Score Based on Patient Factors Can Predict Nausea and Vomiting

A risk scoring algorithm based on several risk factors was able to accurately predict chemotherapy-induced nausea and vomiting (CINV), according to a new study. The score could allow optimization of antiemetic use in cancer patients.

“Despite important advances in new and effective preventative antiemetics, CINV remains among the most unpleasant and feared side effects of cancer chemotherapy,” wrote study authors led by George Dranitsaris, PhD, of the Ottawa Hospital Regional Cancer Centre in Canada.

This study examined data from 1,198 patients enrolled in 1 of 5 non-interventional CINV prospective studies, covering a total of 4,197 chemotherapy cycles; more than half the cohort had breast cancer (56%), and most patients had early-stage disease (76%). Researchers established risk factors for CINV, and then created a risk scoring system to predict it. The study was published in Annals of Oncology.

Grade 2 or higher CINV (defined as at least two vomiting episodes or a decrease in oral intake due to nausea) was reported in 42.2% of patients. Eight risk factors were significantly associated with CINV: nausea or vomiting in the prior chemotherapy cycle; use of non-prescribed antiemetics; platinum- or anthracycline-based chemotherapy; age of 60 years or younger; anticipatory nausea and vomiting; less than 7 hours of sleep the night prior to chemotherapy; a history of morning sickness during pregnancy; and the first 2 cycles of chemotherapy.

These factors were used to create a scoring system that ranges from 0 to 32, with higher scores associated with increased risk of grade 2 or higher CINV over the first 5 days of chemotherapy. Assigning scores to the patient cohort suggested a strong predictive value, with an area under the curve of 0.69 (95% CI, 0.67–0.70).

A cutoff value of 16 was found to offer optimal sensitivity; a score of 16 or higher would suggest a risk of CINV of at least 60%. The authors noted that using a higher threshold before changing antiemetic therapy would potentially minimize the false positive rate, though would also reduce the sensitivity. For example, a score of 20 or higher would offer 75.7% specificity, but 51.2% sensitivity.

“The CINV risk prediction model developed in the current study allows the incorporation of personal risk factors that will identify patients at high risk and ensure they are receiving appropriate prophylaxis,” the authors wrote, adding that the algorithm is easy to apply and can allow risk evaluation quickly and at each cycle of chemotherapy.