Teams often treat CDISC conformance as something that happens at the end of a study: a conversion step between a clean database and a submission package. In practice, the cost and risk of that step are mostly decided much earlier, in how data are collected and defined.
Collection design sets the ceiling
CDASH exists because collection and tabulation are connected. A case report form that captures a concept in a form the standard can't easily represent creates mapping decisions that someone must later defend. Aligning forms with CDASH-style conventions where it makes sense removes a class of avoidable derivations.
Write the mapping specification as a design document
An SDTM mapping specification is more than a programming instruction. It is the record of how each collected item becomes a tabulated one. When it is drafted early and reviewed with data management and biostatistics, gaps surface while they are still cheap to fix.
- Identify non-standard variables early and decide whether they belong in SUPP-- or a custom domain.
- Agree controlled terminology sources and versions up front.
- Record derivation logic in plain language before it is programmed.
ADaM should follow the analysis, not the other way round
Analysis datasets should be shaped by the statistical analysis plan. If the plan is vague about populations, baseline definitions or handling of missing data, the ADaM design will be too, and the ambiguity will resurface as late-stage rework.
Metadata is a deliverable
Define-XML and the reviewer's guide are how a reviewer understands your data. Treating them as an afterthought is a common reason a technically conformant package is still hard to navigate.
Conformance checking tools are valuable, but they verify rules, not judgement. The goal is a package that is both conformant and comprehensible, and that is largely achieved by the decisions made before the data exist.
This article is for general information only and is not medical, regulatory or legal advice.
← All insights