Background: Contemporary clinical care increasingly confronts diseases that are biologically complex, clinically heterogeneous, and operationally demanding. Two areas exemplify this challenge in particularly distinct yet conceptually related ways: allergic rhinitis with comorbid asthma, and cancer management through multidisciplinary tumor boards. The literature on allergic airway disease shows that rhinitis and asthma are strongly interconnected at epidemiological, immunological, symptomatic, and quality-of-life levels, requiring coordinated diagnostic and therapeutic approaches (Leynaert et al., 2000; Kalpaklioğlu & Baççioğlu, 2008; Bousquet et al., 2020; GINA, 2023). Meanwhile, oncology literature demonstrates that multidisciplinary decision-making has become central to patient-centered, precision-oriented management, with recent studies exploring the role of artificial intelligence and large language models as adjunctive tools in tumor boards and cancer care (Luchini et al., 2020; Benary et al., 2023; Sorin et al., 2023; Uprety et al., 2023).

Objective: This article develops an integrative review of how multidisciplinary practice, decision support, and patient-centered outcome assessment can improve management in two major clinical domains: allergic rhinitis–asthma comorbidity and oncology. It also critically evaluates the emerging role of artificial intelligence-based systems in complex clinical decision environments.

Methodology: A qualitative integrative review was conducted strictly on the basis of the references supplied. The study synthesized literature across epidemiology, pathophysiology, guideline-based care, quality of life, environmental and genetic risk, tumor board practice, Bayesian and AI-assisted decision systems, and large language model applications in healthcare.

Results: The review identifies four major findings. First, allergic rhinitis and asthma should be approached as linked airway disorders requiring coordinated evaluation. Second, disease burden extends beyond symptoms to productivity, function, psychosocial well-being, and treatment complexity. Third, multidisciplinary structures improve decision quality in oncology and provide a transferable model for other complex conditions. Fourth, artificial intelligence and large language models show promise as support tools, but their use remains constrained by concerns around reliability, contextual reasoning, bias, and governance.

Conclusion: The future of complex chronic care lies in combining evidence-based guidelines, multidisciplinary collaboration, nuanced phenotyping, and carefully governed intelligent decision support. The clinical promise of such integration is substantial, but it must remain grounded in human oversight, patient context, and rigorous validation.

Allergic rhinitis, asthma comorbidity, multidisciplinary care

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