AI-based prognostic risk stratification and hope in osteosarcoma and bone metastatic cancer

Abstract

Artificial intelligence based prognostic risk stratification is increasingly applied in osteosarcoma and bone metastatic cancer to generate individualized estimates of survival, recurrence, treatment response, and complication risk. While these technologies promise greater precision in oncologic decision making, their implications extend beyond biomedical prediction into the psychosocial domain. Prognostic information is not a neutral technical output but a psychologically salient event that shapes patients’ understanding of illness, emotional adjustment, communication with clinicians, and future oriented meaning making. This narrative review examines AI driven prognostic risk stratification through a psycho oncology lens, with particular attention to its relationship with patient hope. Drawing on literature from oncology, artificial intelligence, communication science, and psycho oncology, hope is conceptualized as a dynamic and adaptive process rather than simple optimism about survival. The review explores how AI based prognostic information may clarify or intensify uncertainty, influence doctor patient communication, and contribute to the construction or recalibration of hope across the disease trajectory. Ethical and psychological challenges are addressed, including risks of algorithmic determinism, inequity, emotional burden, and cultural misalignment. Clinical practice implications are outlined, emphasizing the central role of psycho oncology in mediating AI supported prognostic discussions, screening for distress, and supporting adaptive hope. By integrating technological innovation with psychosocial theory and clinical insight, this review highlights pathways toward ethically responsible and patient centered use of artificial intelligence in bone oncology that supports both informed decision making and psychological wellbeing.

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