作者
Pedro Cardoso, Katie G Young, Anand TN Nair, Rhian Hopkins, Andrew P McGovern, Eram Haider, Piyumanga Karunaratne, Louise Donnelly, Bilal A Mateen, Naveed Sattar, Rury R Holman, Jack Bowden, Andrew T Hattersley, Ewan R Pearson, Angus G Jones, Beverley M Shields, Trevelyan J McKinley, John M Dennis, MASTERMIND consortium
发表日期
2024/2/22
期刊
Diabetologia
页码范围
1-15
出版商
Springer Berlin Heidelberg
简介
Aims/hypothesis
A precision medicine approach in type 2 diabetes could enhance targeting specific glucose-lowering therapies to individual patients most likely to benefit. We aimed to use the recently developed Bayesian causal forest (BCF) method to develop and validate an individualised treatment selection algorithm for two major type 2 diabetes drug classes, sodium–glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1-RA).
Methods
We designed a predictive algorithm using BCF to estimate individual-level conditional average treatment effects for 12-month glycaemic outcome (HbA1c) between SGLT2i and GLP1-RA, based on routine clinical features of 46,394 people with type 2 diabetes in primary care in England (Clinical Practice Research Datalink; 27,319 for model development, 19,075 for hold-out validation), with additional external validation in 2252 people …
学术搜索中的文章
P Cardoso, KG Young, ATN Nair, R Hopkins… - Diabetologia, 2024