通过两阶段专业临床堆叠法对头颈部癌吞咽困难风险进行分层
Dysphagia Risk Stratification in Head and Neck Cancer via Two-Stage PRO-Clinical Stacking
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中文总结 AI 辅助
研究针对头颈部癌吞咽困难风险识别难题及视频荧光成像的局限，提出单次就诊的PRO-临床预测框架和两阶段堆叠模型，利用PRO反应和临床变量预测风险，量化各因素贡献，支持其作为实用无成像方法用于风险分层。
中文摘要 AI 辅助
吞咽困难是头颈部癌（HNC）治疗令人衰弱的晚期效应，在生存护理中及时识别高危患者仍具挑战。明确评估依赖吞咽毒性动态成像分级（CTCAE-DIGEST）的视频荧光成像，虽经验证，但需专业设备、训练有素的人员且给患者带来较大负担，限制其在监测中的常规使用。相比之下，患者报告结局（PROs）低成本、可扩展且易收集。本研究通过制定单次就诊的PRO-临床预测框架并引入临床可解释的两阶段堆叠模型，利用PRO反应和结构化临床变量预测吞咽障碍风险，无需视频荧光成像。该框架在统一且可解释的风险评估模型中量化患者报告症状和临床因素的独立贡献。研究结果表明个体MDADI反应包含的预测信息超出综合或总体总结评分，解释性分析揭示了与吞咽障碍相关的症状模式和临床风险因素。这些结果支持使用结构化PRO-临床整合作为一种实用的、无需成像的方法对头颈部癌幸存者的吞咽困难风险进行分层。
英文摘要
Dysphagia is a debilitating late effect of head and neck cancer (HNC) treatment, yet timely identification of at-risk patients remains challenging in survivorship care. Definitive assessment relies on videofluoroscopic imaging, as captured by the Dynamic Imaging Grade of Swallowing Toxicity (CTCAE-DIGEST), which, while validated, requires specialized equipment, trained personnel, and significant patient burden, limiting its routine use in surveillance. Patient-reported outcomes (PROs), by contrast, are low-cost, scalable, and easily collected at any clinical encounter, making them an attractive alternative signal for identifying patients who may warrant further evaluation. However, a clear clinical framework for translating PRO responses into actionable interventions is still evolving. In particular, uncertainty remains regarding when a patient's self-reported symptom burden should prompt escalation of care. This study addresses this gap by formulating a single-visit PRO-clinical prediction framework and introducing a clinically interpretable two-stage stacking model to predict swallowing impairment risk using PRO responses and structured clinical variables, without requiring videofluoroscopic imaging. The proposed framework quantifies the independent contributions of patient-reported symptoms and clinical factors within a unified and interpretable risk assessment model. Our findings demonstrate that individual MDADI responses contain predictive information beyond that captured by composite or global summary scores, while interpretability analyses reveal symptom patterns and clinical risk factors associated with swallowing impairment. Together, these results support the use of structured PRO-clinical integration as a practical, imaging-free approach for dysphagia risk stratification in HNC survivorship.
