The honey finding is a good example of a comparison that is usually read the wrong way round.
The primary analysis was null: honey and pharmacological antitussives performed comparably on most endpoints. Read as an efficacy question, that is an unremarkable result. Read as a decision, it settles the matter — because the two options are not symmetric. One carries the documented adverse-effect profile of paediatric antitussives; the other is honey, costs almost nothing, and is already in the house.
The habit generalises. When two treatments differ substantially in harm, cost or burden, a demonstration of equivalence favours the safer one and no superiority trial is needed. The mistake is to keep prescribing the riskier option because the safer one was never shown to be better — which inverts where the burden of proof should sit.
The qualifier is the one that matters clinically here: not under twelve months, ever.
- Equivalence favours the option with less harm, cost or burden
- Do not require superiority from the safer arm before switching to it
- Check the comparison is genuinely asymmetric before applying this
- Ask what the riskier option is actually buying if outcomes match
- For honey specifically: never under twelve months
The statistics, in plain English
A non-significant difference between treatments is not proof they are equivalent; that requires an equivalence or non-inferiority design with a margin set in advance. But when one arm carries known harm, the asymmetry does the work a formal equivalence test would: you are no longer asking which is better, only whether the riskier one is enough better to justify itself.
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