Presentation (CTI)

OBJECTIVES: Conventional hypertension models are structurally incomplete because they rely primarily on office-based blood pressure measurement (OBPM) and do not fully capture the multifaceted effects of treatment. A single OBPM may not accurately reflect a patient’s underlying disease burden, whereas 24-hour ambulatory blood pressure monitoring (ABPM) provides a more comprehensive assessment and is a stronger predictor of cardiorenal outcomes. Furthermore, some antihypertensives may improve renal health beyond BP reduction, which is not captured by previous models. The baxdrostat hypertension (BAX-HTN) model addresses these limitations by incorporating treatment effects on multiple prognostic risk factors, including OBPM, ABPM, and urinary albumin-to-creatinine ratio (uACR), to quantify long-term impact of different hypertension management strategies.
METHODS: We developed a patient-level microsimulation that dynamically updates systolic BP (SBP), uACR, estimated glomerular filtration rate (eGFR), comorbidities, and treatment tolerability. The model’s structure prevents double-counting treatment effects. Relative risks associated with SBP reductions are applied to risk equations to predict outcomes (including event incidence, time-to-event and life years) for interventions. The impact of including additional risk factors (ABPM, uACR) on outcome predictions was assessed for patients receiving standard-of-care (SoC) or baxdrostat plus SoC over a lifetime time horizon.
RESULTS: Compared with predictions based exclusively on OBPM, considering additional risk factors (ABPM, uACR) results in decreased time-to-event across all events, resulting in fewer event-free years (6.11 vs. 6.08 years) and fewer total-life years (16.81 vs. 16.22 years) for patients receiving SoC. For patients receiving baxdrostat, including ABPM and uACR increases estimated time-to-event across most events, and increases estimates of event-free (6.40 vs. 6.73 years) and total life years (17.04 vs. 17.32 years, respectively) compared with OBPM alone.
CONCLUSIONS: Meaningful modelling requires the inclusion of key predictive risk factors and treatment effects. The Bax-HTN model more accurately reflects the health consequences of hypertension and provides a fuller assessment of the value of effective management.