Research using CPRD data has informed drug safety guidance and clinical practice and resulted in over 2,500 peer-reviewed publications. The CPRD bibliography is updated on a monthly basis (last updated 5 May 2020) and papers are listed below and in the PDF below.

If you have published papers using CPRD data which are not included in this list, please contact us at so that we can update the bibliography.


 (PDF, 3MB, 203 pages) 

This work uses data provided by patients and collected by the NHS as part of their care and support. CPRD encourages researchers to use this citation in all publications using CPRD data. Find out more about acknowledging the use of patient data at the Understanding Patient Data website



Export 2509 results:
Author Title [ Type(Desc)] Year
Journal Article
A. Tebboth, Lee, S., Scowcroft, A., Bingham-Gardiner, P., Spencer, W., Bolodeoku, J., and Hassan, S. W., Demographic and Clinical Characteristics of Patients With Type 2 Diabetes Mellitus Initiating Dipeptidyl Peptidase 4 Inhibitors: A Retrospective Study of UK General Practice, Clin Ther, vol. 38, pp. 1825-1832.e15, 2016.
A. L. Cope, Chestnutt, I. G., Wood, F., and Francis, N. A., Dental consultations in UK general practice and antibiotic prescribing rates: a retrospective cohort study, Br J Gen Pract, vol. 66, pp. e329-36, 2016.
S. Hawley, Edwards, C. J., Arden, N. K., Delmestri, A., Cooper, C., Judge, A., and Prieto-Alhambra, D., Descriptive epidemiology of hip and knee replacement in rheumatoid arthritis: an analysis of UK electronic medical records, Semin Arthritis Rheum, 2019.
L. A. Garcia Rodriguez, Ruigomez, A., Wallander, M. A., Johansson, S., and Olbe, L., Detection of colorectal tumor and inflammatory bowel disease during follow-up of patients with initial diagnosis of irritable bowel syndrome, Scand J Gastroenterol, vol. 35, pp. 306-11, 2000.
S. H. Mahmoudpour, Baranova, E. V., Souverein, P. C., Asselbergs, F. W., de Boer, A., and van der Zee, A. H. Maitlan, Determinants of angiotensin-converting enzyme inhibitor (ACEI) intolerance and angioedema in the UK Clinical Practice Research Datalink, Br J Clin Pharmacol, vol. 82, pp. 1647-1659, 2016.
R. R. Camejo, McGrath, C., Miraldo, M., and Rutten, F., The determinants of cost-effectiveness potential: an historical perspective on lipid-lowering therapies, Pharmacoeconomics, vol. 31, pp. 445-54, 2013.
N. C. Hazra, Rudisill, C., and Gulliford, M. C., Determinants of health care costs in the senior elderly: age, comorbidity, impairment, or proximity to death?, Eur J Health Econ, vol. 19, pp. 831-842, 2018.
J. D. Chalmers, Tebboth, A., Gayle, A., Ternouth, A., and Ramscar, N., Determinants of initial inhaled corticosteroid use in patients with GOLD A/B COPD: a retrospective study of UK general practice, NPJ Prim Care Respir Med, vol. 27, p. 43, 2017.
A. F. Macedo, Bell, J., McCarron, C., Conroy, R., Richardson, J., Scowcroft, A., Sunderland, T., and Rotheram, N., Determinants of oral anticoagulation control in new warfarin patients: analysis using data from Clinical Practice Research Datalink, Thromb Res, vol. 136, pp. 250-60, 2015.
M. E. Saine, Carbonari, D. M., Newcomb, C. W., Nezamzadeh, M. S., Haynes, K., Roy, J. A., Cardillo, S., Hennessy, S., Holick, C. N., Esposito, D. B., Gallagher, A. M., Bhullar, H., Strom, B. L., and , Determinants of saxagliptin use among patients with type 2 diabetes mellitus treated with oral anti-diabetic drugs, BMC Pharmacol Toxicol, vol. 16, p. 8, 2015.
