Early-phase oncology evidence is often summarized by asking whether a treatment is promising, but an encouraging signal can support several different next studies. We propose Evidence-to-Decision (E2D), a framework that organizes evidence around specific development actions. For each candidate action, E2D defines the contemplated future study, what would count as success, what evidence is needed before taking that step, what evidence is available now, and what assumptions connect the current and future settings. Statistical methods can then quantify action-specific support and sensitivity to those assumptions, while the final development choice remains multidisciplinary. We illustrate E2D in a rare pediatric oncology setting using predictive probabilities for same-setting single-arm expansion, same-setting randomized Phase II, movement to an earlier-line or frontline randomized study, and a separate de-escalation example. Calibrated support rules produced clinically distinct evidence states: intermediate evidence could support same-setting development without supporting frontline movement, safety concerns could narrow support despite strong activity, and stronger evidence could support several paths simultaneously. E2D therefore reframes the question from whether a treatment is generally promising to which next studies are supported by the evidence available now, what remains unsupported, and what additional evidence could change that assessment.

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