受他汀类药物处方且进行过血脂检测的患者历史队列。将为这些患者计算事后QRISK2评分,并对他们进行60天的随访,以确定他们随后是否被处方了他汀类药物。主要分析将包括使用多变量逻辑回归进行预测建模,潜在预测因素包括胆固醇水平、计算出的QRISK2评分、社会人口学特征和合并症。描述性统计将用于确定处方趋势,进一步的二次分析将探讨可能影响他汀类药物处方的其他因素以及处方医生之间的差异程度。
THIN数据收集计划于2003年获得东南多中心研究伦理委员会批准。使用THIN的个体研究需要科学审查委员会批准。本研究的原始方案及后续修正案已获批准(16THIN009A1)。研究结果将发表在同行评审期刊上,并在国内和国际会议上展示。