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  • 1 July 2016 to 30 December 2018
  • Project No: 333
  • Funding round: FR 12
  • Cancer
Familial

Familial Hypercholesterolaemia (FH) is a common inherited cause of raised cholesterol, affecting at least 120,000 people in the UK. However, over 80% of people with FH are still not identified, leading to many avoidable heart attacks and early deaths. The risk of heart disease can be dramatically reduced by starting medicines to lower cholesterol levels.

Currently it is recommended General Practitioners (GPs) identify possible FH by examining patients who have raised cholesterol and a family history of heart disease. We have found this does not accurately identify all people with FH, and also causes unnecessary specialist referral for those without the condition.

Based on analysis of almost 3 million patients’ records and over 5000 cases of FH, we have therefore developed a new computer-based approach to better identify people with possible FH. This uses information from GP computer records, and is called a FH case-ascertainment tool (or ‘FAMCAT’ for short). In this study, we will invite people that FAMCAT has identified as having the highest possibility of FH, to have their diagnosis confirmed by a genetic test and, following assessment by their GP, referred to a specialist.

Many people, such as primary care ‘clinical commissioning’ groups, FH patient groups and specialists are keen to use FAMCAT but we need to evaluate it properly, in stages. This study will tell us how helpful FAMCAT may be when used in around 19 general practices, and if it is acceptable to GPs, practice nurses, and patients. This will help us further refine the FAMCAT approach - as an intervention fit for use in real life practice. Secondly, the findings will help us design the best ways of then fully testing this intervention in a much larger study – a trial to provide ‘definitive’ evidence about the benefits of using FAMCAT in general practice.

Nadeem Qureshi (University of Nottingham) with co-applicants Kate Walters (UCL), Barbara Hanratty (Newcastle),  Katherine Payne (Manchester), Stephen Weng, Joe Kai, Carol Coupland, Matthew Jones and Paul Leighton (Nottingham). 


Amount awarded: £399,168

Evidence synthesis working group

The collaboration will be conducting 18 high impact systematic reviews, under four workstreams.

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