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肝癌患者经动脉化疗栓塞术后疼痛管理预测评分系统的开发与验证

Development and validation of a predictive scoring system for post-transarterial chemoembolization pain management in liver cancer patients.

作者信息

You Ke, Wang Jiaguo, Xu Jie, Zhang Chunyu, Wang Xingxing, Gavriilidis Paschalis, Kawaguchi Takumi, Wang Yunbing

机构信息

Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Department of Surgery, Colchester General Hospital, Colchester, UK.

出版信息

J Gastrointest Oncol. 2024 Feb 29;15(1):425-434. doi: 10.21037/jgo-24-2. Epub 2024 Feb 28.

Abstract

BACKGROUND

Patients experiencing severe postoperative pain often show lower adherence to prescribed treatments, highlighting the clinical need for effective pain prediction and management strategies. This study aims to address this gap by identifying key risk factors associated with post-transarterial chemoembolization (TACE) pain and developing a predictive scoring system.

METHODS

We retrospectively analyzed data from liver cancer patients who underwent their first TACE procedure at our institution between January 2019 and December 2020. Pain levels were assessed using an 11-point numerical rating scale (NRS-11). Patients were randomly assigned to training and validation cohorts. In the training cohort, logistic regression was used to evaluate the correlation between various parameters and post-TACE pain, leading to the development of a risk prediction model. This model's performance was subsequently assessed in the validation cohort.

RESULTS

The study included 255 patients. Univariate analysis in the training cohort identified tumor number, size, microsphere volume, and operation time as factors associated with postoperative pain. These factors were included in a multivariate model, which demonstrated areas under the receiver operating characteristic (ROC) curve (AUCs) of 0.71 in the training cohort and 0.74 in the validation cohort for predicting moderate to severe pain. A nomogram was also developed for clinical application, categorizing patients with scores above 72.90 as high risk for moderate to severe pain.

CONCLUSIONS

Our research successfully developed and validated a novel scoring system capable of predicting moderate to severe pain following initial TACE treatment. However, the study's predictive accuracy, as reflected by AUC values, suggests that further refinement and validation in larger, diverse cohorts are necessary to enhance its clinical utility. This work underscores the importance of predictive tools in improving postoperative pain management and patient outcomes.

摘要

背景

经历严重术后疼痛的患者往往对规定治疗的依从性较低,这凸显了临床对有效疼痛预测和管理策略的需求。本研究旨在通过识别与经动脉化疗栓塞术(TACE)疼痛相关的关键风险因素并开发一种预测评分系统来填补这一空白。

方法

我们回顾性分析了2019年1月至2020年12月在本机构接受首次TACE手术的肝癌患者的数据。使用11点数字评分量表(NRS - 11)评估疼痛程度。患者被随机分配到训练队列和验证队列。在训练队列中,采用逻辑回归评估各种参数与TACE术后疼痛之间的相关性,从而开发出一个风险预测模型。随后在验证队列中评估该模型的性能。

结果

该研究纳入了255例患者。训练队列中的单因素分析确定肿瘤数量、大小、微球体积和手术时间为与术后疼痛相关的因素。这些因素被纳入一个多变量模型,该模型在训练队列中预测中度至重度疼痛的受试者工作特征(ROC)曲线下面积(AUC)为0.71,在验证队列中为0.74。还开发了一个列线图用于临床应用,将得分高于72.90的患者分类为中度至重度疼痛的高风险患者。

结论

我们的研究成功开发并验证了一种能够预测初次TACE治疗后中度至重度疼痛的新型评分系统。然而,AUC值所反映的研究预测准确性表明,有必要在更大、更多样化的队列中进行进一步优化和验证,以提高其临床实用性。这项工作强调了预测工具在改善术后疼痛管理和患者预后方面的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/213a/10932688/abd949f2fb67/jgo-15-01-425-f1.jpg

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