Primary Care Epidemiology
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Primary Care Epidemiology research group

Overview

Our research group includes clinicians, statisticians, epidemiologists, computer scientists and patient representatives.

The group undertakes large scale research into:

  • The epidemiology of diseases (such as heart disease, stroke, diabetes, cancer, thrombosis, osteoporosis, mental health and dementia).
  • Safety of commonly prescribed drugs (including antidepressants, antipsychotics, statins, direct oral anticoagulants, anticholinergics, NSAIDs, Cox-2 inhibitors, hormone replacement therapy, oral contraceptives and drugs used in the treatment of type 2 diabetes).
  • Group members are also involved with the development, validation and implementation of risk prediction tools in collaboration with ClinRisk Ltd.

We make extensive use of a number of databases including  QResearch. Set up by Professor Julia Hippisley-Cox in 2002, QResearch is the largest database of its kind worldwide, containing a wealth of longitudinal data from over 25 million people in over 1,500 UK practices linked to secondary care data for hospital admissions, mortality and cancer registration. 

qresearch
 

Research issues

1. Drug Safety

Whilst clinical trials are undertaken during the development and testing phases for new and commonly used drugs, these trials tend to be in small numbers of selected participants for limited periods of time. Once a drug is licensed, it tends to be used in large numbers of unselected individuals over long periods of time.

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It is therefore important to have independent systematic research into the risk and benefits of new and commonly used drugs to identify and quantify both intended and unintended effects on patients. We use QResearch and other databases to undertake such studies which are of national and international importance.

In one project, we are examining the use of antidepressants when patients are already on other drugs or have other health conditions, and assessing whether these will lead to potential problems. We will then create a decision aid for use in clinical practice to help GPs and patients decide on the best antidepressant for the patient. This work is from the Mental Health & Technology theme of the NIHR Nottingham Biomedical Research Centre (BRC)

 

2. Risk Prediction

Much of clinical practice involves assessing the probability that a patient either has a particular disease or may develop it at some point in the future and also what the risks and benefits of various treatments or interventions are. Doctors need better information to inform discussions with patients and decisions to investigate, refer and treat individuals. Both doctors and patients need better information to ensure patients are fully informed about the risks and benefits of clinical decisions, so they can give consent.

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New approaches to risk estimation were needed to take account of the characteristics of the population to which the tool should be applied and which can be updated over time as the population changes and national guidelines for prevention evolve.

A suite of innovative risk prediction models has been developed by the group using the QResearch database which is a large anonymised repository of electronic health records for medical research, created as part of a not-for-profit partnership between the University of Nottingham and EMIS – a leading supplier of GP clinical computer systems in the UK (www.qresearch.org). 

  1. QRisk tool [1] is a tool for predicting an individual’s 10-year risk of cardiovascular disease. In 2014, it replaced Framingham as the risk engine of choice in the NICE lipid modification guideline[2] and is central to policy guidance such as NHS Health Checks[3]. The QRISK lifetime version of the tool[4] is used by Public Health England on its NHS Choices website to estimate heart age; by September 2017 it had been used by 3 million people[5]. It is recommended by the American Heart Association as the risk engine of choice for South Asians[6].

  2. QStroke tool [7]. QStroke was published in 2013 and predicts 10-year risk of ischaemic stroke to identify patients for whom stroke prevention measures (such as anticoagulation) are likely to be beneficial. 

  3. QBleed tool [8]. Originally published in 2014, QBleed predicts the risk of upper gastrointestinal bleeding and intracranial bleeding with anticoagulation. It is designed to be used with QStroke to help patients weigh up the risks and benefits of anticoagulation. 

  4. QCancer tool [9,10,11]. This estimates the risk of a patient having an existing but as yet undiagnosed cancer based on the pattern of symptoms and risk factors for 12 different types of cancer. The research underpinning the QCancer tool was widely cited in the 2015 NICE guidance on referral for suspected cancer[12]. 

  5. QCancer-10 tool estimates the 10-15 year risk of developing cancer. The colorectal cancer tool had the best performance of any colorectal cancer risk assessment tool in an independent external validation by Cambridge University using the UK-Biobank cohort[13]. 