H. Bricout, Torcel-Pagnon, L., Lecomte, C., Almas, M. F., Matthews, I., Lu, X., Wheelock, A., and Sevdalis, N., Determinants of shingles vaccine acceptance in the United Kingdom, PLoS One, vol. 14, p. e0220230, 2019.
M. Frisher, Short, D., and Bashford, J., Determining patient characteristics for decision analysis support systems using anonymized electronic patient records, Health Informatics J, vol. 16, pp. 49-57, 2010.
A. R. Tate, Martin, A. G., Murray-Thomas, T., Anderson, S. R., and Cassell, J. A., Determining the date of diagnosis–is it a simple matter? The impact of different approaches to dating diagnosis on estimates of delayed care for ovarian cancer in UK primary care, BMC Med Res Methodol, vol. 9, p. 42, 2009.
T. A. Hammad, Margulis, A. V., Ding, Y., Strazzeri, M. M., and Epperly, H., Determining the predictive value of Read codes to identify congenital cardiac malformations in the UK Clinical Practice Research Datalink, Pharmacoepidemiol Drug Saf, vol. 22, pp. 1233-8, 2013.
T. A. Hammad, McAdams, M. A., Feight, A., Iyasu, S., and Dal Pan, G. J., Determining the predictive value of Read/OXMIS codes to identify incident acute myocardial infarction in the General Practice Research Database, Pharmacoepidemiol Drug Saf, vol. 17, pp. 1197-201, 2008.
I. M. Carey, Cook, D. G., De Wilde, S., Bremner, S. A., Richards, N., Caine, S., Strachan, D. P., and Hilton, S. R., Developing a large electronic primary care database (Doctors' Independent Network) for research, Int J Med Inform, vol. 73, pp. 443-53, 2004.
V. Hammersley, Flint, R., Pinnock, H., and Sheikh, A., Developing and testing search strategies to identify patients with active seasonal allergic rhinitis in general practice, Prim Care Respir J, vol. 20, pp. 71-4, 2011.
K. K. Poppe, Doughty, R. N., Wells, S., Gentles, D., Hemingway, H., Jackson, R., and Kerr, A. J., Developing and validating a cardiovascular risk score for patients in the community with prior cardiovascular disease, Heart, vol. 103, pp. 891-892, 2017.
S. Harmala, O'Brien, A., Parisinos, C. A., Direk, K., Shallcross, L., and Hayward, A., Development and validation of a prediction model to estimate the risk of liver cirrhosis in primary care patients with abnormal liver blood test results: protocol for an electronic health record study in Clinical Practice Research Datalink, Diagn Progn Res, vol. 3, p. 10, 2019.
D. Yu, Jordan, K. P., Snell, K. I. E., Riley, R. D., Bedson, J., Edwards, J. J., Mallen, C. D., Tan, V., Ukachukwu, V., Prieto-Alhambra, D., Walker, C., and Peat, G., Development and validation of prediction models to estimate risk of primary total hip and knee replacements using data from the UK: two prospective open cohorts using the UK Clinical Practice Research Datalink, Ann Rheum Dis, 2018.
J. Hippisley-Cox and Coupland, C., Development and validation of risk prediction equations to estimate future risk of blindness and lower limb amputation in patients with diabetes: cohort study, Bmj, vol. 351, p. h5441, 2015.
J. Hippisley-Cox and Coupland, C., Development and validation of risk prediction equations to estimate future risk of heart failure in patients with diabetes: a prospective cohort study, BMJ Open, vol. 5, p. e008503, 2015.
A. A. Sultan, West, J., Grainge, M. J., Riley, R. D., Tata, L. J., Stephansson, O., Fleming, K. M., Nelson-Piercy, C., and Ludvigsson, J. F., Development and validation of risk prediction model for venous thromboembolism in postpartum women: multinational cohort study, Bmj, vol. 355, p. i6253, 2016.
