Pragmatic vs Explanatory Trials: A Quantitative Analysis

Abstract
A Practical Guide: Get 500 Years of Clinical Research in 20, Avoid the Apocalypse, and Make Humanity Filthy Rich by Giving Papers
Keywords

war-on-disease, 1-percent-treaty, medical-research, public-health, peace-dividend, decentralized-trials, dfda, dih, victory-bonds, health-economics, cost-benefit-analysis, clinical-trials, drug-development, regulatory-reform, military-spending, peace-economics, decentralized-governance, wishocracy, blockchain-governance, impact-investing

What are Pragmatic Trials?

Pragmatic trials are designed to test interventions in real-world conditions, focusing on:

Key Differences at a Glance

Metric Pragmatic Trials (e.g., RECOVERY) Traditional Explanatory Trials
Cost per Trial Lower due to existing infrastructure $48-225 million
Time to Results Weeks to months 5-7 years average
Participants Large (e.g., 47,000+ in RECOVERY) Typically 500-3000
Implementation Speed Hours to days Months to years
Patient Population Diverse, real-world Highly selected
Setting Routine clinical practice Specialized research centers
Generalizability High Limited

Cost Analysis

Traditional Explanatory Trials

  • Average phase costs (source):
    • Phase 1: $4 million
    • Phase 2: $13 million
    • Phase 3: $20 million
  • Per-patient costs vary by therapeutic area:

Pragmatic Trials (RECOVERY Example)

  • Cost savings of 68-78% compared to traditional trials
  • Utilized existing healthcare infrastructure
  • Minimal additional staff costs
  • Reduced monitoring costs
  • Simple data collection systems

Speed and Efficiency

RECOVERY Trial Metrics

Traditional Trial Metrics

Clinical Impact

RECOVERY Trial

Traditional Trials

Advantages of Pragmatic Trials

  1. Better Generalizability

    • Results apply to broader patient populations
    • Findings directly relevant to routine clinical practice
    • Higher external validity
  2. Resource Efficiency

    • Uses existing healthcare infrastructure
    • Lower per-patient costs
    • Faster recruitment and completion
  3. Implementation Speed

    • Rapid translation to clinical practice
    • Immediate real-world validation
    • Reduced lag between evidence and practice
  4. Statistical Power

    • Larger sample sizes possible
    • More diverse patient populations
    • Better representation of real-world outcomes