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) 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 | 2019 | hospitalpharmacyeurope.com
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