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.
Keywords: Cancer; Nomogram; Opioid-induced nausea and vomiting (OINV); Predictive model; Risk factors.
© 2023. The Author(s).