  6. QFracture tool [14] predicts 10-year risk of fragility fracture of hip, spine, wrist and shoulder so that high risk patients can have interventions to lower this risk. In 2017, an international independent validation of QFracture showed that QFracture outperforms existing tools[15]. It was implemented by EMIS in 2014. QFracture is recommended by NICE guidelines[16] and in the 2017 NICE Osteoporosis Quality Standard (QS149) [17] and the technology appraisal on Bisphosphonates for treating osteoporosis (TA464) [18]. It is recommended by SIGN (142) in Scotland[19]. It was included as an indicator in the GP Quality and Outcomes Framework national contract for GPs in 2014.

  7. QDiabetes tool [20]. This predicts 10 year risk of developing type 2 diabetes so that patients can have interventions to lower their risk. The QDiabetes® algorithms have been validated by ourselves and others in independent groups of patients using UK primary care databases such as QResearch[21], CPRD[21], THIN[22]. It has been independently and externally validated in international populations and compared with other diabetes risk prediction models and shown to have the best performance[23]. QDiabetes is recommended in the NHS Health Checks[24] and National Institute of Clinical Excellence (NICE) guidance on the prevention of type 2 diabetes in people at high risk[25] and the NICE guidance on promoting health and preventing premature mortality in black, Asian and other ethnic minority groups (QS167) [26]. It is also used by the NHS Diabetes Prevention Programme (NHS DPP). QDiabetes was implemented in EMIS in 2013/4 (see link). 

  8. QAdmissions tool [27] identifies patients at high risk of unplanned hospital admission, so they can have preventative measures to reduce hospital admissions. It is recommended by the 2016 NICE guideline on multi-morbidity (NG56) [28] and the NHS England’s designated enhanced service. It was implemented by EMIS in 2014.

  9. QMortality [29] and QFrailty[29]. The QMortality algorithm was published in 2017 and quantifies risk of death over the next 12 months and the new QFrailty tool is a novel outcomes based classification to identify the most frail patients to meet the requirements of the 2017 GMS contract. It will be implemented by EMIS in 2018

