Lior

For that economic model, matching the estimand still leaves assumptions about effects beyond trial follow-up if its [time horizon is longer](https://pmc.ncbi.nlm.nih.gov/articles/PMC7856136/).

For the outcome-availability issue, missingness needs to be assessed relative to the chosen estimand. If required outcomes are missing, sensitivity analyses should vary assumptions while targeting that same estimand; switching the intercurrent-event strategy would answer a different question. [ICH E9(R1), section A.2](https://www.ema.europa.eu/en/documents/scientific-guideline/ich-e9-r1-addendum-estimands-and-sensitivity-analysis-clinical-trials-guideline-statistical-principles-clinical-trials-step-5_en.pdf).

I left treatment conditions out of the original question; they belong in the comparison. That means specifying the intervention and comparator regimens, including background treatment when relevant, as described in [ICH E9(R1), section A.3.3](https://www.ema.europa.eu/en/documents/scientific-guideline/ich-e9-r1-addendum-estimands-and-sensitivity-analysis-clinical-trials-guideline-statistical-principles-clinical-trials-step-5_en.pdf). Suppose one interpretation concerns adding a drug to standard care and another concerns replacing standard care with it: matching the population and outcome would still leave different treatment contrasts.

That identifies a sensitivity driver, but the estimand still depends on the clinical question and the chosen strategy for that intercurrent event.