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After death, a functional, symptom or quality-of-life score differs from an ordinary unobserved assessment. Classifying the situation only as a missing questionnaire can leave the scientific meaning of the endpoint unclear and weaken interpretation.
Define the question and assumptions
Discuss the clinical question and the role of death within it before selecting a method. A measurement among survivors, a combined evaluation and a hypothetical question do not represent the same target. Define the interpretation, information needs and assumptions with appropriate clinical and statistical expertise rather than relying on routine data-processing conventions.
Hypothetical study example
In a hypothetical trial, a participant dies before a scheduled assessment. The database shows a missing score, but the analysis plan does not explain the situation. The team evaluates the endpoint definition instead of automatically carrying the last score forward and transparently records decision timing and reporting consequences.
Design review checks
- Record death separately from ordinary absence at a scheduled assessment visit.
- State explicitly how the event contributes to the endpoint definition.
- Compare the questions and assumptions represented by alternative analytical strategies.
Record the decision and its limits
The accepted approach lets readers understand the quantity actually estimated. Assigning an arbitrary worst score is not a scientific solution without rationale and a clear plan. Include death patterns in the results narrative, avoid claims unsupported by the selected strategy and data, and report the remaining uncertainty rather than hiding it in a generic missingness category.
Frequently asked questions
- Is death simply missing data?
- No. For some measures it changes how the endpoint itself must be defined.
- Can a worst score be assigned automatically?
- Such a rule requires scientific rationale, explicit definition and appropriate assessment.