Can prediction models individualize the projected risk and benefit of intensive versus standard blood pressure control in patients with hypertension?
Prediction models can help tailor the intensity of blood pressure control by estimating individualized risks of MACE/death versus treatment-related serious adverse events.
BACKGROUND: In SPRINT (Systolic Blood Pressure Intervention Trial), patients with hypertension and high cardiovascular risk treated with intensive blood pressure (BP) control (<120 mm Hg) had fewer major adverse cardiovascular events (MACE) and deaths but higher rates of treatment-related serious adverse events (SAE) than patients randomized to standard BP control (<140 mm Hg). However, the degree of benefit or harm for an individual patient could vary because of heterogeneity in treatment effect. METHODS AND RESULTS: Using patient-level data from 9361 randomized patients in SPRINT, we developed models to predict risk for MACE or death and treatment-related SAE to allow for individualized BP treatment goals based on each patient's projected risk and benefit of intensive versus standard BP control. Models were internally validated using bootstrap resampling and externally validated on 4741 patients from the ACCORD-BP (The Action to Control Cardiovascular Risk in Diabetes blood pressure) trial. Among 9361 SPRINT patients, 755 patients (8.1%) had a MACE or death event and 338 patients (3.6%) had a treatment-related SAE during a median follow-up of 3.3 years. The MACE/death and the SAE model had C statistics of 0.72 and 0.70, respectively, in the derivation cohort and 0.69 and 0.65 in ACCORD. The MACE/death model had 10 variables including treatment interactions with age, baseline systolic BP, and diastolic BP, and the SAE model had 8 variables including treatment interaction with number of BP medications. Intensive BP treatment was associated with a mean 2.2±2.6% lower risk of MACE/death compared with standard treatment (range, 20.7% lower risk to 19.6% greater risk among individual patients) and a mean 2.2±1.2% higher risk for SAEs (range, 0.5%-15.8% more harm in individual patients). CONCLUSIONS: To translate the findings from SPRINT to clinical practice, we developed prediction models to tailor the intensity of BP control based on the projected risk and benefit for each unique patient. This approach should be prospectively tested to better engage patients in shared medical decision making and to improve outcomes. CLINICAL TRIAL REGISTRATION: URL: https://clinicaltrials.gov. Unique identifier: NCT01206062.
Patel et al. (Sat,) studied this question.