Liraglutide 3.0 mg in the treatment of adults with obesity and prediabetes using real-world UK data: A clinical evaluation of a multi-ethnic population.
Laurence J DobbieClaudia CoelhoFarah MgaiethKeisha ChauhanScott CampbellSumaya ShuriyeJoanna HollingtonSarah AppletonPiya Sen GuptaAlastair DuncanBarbara M McGowanPublished in: Clinical obesity (2024)
UK guidelines recommend liraglutide 3.0 mg in adults treated within specialist weight management services with BMI ≥35 kg/m 2 , prediabetes and high cardiovascular disease risk. We aimed to clinically evaluate liraglutide 3.0 mg in specialist weight management services. We evaluated liraglutide 3.0 mg in weight management services at Guys and St Thomas' NHS Foundation Trust. Objective body weight (BW) was measured at baseline and 4 months, allowing classification as 'responders' (≥5% BW reduction) and 'non-responders' (<5% BW reduction). One hundred and twenty-one patients were evaluated. At 4 months, 76.0% attended follow-up (82.6% responders, 17.4% non-responders); BW (-8.6 kg, 95%CI:-9.8, -7.4 kg), BMI (-3.2 kg/m 2 , 95%CI: -3.6, -2.8) and %-BW (-6.6%, IQR: -8.8%, -5.2%) significantly reduced. In responders, HbA1c reduced by -5.0 mmol/mol (IQR: -7.0. -4.0 mmol/mol). In responders BW continued to reduce up to 12 months (4 m: -10.2 kg, p < .0001; 6 m: -15.6 kg, p < .0001; 9 m: -16.5 kg, p < .0001; 12 m: -16.7 kg, p < .01). Those of Black African and Caribbean ethnicity experienced less BW loss than those of white ethnicity (4.12 kg, p = .017) and had a greater attrition rate. In adults with obesity and prediabetes who are treated within specialist weight management services, liraglutide 3.0 mg reduces BW and HbA1c. Those of Black African and Caribbean ethnicity experienced less BW reduction and greater attrition at 4 months. Further evaluation of the ethnic differences in response to obesity pharmacotherapy is required.
Keyphrases
- weight gain
- weight loss
- body weight
- body mass index
- healthcare
- primary care
- cardiovascular disease
- type diabetes
- insulin resistance
- metabolic syndrome
- physical activity
- palliative care
- end stage renal disease
- newly diagnosed
- machine learning
- chronic kidney disease
- patient safety
- deep learning
- prognostic factors
- adipose tissue
- coronary artery disease
- cardiovascular events
- health insurance