Prediction of liver metastasis and recommended optimal follow-up nursing in rectal cancer

IF 2.1 3区 医学 Q2 NURSING Nursing & Health Sciences Pub Date : 2024-02-25 DOI:10.1111/nhs.13102
Yilin Yu, Junxin Wu, Haixia Wu, Jianjian Qiu, Shiji Wu, Liang Hong, Benhua Xu, Lingdong Shao
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Abstract

We aimed to analyze and investigate the clinical factors that influence the occurrence of liver metastasis in locally advanced rectal cancer patients, with an attempt to assist patients in devising the optimal imaging-based follow-up nursing. Between June 2011 and May 2021, patients with rectal cancer at our hospital were retrospectively analyzed. A random survival forest model was developed to predict the probability of liver metastasis and provide a practical risk-based approach to surveillance. The results indicated that age, perineural invasion, and tumor deposit were significant factors associated with the liver metastasis and survival. The liver metastasis risk of the low-risk group was higher at 6–21 months, with a peak occurrence time in the 15th month. The liver metastasis risk of the high-risk group was higher at 0–24 months, with a peak occurrence time in the 8th month. In general, our clinical model could predict liver metastasis in rectal cancer patients. It provides a visualization tool that can aid physicians and nurses in making clinical decisions, by detecting the probability of liver metastasis.
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直肠癌肝转移预测和推荐的最佳随访护理
我们旨在分析和研究影响局部晚期直肠癌患者发生肝转移的临床因素,以帮助患者制定基于影像学的最佳随访护理方案。2011年6月至2021年5月期间,本院对直肠癌患者进行了回顾性分析。我们建立了一个随机生存森林模型来预测肝转移的概率,并提供了一种实用的基于风险的监测方法。结果表明,年龄、神经周围侵犯和肿瘤沉积是与肝转移和生存相关的重要因素。低风险组的肝转移风险在6-21个月时较高,在第15个月时达到高峰。高危组的肝转移风险在0-24个月时较高,高峰期出现在第8个月。总的来说,我们的临床模型可以预测直肠癌患者的肝转移。它提供了一种可视化工具,通过检测肝转移的概率,帮助医生和护士做出临床决策。
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来源期刊
CiteScore
4.80
自引率
3.70%
发文量
91
审稿时长
6-12 weeks
期刊介绍: NHS has a multidisciplinary focus and broad scope and a particular focus on the translation of research into clinical practice, inter-disciplinary and multidisciplinary work, primary health care, health promotion, health education, management of communicable and non-communicable diseases, implementation of technological innovations and inclusive multicultural approaches to health services and care.
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