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Nomogram for Predicting Chemotherapy-Induced Nausea and Vomiting for Breast Cancer Patients.
Huang, Xin-Juan; Li, Xu-Ying; Li, Jin-Hua; Hu, Zhe-Yu; Luo, Lu; Tan, Yan; Chen, Hong-Yun; Fan, Rong-Rong; Wang, Tong-Yu; Meng, Ling-Qi; Wei, Tao.
Afiliación
  • Huang XJ; Department of Nursing, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital.
  • Li XY; Department of Nursing, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital.
  • Li JH; Department of Nursing, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital.
  • Hu ZY; Department of Breast Cancer, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital.
  • Luo L; Department of Mammary Glands, Hunan Provincial Maternal and Child Health Care Hospital.
  • Tan Y; Department of Nursing, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital.
  • Chen HY; Department of Nursing, University of South China.
  • Fan RR; Xiangya School of Nursing, Central South University.
  • Wang TY; School of Nursing, Hunan University of Chinese Medicine.
  • Meng LQ; Xiangya School of Nursing, Central South University.
  • Wei T; Department of Nursing, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital.
Tohoku J Exp Med ; 254(2): 111-121, 2021 06.
Article en En | MEDLINE | ID: mdl-34162779
ABSTRACT
Chemotherapy-induced nausea and vomiting (CINV) is a common side effect of cancer treatment. The factors influencing CINV in breast cancer patients remain unclear. In this study, we developed a nomogram for predicting the occurrence of CINV in this group using prospective clinical data. We pooled data from multiple studies which focused on the emetogenic chemotherapy. Then, we collected 334 breast cancer patients at Hunan Cancer Hospital (training set) to analyze the demographic and clinical variables. Using multivariate logistic regression, we identified the five significant factors that were associated with CINV history of CINV, chemotherapy regimen, chemotherapy cycle, metastasis, and symptoms of distress. Then, we construct a prediction nomogram. The external validation set comprised an additional 66 patients. The reliability of the nomogram was assessed by bootstrap resampling. The C-index was 0.78 (95% confidence interval [CI], 0.73-0.85) for the training set and 0.74 (95% CI, 0.62-0.85) for the validation set. Calibration curves showed good concordance between predicted and actual occurrence of CINV. In conclusions, our nomogram model can reliably predict the occurrence of CINV in breast cancer patients based on five significant variables, which might be useful in clinical decision-making.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Vómitos / Neoplasias de la Mama / Náusea / Antineoplásicos Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Tohoku J Exp Med Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Vómitos / Neoplasias de la Mama / Náusea / Antineoplásicos Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Tohoku J Exp Med Año: 2021 Tipo del documento: Article