Zhang Ying, Zhu Yongjian
College of Nursing, Qingdao University, Qingdao, China.
Nursing Department, Yantai Yuhuangding Hospital, Yantai, China.
Front Oncol. 2023 Jul 27;13:1172096. doi: 10.3389/fonc.2023.1172096. eCollection 2023.
Sarcopenia is associated with a poor prognosis in patients with colorectal cancer. However, the clinical factors that lead to colorectal cancer patients with sarcopenia are still unclear. The objective of this study is to develop and validate a nomogram for predicting the occurrence of sarcopenia and to provide healthcare professionals with a reliable tool for early identification of high-risk patients with colorectal cancer associated sarcopenia.
A total of 359 patients diagnosed with colorectal cancer from July 2021 to May 2022 were included. All patients were randomly divided into a training (n = 287) cohort and a validation cohort (n = 72) at the ratio of 80/20. Univariate and multivariate logistic analysis were performed to evaluate the factors associated with sarcopenia. The diagnostic nomogram of sarcopenia in patients with colorectal cancer was constructed in the training cohort and validated in the validation cohort. Various evaluation metrics were employed to assess the performance of the developed nomogram, including the ROC curve, calibration curve, and Hosmer-Lemeshow test.
Smoking history, drinking history, diabetes, TNM stage, nutritional status, and physical activity were included in the nomogram for the prediction of sarcopenia. The diagnostic nomograms demonstrated excellent discrimination, with AUC values of 0.971 and 0.922 in the training and validation cohorts, respectively. Moreover, the calibration performance of the nomogram is also excellent, as evidenced by the Hosmer-Lemeshow test result of 0.886.
The nomogram consisting of preoperative factors was able to successfully predict the occurrence of sarcopenia in colorectal cancer patients, aiding in the early identification of high-risk patients and facilitating timely implementation of appropriate intervention measures.
肌肉减少症与结直肠癌患者的不良预后相关。然而，导致结直肠癌患者发生肌肉减少症的临床因素仍不清楚。本研究的目的是开发并验证一种用于预测肌肉减少症发生的列线图，并为医疗保健专业人员提供一种可靠的工具，以便早期识别结直肠癌相关肌肉减少症的高危患者。
纳入2021年7月至2022年5月期间诊断为结直肠癌的359例患者。所有患者按80/20的比例随机分为训练队列（n = 287）和验证队列（n = 72）。进行单因素和多因素逻辑回归分析以评估与肌肉减少症相关的因素。在训练队列中构建结直肠癌患者肌肉减少症的诊断列线图，并在验证队列中进行验证。采用各种评估指标来评估所开发列线图的性能，包括ROC曲线、校准曲线和Hosmer-Lemeshow检验。
吸烟史、饮酒史、糖尿病、TNM分期、营养状况和身体活动被纳入预测肌肉减少症的列线图中。诊断列线图显示出出色的区分能力，训练队列和验证队列中的AUC值分别为0.971和0.922。此外，列线图的校准性能也非常出色，Hosmer-Lemeshow检验结果为0.886证明了这一点。
由术前因素组成的列线图能够成功预测结直肠癌患者肌肉减少症的发生，有助于早期识别高危患者并促进及时实施适当的干预措施。
