Article

AIP: Prospective Validation of a Prediction Tool for Identifying Patients at High Risk for Chemotherapy-Induced Nausea and Vomiting

Publish date: July 9, 2012

The primary objective of the current study was to prospectively validate the prediction scoring systems for acute and delayed CINV in an independent sample of patients receiving outpatient chemotherapy. The final objective of this initiative will be to determine if optimal emesis control can be achieved using validated predictive models.
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Original Research

Prospective Validation of a Prediction Tool for Identifying Patients at High Risk for Chemotherapy-Induced Nausea and Vomiting

  • George Dranitsaris, BPharm, PhD,
    Nathaniel Bouganim, MD,Carolyn Milano, Lisa Vandermeer, MSc, Susan Dent, MD, Paul Wheatley-Price, MD, Jenny Laporte, RN, Karen-Ann Oxborough, RN, Mark Clemons, MD

    Abstract

    Background

    Even with modern antiemetic regimens, up to 20% of cancer patients suffer from moderate to severe chemotherapy-induced nausea and vomiting (CINV) (≥ grade 2). We previously developed chemotherapy cycle–based risk predictive models for ≥ grade 2 acute and delayed CINV. In this study, the prospective validation of the prediction models and associated scoring systems is described.

    Objective

    Our objective was to prospectively validate prediction models designed to identify patients at high risk for moderate to severe CINV.

    Methods

    Patients receiving chemotherapy were provided with CINV symptom diaries. Prior to each cycle of chemotherapy, the acute and delayed CINV scoring systems were used to stratify patients into low- and high-risk groups. Logistic regression was used to compare the occurrence of ≥ grade 2 CINV between patients considered by the model to be at high vs low risk. The external validity of each system was assessed via an area under the receiver operating characteristic (AUROC) curve analysis.

    Results

    Outcome data were collected from 97 patients following 401 cycles of chemotherapy. The incidence of ≥ grade 2 acute and delayed CINV was 13.5% and 21.4%, respectively. There was a significant correlation between the risk score and the probability of developing acute and delayed CINV following chemotherapy. Both the acute and delayed scoring systems had good predictive accuracy when applied to the validation sample (acute, AUROC = 0.70, 95% CI, 0.62–0.77; delayed, AUROC = 0.75, 95% CI, 0.69–0.80). Patients who were identified as high risk were 3.1 (P = .006) and 4.2 (P < .001) times more likely to develop ≥ grade 2 acute and delayed CINV than were those identified as low risk.

    Conclusion

    This study demonstrates that the scoring systems are able to accurately identify patients at high risk for acute and delayed CINV.


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