- Published
- Updated
Publications may use the same product-family name while device versions or clinically important features differ. Combining their data into one result can conceal different effects. Assess relevance of version differences before using the family name as the basis for pooling.
Scope of the decision
Changes do not all have equal importance. Consider deployment method, material, algorithm or interface differences in context. Explain the assumptions behind evidence grouping. Statistically similar results do not by themselves demonstrate that clinical or technical differences are unimportant.
Worked review
For example, three papers assess one device family, but one uses an earlier measurement algorithm and two use the current version. Before calculating a single average, the team examines how the algorithm could affect the endpoint. It retains version distinctions and explains the scientific rationale and uncertainty of any proposed combination.
Practical checks
- Record identifiable device versions and important characteristics for each dataset.
- Assess links between version differences and the analysed outcome with suitable expertise.
- Keep meaningful subgroup differences visible beside any combined estimate.
Acceptance and limits
Acceptance requires a grouping or separation decision justified by the data and intended question. If a publication does not identify the version, do not present an assumption as fact. Missing version information can limit evidence weight and applicability to the device concerned.
Frequently asked questions
- Is the same trade name sufficient?
- No. Important characteristics may change while the name remains unchanged.
- Do similar results prove versions are equivalent?
- Not alone. Equivalence and clinical interpretation need their own appropriately scoped assessments.