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◆ Photodiagnosis and photodynamic therapy2026-09-17

Toward Precision Photobiomodulation for Radiation-Induced Xerostomia: Clinical Evidence, Salivary Biomarkers, and Artificial Intelligence.

Shahriar Eftekharian, Shole Rastkar

一句话结论 · In one sentence

PBMT is a plausible supportive intervention, but biomarker-guided or AI-guided precision PBMT remains unvalidated. Future studies should standardize dosimetry, separate subjective and objective endpoints, account for gland-specific radiation exposure, incorporate long-term oncologic safety, and prospectively test treatment-effect models before clinical implementation.

原始摘要(英文原文)· Original abstract
BACKGROUND: Radiotherapy for head and neck cancer can cause xerostomia, the subjective sensation of oral dryness, and hyposalivation, an objectively measurable reduction in salivary output. Photobiomodulation therapy (PBMT) has been investigated as supportive care, but efficacy varies with timing, dosimetry, and outcome definition. METHODS: This structured narrative review critically evaluated PBMT for radiation-related salivary dysfunction and separately considered prevention, mitigation, early treatment, and late treatment. The final synthesis incorporated 42 publications spanning clinical PBMT studies, evidence syntheses and guidelines, radiotherapy dose studies, salivary biomarker studies, radiomics/machine-learning studies, and oncologic-safety evidence. RESULTS: Controlled clinical evidence suggests that PBMT can preserve or improve salivary flow in some settings, but patient-reported xerostomia benefits are inconsistent. A 2026 meta-analysis reported improved salivary flow (SMD 0.75, 95% CI 0.03-1.46) without significant improvement in xerostomia (SMD -0.07, 95% CI -0.47 to 0.33), with very-low-certainty evidence. Protocols remain heterogeneous and incompletely reported. Salivary cytokines, oxidative-stress markers, proteomic/metabolomic features, and imaging-derived variables are biologically or prognostically informative, but none is validated to predict differential PBMT benefit. Radiomics and machine-learning models can estimate radiation-related xerostomia risk, yet no model currently selects PBMT responders or optimizes PBMT parameters. These findings emphasize endpoint selection, external validation, and clinically meaningful treatment effects. CONCLUSIONS: PBMT is a plausible supportive intervention, but biomarker-guided or AI-guided precision PBMT remains unvalidated. Future studies should standardize dosimetry, separate subjective and objective endpoints, account for gland-specific radiation exposure, incorporate long-term oncologic safety, and prospectively test treatment-effect models before clinical implementation.
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Toward Precision Photobiomodulation for Radiation-Induced Xerostomia: Clinical Evidence, Salivary Biomarkers, and Artificial Intelligence. — 科研速览 Science Skim