Development and validation of risk prediction model for sarcopenia in patients with colorectal cancer

被引:5
|
作者
Zhang, Ying [1 ]
Zhu, Yongjian [1 ,2 ]
机构
[1] Qingdao Univ, Coll Nursing, Qingdao, Peoples R China
[2] Yantai Yuhuangding Hosp, Nursing Dept, Yantai, Peoples R China
来源
FRONTIERS IN ONCOLOGY | 2023年 / 13卷
关键词
colorectal cancer; sarcopenia; malnutrition; influence factors; nomogram; PHYSICAL-ACTIVITY; MUSCLE; EXERCISE; SMOKING;
D O I
10.3389/fonc.2023.1172096
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
ObjectivesSarcopenia 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. MethodsA 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. ResultsSmoking 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. ConclusionsThe 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.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Development and Validation of a Prediction Model to Estimate Individual Risk of Pancreatic Cancer
    Yu, Ami
    Woo, Sang Myung
    Joo, Jungnam
    Yang, Hye-Ryung
    Lee, Woo Jin
    Park, Sang-Jae
    Nam, Byung-Ho
    PLOS ONE, 2016, 11 (01):
  • [42] Development and external validation of a head and neck cancer risk prediction model
    Smith, Craig D. L.
    Mcmahon, Alex D.
    Lyall, Donald M.
    Goulart, Mariel
    Inman, Gareth J.
    Ross, Al
    Gormley, Mark
    Dudding, Tom
    Macfarlane, Gary J.
    Robinson, Max
    Richiardi, Lorenzo
    Serraino, Diego
    Polesel, Jerry
    Canova, Cristina
    Ahrens, Wolfgang
    Healy, Claire M.
    Lagiou, Pagona
    Holcatova, Ivana
    Alemany, Laia
    Znoar, Ariana
    Waterboer, Tim
    Brennan, Paul
    Virani, Shama
    Conway, David I.
    HEAD AND NECK-JOURNAL FOR THE SCIENCES AND SPECIALTIES OF THE HEAD AND NECK, 2024, 46 (09): : 2261 - 2273
  • [43] Establishment and validation of a risk prediction model for sarcopenia in gastrointestinal cancer patients: A systematic review and meta-analysis-based approach
    Zhang, Ying
    Zhang, Lufang
    Guan, Yaqi
    Chen, Keya
    Zhang, Wei
    Hu, Zheqing
    Chen, Yu
    CLINICAL NUTRITION, 2024, 43 (11) : 91 - 98
  • [44] Postoperative mortality risk assessment in colorectal cancer: development and validation of a clinical prediction model using data from the Dutch ColoRectal Audit
    de Nes, Lindsey C. F.
    Hannink, Gerjon
    't Lam-Boer, Jorine
    Hugen, Niek
    Verhoeven, Rob H.
    de Wilt, Johannes H. W.
    BJS OPEN, 2022, 6 (02):
  • [45] Development and validation of a risk prediction model for breast cancer-related lymphedema in postoperative patients with breast cancer
    Li, Miao-miao
    Wu, Pei-pei
    Qiang, Wan-min
    Li, Jia-qian
    Zhu, Ming-yu
    Yang, Xiao-lin
    Wang, Ying
    EUROPEAN JOURNAL OF ONCOLOGY NURSING, 2023, 63
  • [46] Development and External Validation of a Prediction Model for Colorectal Cancer Among Patients Awaiting Surveillance Colonoscopy Following Polypectomy
    Levin, Theodore R.
    Jensen, Christopher D.
    Marks, Amy R.
    Schlessinger, David
    Liu, Vincent
    Udaltsova, Natalia
    Badalov, Jessica
    Layefsky, Evan
    Corley, Douglas A.
    Nugent, Joshua R.
    Lee, Jeffrey K.
    GASTRO HEP ADVANCES, 2024, 3 (05):
  • [47] Development and validation of a risk prediction model for placental abruption in patients with preeclampsia
    Yang, Mei
    Wang, Menghui
    Zhu, Qing
    Li, Nanfang
    PLACENTA, 2025, 164 : 1 - 9
  • [48] Development and Validation of a Risk Prediction Model for Frailty in Patients with Chronic Diseases
    Xu, Yuanchun
    Cao, Wei
    He, Zongsheng
    Wu, Nuoyi
    Cai, Mingyu
    Yang, Li
    Liu, Shuying
    Jia, Wangping
    He, Haiyan
    Wang, Yaling
    GERONTOLOGY AND GERIATRIC MEDICINE, 2024, 10
  • [49] Preoperative Prediction of Sarcopenia in Patients Scheduled for Gastric and Colorectal Cancer Surgery
    Beijia Zhou
    Yanjun Song
    Chen Chen
    Xiaotian Chen
    Tingting Tao
    Journal of Gastrointestinal Cancer, 2025, 56 (1)
  • [50] Development and validation of risk prediction model for refeeding syndrome in neurocritical patients
    Zhang, Wei
    Zhang, Sheng-Xiang
    Chen, Shu-Fan
    Yu, Tao
    Tang, Yun
    FRONTIERS IN NUTRITION, 2023, 10