A Descriptive Analysis of Demographic, Co-Morbid and Prescribing Data from the UK CPRD in People with Type 2 Diabetes and Cardiovascular Conditions

Moderator

Patrick Muller, MSc, PhD, National Institute for Health and Care Excellence (NICE), London, United Kingdom

Speakers

Muksitur Rahman, United Kingdom; James Hawkins; Jonathan Wray, BSc, PhD, NICE, Manchester, United Kingdom; Lesley Owen, London, United Kingdom

OBJECTIVES: Newer therapies in type 2 diabetes mellitus (T2DM) that have demonstrable cardiovascular (CV) benefits have changed treatment goals from simply maintaining glycaemic control to also preventing future CV events. Prior economic evaluations in people with T2DM have modelled the overall population. Since most validated T2DM models use time-varied changes in risk factors to predict occurrences of CV events among others, the NICE T2DM guideline update stratified people into groups whose risk factors were expected to differ to better capture treatment effects between differing risk profiles.
METHODS: Data from the Clinical Practice Research Datalink (CPRD) Aurum was linked to the Hospital Episode Statistics Admitted Patient Care (HES APC) dataset. The cross-sectional date was set as 1st September 2023. People with T2DM were categorised along five comorbidities: atherosclerotic cardiovascular disease (asCVD), chronic kidney disease (CKD) stages 1-3, CKD stage 4, heart failure (HF) and high risk of cardiovascular disease (hrCVD). This paper presents a descriptive summary across cohorts.
RESULTS: People with T2DM mostly had hrCVD (64%), followed by CKD 1-3 (30%) and asCVD (28%). Glycosylated haemoglobin and body mass index were similar across cohorts. People with asCVD or hrCVD were more likely to smoke and had higher systolic blood pressure. Lower limb ulceration, established kidney disease and diabetic retinopathy were all higher in people with HF. A third of people with asCVD, HF or hrCVD were not currently prescribed any glucose-lowering therapy, falling to 27% and 28% in CKD 1-3 and CKD 4, respectively. Metformin was most frequently prescribed, followed by SGLT-2 inhibitors, DPP-4 inhibitors and sulfonylureas.
CONCLUSIONS: Differences in demographics, risk factors and comorbidities were observed between groups, suggesting that it would be more appropriate to account for these differences in future health economic modelling exercises as whole population models may underestimate the CV-related benefits of newer treatments in certain sub-populations.

Conference/Value in Health Info

2025-05, ISPOR 2025, Montréal, Quebec, CA

Value in Health, Volume 28, Issue S1

Code

EE182

Topic

Economic Evaluation

Disease

SDC: Cardiovascular Disorders (including MI, Stroke, Circulatory), SDC: Diabetes/Endocrine/Metabolic Disorders (including obesity)

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