Hill's considerations are not causal criteria.

Area of Science:

• Epidemiology
• Causal Inference
• Biostatistics

Background:

• Sir Austin Bradford Hill's criteria, proposed 60 years ago, are a landmark in interpreting epidemiologic evidence.
• These criteria are frequently misused as a checklist for scoring and summing, despite causal inference being algorithmically unattainable.
• Distinguishing statistical associations from causal effects was a key contribution of Hill's work.

Purpose of the Study:

• To critique the misuse of Hill's criteria in epidemiologic evidence interpretation.
• To highlight advancements in causal inference methods beyond Hill's original considerations.
• To emphasize that causal inference is an indirect process, not a checklist outcome.

Main Methods:

• Critique of traditional interpretation of Hill's considerations.
• Introduction of modern quantitative bias analysis to directly assess confounding and other biases.
• Emphasis on triangulation and exploring informative inconsistencies across studies.

Main Results:

• Hill's criteria are often misapplied, leading to flawed causal assessments.
• Newer methods like quantitative bias analysis provide more explicit and effective causal inference.
• Causal inference is strengthened by withstanding challenges from competing explanations, not by checklist scoring.

Conclusions:

• Causal inference in epidemiology has evolved significantly beyond Hill's original guidelines.
• Modern approaches focus on directly addressing biases and rigorously testing alternative explanations.
• A causal connection is gradually established through robust scientific challenge, not by fulfilling a list of criteria.