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Type 1 diabetes (T1D) is a staged, heterogeneous autoimmune disease in which immune injury, inflammatory signaling, antigen presentation, beta-cell stress, and loss of regulatory control interact over time. Human intervention studies establish that the disease course can be modified, yet benefits are commonly partial, heterogeneous, or treatment-dependent, and durable treatment-free tolerance remains uncommon. This article integrates randomized and prospective T1D trials, long-term follow-up, human mechanistic studies, negative and transient therapeutic studies, contemporary beta-cell-directed interventions, and cell-replacement evidence to examine why biological activity at individual targets has not consistently produced durable system control. Our central hypothesis is that, because the dominant biological bottleneck can change over time, a conditional multi-step treatment strategy that sequentially targets measured residual mechanisms may achieve greater and more durable disease modification than a single-agent strategy directed at one target alone. This does not imply indiscriminate polytherapy: each additional step should be entered only when a defined biological objective remains unmet and should be withdrawn when its task is complete. We therefore propose a conditional statetransition framework comprising seven research operations: baseline staging and stabilization; finite immune induction; optional immune-recovery control; mechanism-directed continuation or finite reinforcement; tolerance consolidation; withdrawal and surveillance; and mechanismmatched reintervention or transition to beta-cell replacement. A parallel beta-cell axis is selected independently to address metabolic load, tissue stress, and recoverable function. The framework is not a treatment protocol and the superiority of the proposed multi-step strategy has not been clinically established. It is a falsifiable hypothesis intended to generate component-controlled trials that directly compare state-guided sequencing with appropriate monotherapy or inductionalone controls.
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Mario José do Canto Filho (2026) studied this question.
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