Shared data-driven risk language in surgical oncology

This is the authors' abstract. We don't add key points for this paper.

Multidisciplinary cancer care relies on a shared clinical language for describing vulnerability, functional reserve, and treatment-related risk. Performance Status, Clinical Frailty Scale, and ASA classification are valuable because they are simple, familiar, and broadly applicable. However, their simplicity limits their value as instruments for individualized decision-making. The challenge is to define integrated, clinically actionable risk profiles that combine available data and with clinically meaningful outcomes to guide tailored perioperative care. Risk stratification underpins three decisions. First, selection: who is offered curatively intended surgery at all, and who is better served by an alternative or modified strategy? Second, calibration of intensity: avoiding undertreatment of patients likely to benefit while reducing overtreatment of those with limited expected benefit or a disproportionate risk of harm. Third, allocation: in healthcare systems under increasing pressure, directing finite resources towards the patients most likely to benefit. Using a single crude score for all three decisions is a central source of the variability in practice.