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Construction and validation of a nomogram model for predicting CINV in patients with gynecological malignancies

  • 0The First Affiliated Hospital of Kangda College of Nanjing Medical University, 6 zhenhua East Rd., Lianyungang 222000, China.
Japanese Journal of Clinical Oncology +

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March 10, 2025

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March 10, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

A nomogram effectively predicts chemotherapy-induced nausea and vomiting (CINV) in gynecological cancer patients. Key predictors include age, motion sickness, pregnancy vomiting history, and chemotherapy drug type.

Area Of Science

  • Oncology
  • Clinical Prediction Models
  • Gynecological Malignancies

Background

  • Chemotherapy-induced nausea and vomiting (CINV) significantly impacts treatment adherence and quality of life in patients with gynecological malignancies.
  • Accurate prediction of CINV risk is crucial for personalized antiemetic management.

Purpose Of The Study

  • To develop and validate a nomogram model for predicting CINV risk in patients undergoing chemotherapy for gynecological malignancies.
  • Identify key clinical and demographic risk factors associated with CINV.

Main Methods

  • Retrospective analysis of patients with gynecological malignancies treated between February 2020 and October 2021.
  • Development of a nomogram using logistic regression on a training set and validation using an internal validation set and external patient data.
  • Assessment of model performance using receiver operating characteristic (ROC) curves and calculation of area under the curve (AUC), sensitivity, and specificity.

Main Results

  • Multivariate analysis identified age <60 years, motion sickness, history of pregnancy-related vomiting, and use of moderate/high emetogenic chemotherapy drugs as independent predictors of CINV.
  • The nomogram demonstrated good discrimination in the training set (AUC=0.844) and internal validation set (AUC=0.945).
  • External validation showed an AUC of 0.704, indicating moderate predictive ability in a broader population.

Conclusions

  • The developed nomogram, incorporating age, emetogenic potential of chemotherapy, motion sickness, and pregnancy vomiting history, is a valuable tool for predicting CINV in gynecological cancer patients.
  • The nomogram shows good discriminative ability, supporting its use in clinical practice for risk stratification and personalized antiemetic therapy.
  • Further validation in diverse populations is recommended to optimize its clinical utility.

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