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Nomogram for predicting opioid-induced nausea and vomiting for cancer pain patients.
Kong, Lingping; Wang, Jing; Guan, Shasha; Chen, Xiaochen; Li, Meiqing; Gao, Liming; Zhong, Diansheng; Zhang, Linlin.
Afiliação
  • Kong L; Department of Medical Oncology, Tianjin Medical University General Hospital, Tianjin, 300052, China.
  • Wang J; Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
  • Guan S; Department of Medical Oncology, Tianjin Medical University General Hospital, Tianjin, 300052, China.
  • Chen X; Department of Medical Oncology, Tianjin Medical University General Hospital, Tianjin, 300052, China.
  • Li M; Department of Oncology, People's Hospital of Inner Mongolia Autonomous Region, Hohhot, 010017, Inner Mongolia, China.
  • Gao L; Department of Oncology, The First Hospital of Qinhuangdao, Qinhuangdao, 066000, Hebei, China.
  • Zhong D; Department of Medical Oncology, Tianjin Medical University General Hospital, Tianjin, 300052, China.
  • Zhang L; Department of Medical Oncology, Tianjin Medical University General Hospital, Tianjin, 300052, China. zllcaroline@tmu.edu.cn.
Support Care Cancer ; 31(12): 663, 2023 Nov 02.
Article em En | MEDLINE | ID: mdl-37914831
ABSTRACT

OBJECTIVE:

Opioid-induced nausea and vomiting are frequently observed as an adverse effect in the treatment of cancer-related pain. The factors that affect OINV in cancer patients remain unclear. In this study, we developed a nomogram for predicting the occurrence of OINV in this population using retrospective clinical data.

METHODS:

We collected data from 416 cancer pain patients, 70% of whom used the training set to analyze demographic and clinical variables. We used multivariate logistic regression to identify significant factors associated with OINV. Then, we construct a prediction nomogram. The validation set comprises the remaining 30%. The reliability of the nomogram is evaluated by bootstrap resampling.

RESULTS:

Using multivariate logistic regression, we identified five significant factors associated with OINV. The C-index was 0.835 (95% confidence interval [CI], 0.828-0.842) for the training set and 0.810 (95% CI, 0.793-0.826) for the validation set. The calibrated curves show a good agreement between the predicted and actual occurrence of OINV.

CONCLUSION:

In a retrospective study based on five saliency-found variables, we developed and proved a reliable nomogram model to predict OINV in cancer pain patients. Future prospective studies should assess the model's reliability and usefulness in clinical practice.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Dor do Câncer / Antieméticos / Neoplasias Limite: Humans Idioma: En Revista: Support Care Cancer Assunto da revista: NEOPLASIAS / SERVICOS DE SAUDE Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Dor do Câncer / Antieméticos / Neoplasias Limite: Humans Idioma: En Revista: Support Care Cancer Assunto da revista: NEOPLASIAS / SERVICOS DE SAUDE Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China