#393 ‒ AMA #85: A guide to medications and supplements: determining what to take, what to skip, and how to know if they're working for you
In AMA #85, Peter Attia, MD, explores critical thinking about medications and supplements, emphasizing defining health problems with actionable metrics, classifying interventions by purpose, and evaluating evidence and risks. He highlights why skepticism is crucial, especially for 'optimization' claims, to make informed personal health decisions.
Deep Dive Analysis
10 Topic Outline
Introduction to AMA 85: Medications and Supplements
Defining Health Problems for Effective Intervention
Importance of Actionable Metrics, Thresholds, and Timelines
The Counterfactual: Consequences of Doing Nothing
Classifying Intervention Purpose and Evidence Standards
Evidence Thresholds for Disease Treatment
Evidence Thresholds for Symptom Relief
Evidence Thresholds for Risk Reduction
Evidence Thresholds for Optimization and Longevity Interventions
Avoiding Confusion in Evidence Tiers
4 Key Concepts
Actionable Problem Definition
This is a framework for defining a health problem with specific, measurable metrics, a target threshold, and a timeline, rather than vague goals. It ensures interventions can be objectively evaluated and prevents self-deception.
Counterfactual
The hypothetical outcome of a situation if no intervention is taken. Considering the counterfactual helps assess whether a problem truly warrants intervention by understanding its natural progression or potential downstream consequences.
Intervention Job Classification
A framework categorizing medications or supplements into four purposes: disease treatment, symptom relief, risk reduction, or optimization. This classification is critical for determining the appropriate evidence standard and acceptable risk for any given intervention.
Validated Surrogate Biomarker
A measurable indicator that is not the direct clinical endpoint but is strongly and reliably correlated with it. It allows for the evaluation of intervention effectiveness when hard outcomes are difficult to measure, such as ApoB for cardiovascular risk.
3 Questions Answered
One should define problems with actionable metrics, specific thresholds, and a timeline, also considering the counterfactual (what happens if nothing is done) to avoid vague goals and self-deception.
The 'job' (disease treatment, symptom relief, risk reduction, or optimization) dictates the evidence bar and acceptable risk; more serious problems warrant higher evidence and potentially more risk, while speculative goals require less tolerance for downside.
Supplements often fall into the 'optimization' category, where error rates are highest, expected effects are small, claims are mechanistic, and objective measurement is difficult, making self-deception common.
8 Actionable Insights
1. Define Problems Actionably
Instead of vague goals like ‘be healthier,’ define problems with specific, measurable metrics, a target threshold, and a timeline. This approach helps prevent self-deception and ensures interventions can be objectively evaluated.
2. Consider the Counterfactual
Before starting any intervention, ask what would happen if you did nothing. This helps separate real problems that meaningfully increase risk or reduce quality of life from those that merely feel actionable.
3. Classify Intervention’s ‘Job’
Categorize the purpose of a medication or supplement into one of four buckets: disease treatment, symptom relief, risk reduction, or optimization. This classification is crucial for determining the appropriate evidence threshold and acceptable risk.
4. Demand Strong Evidence for Disease Treatment
For interventions aimed at treating a disease, require strong evidence such as hard outcome trials or well-validated surrogate endpoints. You may be willing to accept more downside risk due to the seriousness of the underlying problem.
5. Prioritize Lived Benefit for Symptom Relief
When the goal is symptom relief, focus on whether the person actually feels or functions better. While acknowledging placebo risk and safety unknowns, a low-downside intervention that improves subjective symptoms can be a reasonable trade-off.
6. Require High Evidence for Risk Reduction
For interventions focused on risk reduction, which often treat conditions a person cannot feel, demand high-quality evidence like hard outcomes or very well-validated surrogate markers (e.g., ApoB), rather than vague inflammatory markers.
7. Approach Optimization with Skepticism
For ‘optimization’ interventions, especially when starting from a healthy baseline, maintain a high degree of skepticism. Claims are often mechanistic, expected effects are small, and objective measurement is difficult, making self-deception common.
8. Be Skeptical of Longevity Interventions
Many so-called ’longevity interventions’ are actually optimizations masquerading as risk reductions. They often borrow the language of prevention but lack strong evidence, requiring increased skepticism regarding both efficacy and safety.
4 Key Quotes
The right question is whether a specific intervention makes sense for a specific person with a specific problem.
Peter Attia
Do not start with the molecule. Start with the problem. Define tightly enough that you could actually be proven wrong.
Peter Attia
If the problem is vague, almost anything can look like it helped.
Peter Attia
Most of the longevity interventions are really really optimizations masquerading as risk reductions.
Peter Attia