Heterogeneity of Treatment Effects for Intensive Blood Pressure Therapy by Individual Components of FRS: An Unsupervised Data-Driven Subgroup Analysis in SPRINT and ACCORD

Some patients with type 2 diabetes may benefit from intensive glycaemic and blood pressure control: A post-hoc machine learning analysis of ACCORD trial data

AIM

The action to control cardiovascular risk in diabetes (ACCORD) trial showed a neutral average treatment effect of intensive blood glucose and blood pressure (BP) controls in preventing major adverse cardiovascular events (MACE) in individuals with type 2 diabetes. Yet, treatment effects across patient subgroups have not been well understood. We aimed to identify patient subgroups that might benefit from intensive glucose or BP controls for preventing MACE.

MATERIALS AND METHODS

As a post-hoc analysis of the ACCORD trial, we included 10 251 individuals with type 2 diabetes. We applied causal forest and causal tree models to identify participant characteristics that modify the efficacy of intensive glucose or BP controls from 68 candidate variables (demographics, comorbidities, medications and biomarkers) at the baseline. The exposure was (a) intensive versus standard glucose control [glycated haemoglobin (HbA1c) <6.0% vs. 7.0%-7.9%], and (b) intensive versus standard BP control (systolic BP <120 vs. <140 mmHg). The primary outcome was MACE.

RESULTS

Compared with standard glucose control, intensive one reduced MACE in those with baseline HbA1c <8.5% [relative risk (RR): 0.79, 95% confidence interval (CI): 0.67-0.93] and those with estimated glomerular filtration rate ≥106 ml/min/1.73 m2 (RR: 0.74, 95% CI: 0.55-0.99). Intensive BP control reduced MACE in those with normal high-density lipoprotein levels (women >55 mg/dl, men >45 mg/dl; RR: 0.51, 95% CI: 0.34-0.74). Risk reductions were not significant in other patient subgroups.

CONCLUSIONS

Our findings suggest heterogeneous treatment effects of intensive glucose and BP control and could provide biomarkers for future clinical trials to identify more precise HbA1c and BP treatment goals for individualized medicine.