R. A. Payne, Mendonca, S. C., Elliott, M. N., Saunders, C. L., Edwards, D. A., Marshall, M., and Roland, M., Development and validation of the Cambridge Multimorbidity Score, Cmaj, vol. 192, pp. E107-e114, 2020.
H. B. Mehta, Mehta, V., Tsai, C. L., Chen, H., Aparasu, R. R., and Johnson, M. L., Development and Validation of the RxDx-Dementia Risk Index to Predict Dementia in Patients with Type 2 Diabetes and Hypertension, J Alzheimers Dis, vol. 49, pp. 423-32, 2016.
C. J. D. Threapleton, Kimpton, J. E., Carey, I. M., DeWilde, S., Cook, D. G., Harris, T., and Baker, E. H., Development of a structured clinical pharmacology review for specialist support for management of complex polypharmacy in primary care, Br J Clin Pharmacol, 2020.
K. Wing, Douglas, I., Bhaskaran, K., Klungel, O. H., Reynolds, R. F., Pirmohamed, M., Smeeth, L., and van Staa, T. P., Development of predictive genetic tests for improving the safety of new medicines: the utilization of routinely collected electronic health records, Drug Discov Today, vol. 19, pp. 361-6, 2014.
S. Venkatesan, Myles, P. R., McCann, G., Kousoulis, A. A., Hashmi, M., Belatri, R., Boyle, E., Barcroft, A., van Staa, T. P., Kirkham, J. J., Van Tam, J. S. Nguyen, Williams, T. J., and Semple, M. G., Development of processes allowing near real-time refinement and validation of triage tools during the early stage of an outbreak in readiness for surge: the FLU-CATs Study, Health Technol Assess, vol. 19, pp. 1-132, 2015.
C. Becker, Brobert, G. P., Johansson, S., Jick, S. S., and Meier, C. R., Diabetes in patients with idiopathic Parkinson's disease, Diabetes Care, vol. 31, pp. 1808-12, 2008.
C. Carlson, Hornbuckle, K., DeLisle, F., Kryzhanovskaya, L., Breier, A., and Cavazzoni, P., Diabetes mellitus and antipsychotic treatment in the United Kingdom, Eur Neuropsychopharmacol, vol. 16, pp. 366-75, 2006.
M. Bodmer, Brauchli, Y. B., Jick, S. S., and Meier, C. R., Diabetes mellitus and the risk of cholecystectomy, Dig Liver Dis, vol. 43, pp. 742-7, 2011.
R. Alsaggaf, Pfeiffer, R. M., Wang, Y., St George, D. M. M., Zhan, M., Wagner, K. R., Amr, S., Greene, M. H., and Gadalla, S. M., Diabetes, Metformin, and Cancer Risk in Myotonic Dystrophy Type I, Int J Cancer, 2019.
C. Seliger, Ricci, C., Meier, C. R., Bodmer, M., Jick, S. S., Bogdahn, U., Hau, P., and Leitzmann, M. F., Diabetes, use of antidiabetic drugs, and the risk of glioma, Neuro Oncol, vol. 18, pp. 340-9, 2016.
C. Seliger, Meier, C. R., Becker, C., Jick, S. S., Proescholdt, M., Bogdahn, U., Hau, P., and Leitzmann, M. F., Diabetes, use of metformin, and the risk of meningioma, PLoS One, vol. 12, p. e0181089, 2017.
R. G. Gibbs, Newson, R., Lawrenson, R., Greenhalgh, R. M., and Davies, A. H., Diagnosis and initial management of stroke and transient ischemic attack across UK health regions from 1992 to 1996: experience of a national primary care database, Stroke, vol. 32, pp. 1085-90, 2001.
M. Pujades-Rodriguez, Assi, V., Gonzalez-Izquierdo, A., Wilkinson, T., Schnier, C., Sudlow, C., Hemingway, H., and Whiteley, W. N., The diagnosis, burden and prognosis of dementia: A record-linkage cohort study in England, PLoS One, vol. 13, p. e0199026, 2018.
