is to predict CINV risk according
to cycle of chemotherapy using
repeated measures in addition
to baseline data. 2 An easy-to-
use online tool (www.cinvrisk.
org) recently created based on
this model helps oncologists to
calculate the risk, in real-time,
of developing Grade 2 or higher
CINV events for cancer patients
with specific risk factors. The
online tool also suggests specific
antiemetic regimens to improve
CINV control. 2 These useful tools
will certainly be refined in the
future as additional evidence on
approaches to CINV is gathered.
Conclusions
CINV can profoundly affect
cancer patients by reducing their
quality of life and thus decreasing
adherence to treatment, with
potential negative effects on
survival and health care costs.
Better antiemetic agents (either
targeting early or delayed
symptoms), together with patient
education initiatives and support
programmes, can reduce the
negative impact of these side
effects without sacrificing the
efficacy of anticancer therapies.
The development and validation of
tools with good predictive accuracy
and high generalisability for the
different types of malignancies will
ultimately contribute to improved,
personalised, emetic therapy
strategies in the oncology
setting.
32 | 2018 | hospitalpharmacyeurope.com
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