A headline can be true and still lead to the wrong decision. “Cuts risk in half” says nothing about how likely the event was, what treatment asks of you, or whether the result applies to your life.
Ask: compared with what?
Symptoms fluctuate. People often start treatment at a low point, then improve as time passes or other things change. A testimonial cannot separate those effects. A fair comparison can help, but its choice matters: beating no treatment is a different achievement from improving on established care. Ask whether the participants, dose and follow-up resemble the decision you face.
Measure what matters
A changed blood test, scan or biological-age score is a clue, not automatically proof that someone lives longer or feels better. Check whether the study measured the benefit being advertised. A small P value cannot tell you whether an improvement is noticeable or worth its harms. Look at the size of the effect and its confidence interval, which helps show how precise the estimate is.
Follow the missing people
A success rate can flatter a treatment if people who stop because of adverse effects disappear from the account. Ask how many entered, how many finished and how missing outcomes were handled. Transparent reporting makes a claim easier to assess; it does not itself prove that a treatment works.
Make uncertainty useful
One impressive study is a beginning. Look for agreement across well-conducted research and effects large enough to matter to you. The decision also includes burden: adverse effects, cost, appointments and effort. Bring the question to a clinician in practical terms: “For someone like me, how much benefit is likely, over what time, and what would make us reconsider?”