{"title":"Prediction of liver metastasis and recommended optimal follow-up nursing in rectal cancer","authors":"Yilin Yu, Junxin Wu, Haixia Wu, Jianjian Qiu, Shiji Wu, Liang Hong, Benhua Xu, Lingdong Shao","doi":"10.1111/nhs.13102","DOIUrl":null,"url":null,"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.","PeriodicalId":49730,"journal":{"name":"Nursing & Health Sciences","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nursing & Health Sciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/nhs.13102","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NURSING","Score":null,"Total":0}
引用次数: 0
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.
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.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
