[口腔癌患者士气低落综合征的风险预测]

[Risk prediction of demoralization syndrome in patients with oral cancer].

作者信息

Mao Liyan, Yang Xixi, Bi Xiaoqin, Liu Min, Zhao Chongyang, Wen Zuozhen

机构信息

West China School of Nursing, Sichuan University, Chengdu 610041, China.

State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Dept. of Orthognathic and Temporomandibular Joint Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China.

出版信息

Hua Xi Kou Qiang Yi Xue Za Zhi. 2025 Jun 1;43(3):395-405. doi: 10.7518/hxkq.2025.2024340.

DOI:10.7518/hxkq.2025.2024340

PMID:40523820

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12211499/

Abstract

OBJECTIVES

This study aimed to construct a risk prediction model for the occurrence of the demora-lization syndrome in patients with oral cancer and provide a scientific basis for the prevention of this syndrome in patients with oral cancer and the development of personalized care programs.

METHODS

A total of 486 patients with oral cancer in West China Hospital of Stomatology of Sichuan University and Sun Yat-sen Memorial Hospital of Sun Yat-sen University from 2024 March to July were selected by convenience sampling. We integrated clinical data and evidence from previous studies to identify the key variables affecting the demoralization syndrome in patients with oral cancer. The 486 patients were divided into a training set and a validation set in an 8∶2 ratio. A clinical risk prediction model was established based on the individual data of 365 patients in the development cohort. Through least absolute shrinkage and selection operator (LASSO) regression, a moderate to severe risk prediction model of demoralization syndrome in oral cancer was constructed, and a clinical machine-learning nomogram was constructed. Bootstrap resampling was used for internal validation. The data of 121 patients in the validation cohort were externally validated.

RESULTS

The incidence of the demoralization syndrome in patients with oral cancer was 405 cases (83.3%), of which 279 cases (57.4%) were mild, 176 cases (36.2%) were moderate, and 31 cases (6.4%) were severe. The core model, including patient education level, disease understanding, and MDASI-HN score, was used to predict the risk of outcome. Internal validation of the model yielded C statistic of 0.783 6 (95% CI: 0.78-0.87), beta of 0.843 4, and calibration intercept of -0.040 6. Through external validation, the validation set C statistic was 0.80 (95%CI: 0.71-0.87), beta was 0.80, and calibration intercept was -0.08.

CONCLUSIONS

Our risk prediction mo-del of the demoralization syndrome in patients with oral cancer performed robustly in validation cohorts of different nur-sing environments. The model has good correction and good discrimination and can be used as an evaluation and prediction item at admission.

摘要

目的

本研究旨在构建口腔癌患者发生失志综合征的风险预测模型，为口腔癌患者预防该综合征及制定个性化护理方案提供科学依据。

方法

采用便利抽样法，选取2024年3月至7月在四川大学华西口腔医院和中山大学孙逸仙纪念医院就诊的486例口腔癌患者。整合临床数据和既往研究证据，确定影响口腔癌患者失志综合征的关键变量。将486例患者按8∶2的比例分为训练集和验证集。基于365例患者的个体数据在开发队列中建立临床风险预测模型。通过最小绝对收缩和选择算子（LASSO）回归，构建口腔癌失志综合征中重度风险预测模型，并构建临床机器学习列线图。采用自助重抽样法进行内部验证。对验证队列中121例患者的数据进行外部验证。

结果

口腔癌患者失志综合征发生率为405例（83.3%），其中轻度279例（57.4%），中度176例（36.2%），重度31例（6.4%）。核心模型包括患者教育程度、疾病认知和MDASI-HN评分，用于预测结局风险。模型内部验证的C统计量为0.783 6（95%CI：0.78 - 0.87），β为0.843 4，校准截距为 - 0.040 6。通过外部验证，验证集C统计量为0.80（95%CI：0.71 - 0.87），β为0.80，校准截距为 - 0.08。