Simple Prediction Tool Could Optimise Antiemetic Use

A scoring system based on patient-specific risk factors could help to improve chemotherapy-induced emesis prophylaxis and optimise antiemetic use

  • Date: 13 Apr 2017
  • Author: By Shreeya Nanda, Senior medwireNews Reporter
  • Topic: Supportive Measures

medwireNews: An international team has developed a prediction tool incorporating patient-specific factors that could help to identify those at high risk of chemotherapy-induced nausea and vomiting (CINV) prior to each chemotherapy cycle.

“The clinical application of this prediction tool will be an important source of individual patient risk information for the oncology clinician and may enhance patient care by optimizing the use of the antiemetics in a proactive manner”, the researchers write in the Annals of Oncology.

They explain that appropriate prophylaxis is crucial to ensure that “CINV [is] managed effectively in the first cycle of chemotherapy because it will almost certainly have a negative impact in CINV outcomes in subsequent cycles.”


Writing in a linked editorial, Florian Scotté, from Hôpital Européen Georges Pompidou in Paris, France, agrees that "[t]he screening of patients at high risk would allow more efficient nausea and vomiting prophylaxis as well as optimized antiemetic use."

He adds: “This novel approach could possibly change routine daily practice for these patients.”

Pooling data from 1198 participants of five prospective studies conducted between 2008 and 2015, the researchers found that 42.2% experienced grade 2 or worse CINV, defined as at least two vomiting episodes or a decrease in oral intake due to nausea, during the initial 5 days of chemotherapy.

Eight patient-specific parameters were significantly associated with CINV risk, namely age of 60 years or younger, being in cycle two or three versus cycle one of chemotherapy, anticipatory nausea and vomiting, history of morning sickness, less than 7 hours of sleep the night before, occurrence of CINV during the prior cycle, self-medication with non-prescribed antiemetics, and the use of platinum- or anthracycline-based regimens versus single agent taxanes or other chemotherapy types.

These factors were incorporated into a risk scoring system that assigned scores between 0 and 32 points, where higher scores indicated an increased risk of at least grade 2 CINV over the first 5 days of chemotherapy.

At or above a cutoff of 16 points, the model distinguished high-risk patients from those at low risk with an area under the receiver operating characteristic curve (AUC) of 0.69, a sensitivity of 87.4% and a specificity of 38.4%.

Study author George Dranitsaris, from The Ottawa Hospital Regional Cancer Centre in Ontario, Canada, and collaborators recognise that although the AUC is acceptable, there is room for improvement, and the specificity is low.

However, they point out that “the risk cut off can be adjusted based on a patient’s risk tolerance”, and add: “External validation of the risk prediction model in a new sample of patients would also improve the specificity.”

Noting that the algorithm is “easy to apply”, the researchers highlight that they have generated an online version of the prediction tool to “allow the percentage of CINV risk to be rapidly calculated, ‘just in time’ to modify antiemetic prophylaxis.”

Editorialist Florian Scotté explains that the current approach to antiemesis is based on assessing the emetogenic level of the chemotherapy regimen. He suggests that perhaps the risk score could be incorporated into a second level of decision-making, allowing the choice of antiemetic agent to be “specifically formulated for each patient.”


Dranitsaris G, Molassiotis A, Clemons M, et al. The development of a prediction tool to identify cancer patients at high risk for chemotherapy-induced nausea and vomiting. Ann Oncol; Advance online publication 7 April 2017. doi:

Scotté F. Identifying predictive factors of chemotherapy induced nausea and vomiting (CINV). A novel approach. Ann Oncol; Advance online publication 7 April 2017. doi:

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