  10. QKidney tool[30] identifies patients at high risk of moderate or severe kidney failure. It is recommended by Kidney Health in Australia  here
references
  1. Hippisley-Cox J, Coupland C, Vinogradova Y, et al. Performance of the QRISK cardiovascular risk prediction algorithm in an independent UK sample of patients from general practice: a validation study. Heart 2008;94:34-39. doi: 10.1136/hrt.2007.134890
  2. National Clinical Guideline Centre. Lipid modification: cardiovascular risk assessment and the modification of blood lipids for the primary and secondary prevention of cardiovascular disease. London, 2014:286
  3. Robson J, Dostal I, Sheikh A, et al. The NHS Health Check in England: an evaluation of the first 4 years. BMJ Open 2016;6(1) doi: 10.1136/bmjopen-2015-008840
  4. Hippisley-Cox J, Coupland C, Robson J, et al. Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database. BMJ 2010;341:c6624. [published Online First: 2010/12/15]  doi: https://doi.org/10.1136/bmj.c6624 
  5. Public Health England. Action plan for cardiovascular disease prevention. London: Public Health England, 2017
  6. Volgman AS, Palaniappan LS, Aggarwal NT, et al. Atherosclerotic Cardiovascular Disease in South Asians in the United States: Epidemiology, Risk Factors, and Treatments: A Scientific Statement From the American Heart Association. Circulation 2018 doi: 10.1161/cir.0000000000000580
  7. Hippisley-Cox J, Coupland C, Brindle P. Derivation and validation of QStroke score for predicting risk of ischaemic stroke in primary care and comparison with other risk scores: a prospective open cohort study. BMJ 2013;346:f2573  doi: 10.1136/bmj.f2573
  8. Hippisley-Cox J, Coupland C. Predicting risk of upper gastrointestinal bleed and intracranial bleed with anticoagulants: cohort study to derive and validate the QBleed scores. BMJ 2014;349:g4606  doi: 10.1136/bmj.g4606
  9. Hippisley-Cox J, Coupland C. Identifying women with suspected ovarian cancer in primary care: derivation and validation of algorithm. BMJ 2012;344 doi: 10.1136/bmj.d8009
  10. Hippisley-Cox J, Coupland C. Symptoms and risk factors to identify men with suspected cancer in primary care: derivation and validation of an algorithm. Br J Gen Pract 2013;63(606):1-10  doi: 10.3399/bjgp13X660724
  11. Hippisley-Cox J, Coupland C. Symptoms and risk factors to identify women with suspected cancer in primary care: derivation and validation of an algorithm. British Journal of General Practice 2013;63(606):11-21  doi: 10.3399/bjgp13X660733
  12. National Institute for Health and Care Excellence. Suspected cancer: recognition and referral. NICE guideline. 1 ed. London: NICE, 2015:378
  13. Usher-Smith JA, Harshfield A, Saunders CL, et al. External validation of risk prediction models for incident colorectal cancer using UK Biobank. British Journal of Cancer 2018 doi: 10.1038/bjc.2017.463
  14. Hippisley-Cox J, Coupland C. Derivation and validation of updated QFracture algorithm to predict risk of osteoporotic fracture in primary care in the United Kingdom: prospective open cohort study. BMJ 2012;344:e3427  doi: 10.1136/bmj.e3427
  15. Dagan N, Cohen-Stavi C, Leventer-Roberts M, et al. External validation and comparison of three prediction tools for risk of osteoporotic fractures using data from population based electronic health records: retrospective cohort study. BMJ 2017;356:i6755  doi: 10.1136/bmj.i6755
  16. National Institute for Health and Care Excellence. Osteoporosis: Fragility fracture risk. Short clinical guideline - evidence and recommendation. In: NICE, ed. London: National Clinical Guideline Centre, 2012:90
  17. National Institute for Health and Care Excellence. Osteoporosis - quality standard (QS149). London: NICE, 2017
  18. National Institute for Health and Care Excellence. Bisphosphonates for treating osteoporosis: Technology appraisal guidance (TA464). London: NICE, 2017
  19. Healthcare Improvement Scotland. SIGN142 Management of osteoporosis and the prevention of fragility fractures, 2015:128
  20. Hippisley-Cox J, Coupland C, Robson J, et al. Predicting risk of type 2 diabetes in England and Wales: prospective derivation and validation of QDScore. BMJ 2009;338:b880 doi: 10.1136/bmj.b880
  21. Hippisley-Cox J, Coupland C, Brindle P. The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study. BMJ Open 2014;4(8):e005809 doi: 10.1136/bmjopen-2014-005809
  22. Collins GS, Altman DG. External validation of the QDScore for predicting the 10-year risk of developing Type 2 diabetes. Diabetic Medicine 2011;28:599-607 doi: 10.1111/j.1464-5491.2011.03237.x
  23. Kengne AP, Beulens JWJ, Peelen LM, et al. Non-invasive risk scores for prediction of type 2 diabetes (EPIC-InterAct): a validation of existing models. The Lancet Diabetes & Endocrinology 2014;2(1):19-29  doi: 10.1016/S2213-8587(13)70103-7
  24. Public Health England. NHS Health Check best practice guidance 2017. In: Kwok P, Thompson K, Kearney M, Lagord C, Waterall J, Rees H., ed. London: Public Health England, 2017:33
  25. National Institute for Health and Care Excellence. Type 2 diabetes: prevention in people at high risk: NICE guidelines [PH38]  updated in 2017. London, 2017
  26. National Institute for Health and Care Excellence. Promoting health and preventing premature mortality in black, Asian and other minority ethnic groups: Quality standard (QS167); 2018:34
  27. Hippisley-Cox J, Coupland C. Predicting risk of emergency admission to hospital using primary care data: derivation and validation of QAdmissions score. BMJ Open 2013;3(8):e003482 doi: 10.1136/bmjopen-2013-003482
  28. National Institute for Health and Care Excellence. Multimorbidity: clinical assessment and management, NICE guidelines NG56. In: NICE, ed. London, 2016:443
  29. Hippisley-Cox J, Coupland C. Development and validation of QMortality risk prediction algorithm to estimate short term risk of death and assess frailty: cohort study. BMJ 2017;358 doi: 10.1136/bmj.j4208
  30. Hippisley-Cox J, Coupland C. Predicting the risk of Chronic Kidney Disease in Men and Women in England and Wales: prospective derivation and external validation of the QKidney®Scores. BMC Family Practice 2010;11:49 doi: 10.1186/1471-2296-11-49
 

 

 

Outcomes and Impact

All of the risk prediction tools developed by the group are publicly accessible and the majority have been integrated into the major GP clinical system (EMIS Health) which supplies computer systems to over 55% of GP practices nationally covering a population in excess of 30 million. The tools are also available as free open source software to facilitate use internationally. 

