The Fixation–Autonomy Continuum (FAC): A Unified Systems Framework for Understanding Chronic Disease and Cancer Progression

Abstract Modern medicine classifies diseases according to anatomy, pathology, molecular mechanisms, and diagnostic categories. While these approaches have generated substantial advances in scientific understanding and clinical management, they often provide limited insight into a broader systems-level question: why do some disease processes remain highly responsive to changing physiological and environmental conditions, while others become progressively resistant to modification and increasingly self-sustaining? This paper proposes the Fixation–Autonomy Continuum (FAC), a conceptual framework describing chronic disease progression as a gradual transition from condition-sensitive dysfunction toward increasingly autonomous biological organization. The framework suggests that many chronic diseases begin in states characterized by substantial responsiveness to physiological conditions, adaptive flexibility, and functional variability. Over time, persistent adaptive responses may become progressively embedded within biological structure and regulatory organization. As fixation increases, responsiveness to changing conditions declines. In advanced states, disease processes may acquire varying degrees of systemic autonomy, allowing persistence despite alterations in the conditions that originally contributed to their emergence. FAC integrates two complementary concepts: disease fixation and systemic autonomy. Within the present framework, fixation and autonomy are proposed as opposite perspectives on the same biological transition. Fixation describes the progressive loss of condition sensitivity, whereas autonomy describes the progressive acquisition of self-sustaining capacity. Cancer is presented not as a fundamentally separate phenomenon, but as a potential extreme expression of a broader biological principle observable across chronic disease. Rather than replacing existing theories of adaptation, resilience, allostasis, or disease progression, FAC is proposed as an integrative systems-level dimension capable of organizing observations currently distributed across multiple scientific domains. The framework is intended as a conceptual and hypothesis-generating model for future empirical investigation.