Research using CPRD data has informed drug safety guidance and clinical practice and resulted in over 2,300 peer-reviewed publications.

The CPRD bibliography is updated on a monthly basis (last updated 4 December 2019) 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, 193 pages)


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Author [ Title(Desc)] Type Year
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J. Wilding, Bailey, C., Rigney, U., Blak, B., Kok, M., and Emmas, C., Dapagliflozin therapy for type 2 diabetes in primary care: Changes in HbA1c, weight and blood pressure over 2 years follow-up, Prim Care Diabetes, vol. 11, pp. 437-444, 2017.
S. C. Denaxas, George, J., Herrett, E., Shah, A. D., Kalra, D., Hingorani, A. D., Kivimaki, M., Timmis, A. D., Smeeth, L., and Hemingway, H., Data resource profile: cardiovascular disease research using linked bespoke studies and electronic health records (CALIBER), Int J Epidemiol, vol. 41, pp. 1625-38, 2012.
E. Herrett, Gallagher, A. M., Bhaskaran, K., Forbes, H., Mathur, R., Van Staa, T., and Smeeth, L., Data Resource Profile: Clinical Practice Research Datalink (CPRD), Int J Epidemiol, vol. 44, pp. 827-36, 2015.
A. Wolf, Dedman, D., Campbell, J., Booth, H., Lunn, D., Chapman, J., and Myles, P., Data resource profile: Clinical Practice Research Datalink (CPRD) Aurum, Int J Epidemiol, 2019.
R. A. Charlton, Cunnington, M. C., de Vries, C. S., and Weil, J. G., Data resources for investigating drug exposure during pregnancy and associated outcomes: the General Practice Research Database (GPRD) as an alternative to pregnancy registries, Drug Saf, vol. 31, pp. 39-51, 2008.
M. C. Gulliford, Charlton, J., Rudd, A., Wolfe, C. D., and Toschke, A. M., Declining 1-year case-fatality of stroke and increasing coverage of vascular risk management: population-based cohort study, J Neurol Neurosurg Psychiatry, vol. 81, pp. 416-22, 2010.
R. Ravindrarajah, Dregan, A., Hazra, N. C., Hamada, S., Jackson, S. H. D., and Gulliford, M. C., Declining blood pressure and intensification of blood pressure management among people over 80 years: cohort study using electronic health records, J Hypertens, vol. 35, pp. 1276-1282, 2017.
R. Howell-Jones, Soldan, K., Wetten, S., Mesher, D., Williams, T., Gill, O. N., and Hughes, G., Declining genital Warts in young women in england associated with HPV 16/18 vaccination: an ecological study, J Infect Dis, vol. 208, pp. 1397-403, 2013.
T. Fundament, Eldridge, P. R., Green, A. L., Whone, A. L., Taylor, R. S., Williams, A. C., and Schuepbach, W. M., Deep Brain Stimulation for Parkinson's Disease with Early Motor Complications: A UK Cost-Effectiveness Analysis, PLoS One, vol. 11, p. e0159340, 2016.
M. Frischer, Heatlie, H., Chapman, S., and Millson, D., Defining the spectrum of appropriate prescribing: implications for effective medicines management, International Journal of Pharmaceutical Medicine, vol. 14, pp. 17-21, 2000.
C. J. Crooks, Card, T. R., and West, J., Defining upper gastrointestinal bleeding from linked primary and secondary care data and the effect on occurrence and 28 day mortality, BMC Health Serv Res, vol. 12, p. 392, 2012.
A. Douros, Dell'Aniello, S., Dehghan, G., Boivin, J. F., and Renoux, C., Degree of serotonin reuptake inhibition of antidepressants and ischemic risk: A cohort study, Neurology, vol. 93, pp. e1010-e1020, 2019.
S. K. Paul, Klein, K., Thorsted, B. L., Wolden, M. L., and Khunti, K., Delay in treatment intensification increases the risks of cardiovascular events in patients with type 2 diabetes, Cardiovasc Diabetol, vol. 14, p. 100, 2015.
C. S. Arhi, Markar, S., Burns, E. M., Bouras, G., Bottle, A., Hanna, G., Aylin, P., Ziprin, P., and Darzi, A., Delays in referral from primary care are associated with a worse survival in patients with esophagogastric cancer, Dis Esophagus, 2019.
S. Turnbull, Ward, A., Treasure, J., Jick, H., and Derby, L., The demand for eating disorder care. An epidemiological study using the general practice research database, Br J Psychiatry, vol. 169, pp. 705-12, 1996.
S. Landis, Suruki, R., Maskell, J., Bonar, K., Hilton, E., and Compton, C., Demographic and Clinical Characteristics of COPD Patients at Different Blood Eosinophil Levels in the UK Clinical Practice Research Datalink, Copd, vol. 15, pp. 177-184, 2018.
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.
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.
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.
[Page last reviewed 6 December 2019]