M. Iwagami, Mansfield, K., Quint, J., Nitsch, D., and Tomlinson, L., Diagnosis of acute kidney injury and its association with in-hospital mortality in patients with infective exacerbations of bronchiectasis: cohort study from a UK nationwide database, BMC Pulm Med, vol. 16, p. 14, 2016.
S. Ratib, West, J., Crooks, C. J., and Fleming, K. M., Diagnosis of liver cirrhosis in England, a cohort study, 1998-2009: a comparison with cancer, Am J Gastroenterol, vol. 109, pp. 190-8, 2014.
M. T. Redaniel, Martin, R. M., Ridd, M. J., Wade, J., and Jeffreys, M., Diagnostic intervals and its association with breast, prostate, lung and colorectal cancer survival in England: historical cohort study using the Clinical Practice Research Datalink, PLoS One, vol. 10, p. e0126608, 2015.
N. Conrad, Judge, A., Canoy, D., Tran, J., O'Donnell, J., Nazarzadeh, M., Salimi-Khorshidi, G., Hobbs, F. D. R., Cleland, J. G., McMurray, J. J. V., and Rahimi, K., Diagnostic tests, drug prescriptions, and follow-up patterns after incident heart failure: A cohort study of 93,000 UK patients, PLoS Med, vol. 16, p. e1002805, 2019.
S. S. Jick, Kaye, J. A., and Jick, H., Diclofenac and acute myocardial infarction in patients with no major risk factors, Br J Clin Pharmacol, vol. 64, pp. 662-7, 2007.
T. Kendrick, Stuart, B., Newell, C., Geraghty, A. W., and Moore, M., Did NICE guidelines and the Quality Outcomes Framework change GP antidepressant prescribing in England? Observational study with time trend analyses 2003-2013, J Affect Disord, vol. 186, pp. 171-7, 2015.
B. M. Verdel, Souverein, P. C., Egberts, A. C., and Leufkens, H. G., Difference in risks of allergic reaction to sulfonamide drugs based on chemical structure, Ann Pharmacother, vol. 40, pp. 1040-6, 2006.
G. T. McInnes, The differences between ACE inhibitor-treated and calcium channel blocker-treated hypertensive patients, J Clin Hypertens (Greenwich), vol. 5, pp. 337-44, 2003.
D. Stolz, Kostikas, K., Loefroth, E., Fogel, R., Gutzwiller, F. S., Conti, V., Cao, H., and Clemens, A., Differences in COPD exacerbation risk between women and men: analysis from the UK Clinical Practice Research Datalink data, Chest, 2019.
N. C. Hazra, Dregan, A., Jackson, S., and Gulliford, M. C., Differences in Health at Age 100 According to Sex: Population-Based Cohort Study of Centenarians Using Electronic Health Records, J Am Geriatr Soc, vol. 63, pp. 1331-7, 2015.
H. E. Seaman, de Vries, C. S., and Farmer, R. D., Differences in the use of combined oral contraceptives amongst women with and without acne, Hum Reprod, vol. 18, pp. 515-21, 2003.
A. Gaitatzis, Purcell, B., Carroll, K., Sander, J. W., and Majeed, A., Differences in the use of health services among people with and without epilepsy in the United Kingdom: socio-economic and disease-specific determinants, Epilepsy Res, vol. 50, pp. 233-41, 2002.
L. A. Garcia Rodriguez, Varas, C., and Patrono, C., Differential effects of aspirin and non-aspirin nonsteroidal antiinflammatory drugs in the primary prevention of myocardial infarction in postmenopausal women, Epidemiology, vol. 11, pp. 382-7, 2000.
E. G. Tyrrell, Orton, E., Sayal, K., Baker, R., and Kendrick, D., Differing patterns in intentional and unintentional poisonings among young people in England, 1998-2014: a population-based cohort study, J Public Health (Oxf), vol. 39, pp. e1-e9, 2017.
[Page last reviewed 5 May 2020]