Kidney disease is an important and serious problem that is commonly associated with diabetes and hypertension. The relationship between kidney and cardiovascular diseases are increasingly being recognised as leading cause of severe illness and these diseases should be detected and treated in early stages in order to prevent complications and deaths. In a time of emerging treatment options that may offer benefits to patients with kidney disease, there is an increasing need to understand the characteristics of patients affected, those who might be eligible to receive these treatments and the impact of the choice of medications used to treat these patients in clinical practice. The results from recently concluded clinical trials are very encouraging and show new treatments reduced the progression of heart failure as well as kidney deterioration in patients with and without diabetes. However, as only limited number of people can be enrolled in trials due to the rigorous selection criteria, the findings may not be generalised across all populations. In addition there is very sparse information on the characteristics of specific subgroup populations, particularly people who may be at a higher risk of experiencing chronic kidney disease. Therefore, this study will use administrative healthcare records to describe populations of patients with chronic kidney disease in order to understand the demographic and clinical characteristics, treatment patterns, drug utilisation and the change in kidney disease progression before and after initiation of the new treatments.
Using a cohort of patients with a diagnosis for chronic kidney disease (CKD), we aim to describe and compare the characteristics of patients who initiated treatment with dapagliflozin, a sodium-glucose co-transporter-2 (SGLT-2) inhibitor over time. This include the epidemiology of dapagliflozin and other SGLT-2 inhibitor treatment uptake in various population groups, description of the treatment patterns and the impact of the choice of medications used to treat these patients on clinical outcomes. This study will utilise the CPRD Aurum database and the study period will begin on 1 January 2015 until the last GP’s collection day. Each of the outcome measures of interest will be described separately. Patient characteristics and health care resource use will be described for the study population and the results will be summarised using descriptive statistics. Event rates and 95% confidence intervals will be reported as incidence rates. Survival distributions utilising Kaplan-Meir method will describe time to treatment initiation or treatment substitution from the date of licence approval or latest consultation after the licence approval date for dapagliflozin use for CKD. Relative risks and risk factors associated with clinical outcomes will be estimated using Cox proportional hazard regression. In addition, we aim to further evaluate the treatment pathways of the patients to describe their health resource use including GP consultations, laboratory tests, medication, referrals to specialist and hospital admissions. Such evidence will be used to highlight any unmet treatment needs and inform the evidence gap in this area.
• Baseline demographic and clinical characteristics
• Time to dapagliflozin treatment initiation and factors associated with treatment initiation
• Changes in the estimated glomerular filtration rate (eGFR) and albumin-creatinine ratio (ACR) measurements over time
• Descriptions of medication issues and treatment change patterns over time
• Time to clinical outcomes including cardiovascular, kidney and mortality outcomes
• Outcomes stratified by baseline demographic, disease, laboratory tests measurements, treatment-related factors as well as subgroup populations.
Jil Billy Mamza - Chief Investigator - AstraZeneca Ltd - UK Headquarters
He Gao - Corresponding Applicant - AstraZeneca Ltd - UK Headquarters
Alexander Gueret-Wardle - Collaborator - AstraZeneca Ltd - UK Headquarters
Benjamin Heywood - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Christopher Morgan - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Elgan Mathias - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Leah Fisher - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Ruiqi Zhang - Collaborator - AstraZeneca Ltd - UK Headquarters
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation