Blood pressure-lowering efficacy of antihypertensive drugs and their combinations: a systematic review and meta-analysis of randomised, double-blind, placebo-controlled trials.
Summary
Across 484 randomized trials (104,176 participants), standard-dose monotherapy reduced systolic BP by 8.7 mm Hg (each dose doubling added 1.5 mm Hg), while one-standard-dose dual combinations reduced systolic BP by 14.9 mm Hg (each doubling added 2.5 mm Hg). Efficacy decreased with lower baseline BP, and a validated model accurately predicted combination effects, enabling therapy to be classified into low, moderate, and high intensity.
Key Findings
- Standard-dose monotherapy reduced systolic BP by 8.7 mm Hg; each dose doubling added 1.5 mm Hg.
- One-standard-dose dual combinations reduced systolic BP by 14.9 mm Hg; doubling both doses added 2.5 mm Hg.
- Lower baseline systolic BP reduced observed treatment efficacy by 1.3 mm Hg per 10 mm Hg decrease.
- Predictive model for combinations showed strong external validation (r=0.76).
Clinical Implications
Use intensity-based targets to select single or dual agents and titrate doses to achieve desired mm Hg reductions; anticipate smaller effects in lower baseline BP; employ the model to design efficient stepwise combination therapy.
Why It Matters
Provides robust, generalizable dose–response and combination-effect estimates with a validated predictive model, directly informing rational antihypertensive regimen selection.
Limitations
- Short follow-up durations (mean 8.6 weeks) limit long-term extrapolation
- Fixed-effects approach and between-trial heterogeneity may influence pooled estimates; safety outcomes not primary focus
Future Directions
Incorporate long-term outcomes, adverse effects, and diverse populations to refine intensity-based treatment algorithms and integrate into decision-support tools.
Study Information
- Study Type
- Systematic Review/Meta-analysis
- Research Domain
- Treatment
- Evidence Level
- I - Synthesis of randomized, double-blind, placebo-controlled trials with model validation
- Study Design
- OTHER