How to evaluate peptide evidence without hype

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1. Which evidence most directly tests cause and effect for an intervention when well designed and feasible?

A randomized controlled human trialA receptor diagramAn uncontrolled anecdoteA product page

2. A headline says a peptide 'increased a biomarker by 40%'. What should you ask next?

What was studied, what was the comparator, and does that biomarker map to the claimed outcome?Is 40% always clinically meaningful?Can the number be used as a dose?Which brand sells it?

3. Which statement is strongest?

P < 0.05 proves the effect is importantEffect estimate, confidence interval and outcome importance should be considered togetherOnly the P value mattersConfidence intervals are optional

4. An observational human study finds an association. What can it usually establish most directly?

An association that may be influenced by confoundingGuaranteed causationRegulatory approvalThe correct amount to use

5. What is the anti-hype rule?

Never make the conclusion stronger than the design, population or endpoint allowsIgnore all early researchOnly discuss approved medicinesTreat every positive result as proof

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