The Department of Health uses both QRISK and QDiabetes as integral parts of the NHS Health Check prevention programme in England. This programme offers a risk assessment of health issues such as heart disease, stroke and type 2 diabetes, to adults aged 40-74 years in England, and helps to identify ways to reduce their risks. Interventions include weight reduction, smoking cessation, blood pressure lowering treatment and cholesterol lowering treatment. Similar tools which estimate risk of other conditions such as osteoporotic fracture are also now recommended in national guidelines and tools embedded in clinical computer systems.

QRISK, QFracture, QDiabetes and QAdmissions are recommended by NICE guidelines.

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QRISK software, which is embedded in > 99% of UK GP clinical computer systems, runs calculations every night which generate a rank-ordered list of those at high risk of heart disease or stroke. Similar tools which estimate risk of other conditions such as osteoporotic fracture ( QFracture) and diabetes ( QDiabetes) are also recommended in national guidelines and embedded in GP clinical computer systems. The tools help identify those patients at high risk of developing a disease for whom preventative measures can be considered.

  • QRISK:
    • Is recommended in the NICE lipid modification guideline (Clinical guideline CG181); NHS Health Checks Best Practice Guidance; the   American Heart Association for South Asians.
    • It also outperformed the American Atherosclerotic Cardiovascular Disease (ASCVD) risk score in an international validation on US subjects.
    • By 2017, the QRISK lifetime version of the tool had been used over 3 million times on the NHS Choices website to estimate heart age as reported here.
    • A microsimulation study by researchers at the University of Cambridge estimated that the program is reducing health inequalities and preventing approximately 300 premature deaths (before 80 years) and resulting in an additional 1,000 people being free of cardiovascular diseases, dementia, and lung cancer at age 80 each year in England.
    • QRISK was highlighted by the BBC2 Horizon’s program here, the BBC1 Science series “Doctor in the House” and several times in the Radio 4 series “Inside Health”.  
  • QFracture:
  • QDiabetes:
    • Had the best performance of any diabetes risk assessment tool in an international validation study.
    • Is recommended in the NHS Heath Check; NICE guidance on the prevention of type 2 diabetes in people at high risk [ PH38]; NICE guidance on promoting health and preventing premature mortality in black, Asian and other minority ethnic groups [ QS167].
    • Is used by the national NHS Diabetes Prevention Programme.
  • QAdmissions is recommended by the 2016 NICE guideline [ NG56] on multi-morbidity.
  • QKidney is recommended by Kidney Health in Australia.
  • QCancer:
    • The research underpinning the development of the QCancer tool was used extensively within the NICE guidance on referral for suspected cancer [ CG27]. 
    • The QCancer tool has been evaluated in the UK by Macmillan Cancer Support and is recommended by Cancer Research UK.  It was subsequently implemented into EMIS Health systems in 2016 and is used across the NHS.
 

Current projects

  • Safety and harms of antidepressant medication.
  • Risk of cancer in patients with diabetes.
  • Risk of dementia among patients prescribed anticholinergic drugs.
  • Cross validation of QScores on QResearch and CPRD.
  • Safety and effectiveness of novel anticoagulants.
  • Risk of venous thromboembolism with the oral contraceptive pill.
  • Risk of venous thromboembolism with different types of HRT.
  • Prostate specific antigen (PSA) testing and its implications.
  • Development of decision aids to improve prescribing of antidepressants.
 

 

Primary Care Epidemiology

The University of Nottingham
School of Medicine, Tower Building
Nottingham, NG7 2RD


telephone: +44 (0) 115 846 6915
email:carol.coupland@nottingham.ac.uk