Hepatology Communications,
Год журнала:
2024,
Номер
8(11)
Опубликована: Ноя. 1, 2024
Background:
Professional
guidelines
recommend
HCC
screening
in
at-risk
patients
using
semi-annual
ultrasound
with
or
without
alpha-fetoprotein
(AFP);
however,
this
strategy
has
limited
effectiveness
due
to
low
adherence
and
sensitivity.
Increasing
data
support
the
potential
role
of
blood-based
biomarker
panels,
which
could
improve
both
aspects.
The
panel
GALAD,
comprised
sex,
age,
3
blood
biomarkers
(AFP,
AFP-L3,
des-carboxy
prothrombin
prothrombin),
shown
high
sensitivity
specificity
phase
II
(case-control)
III
(retrospective
cohort)
validation
studies.
However,
prospective
a
large
IV
clinical
utility
trial
is
necessary
before
its
adoption
practice.
Methods:
National
Liver
Cancer
Screening
Trial
an
adaptive
pragmatic
randomized
trial,
began
enrollment
January
2024,
comparing
ultrasound-based
versus
biomarker-based
5500
chronic
hepatitis
B
infection
cirrhosis
from
any
etiology.
Eligible
are
randomly
assigned
1:1
ratio
±
(arm
A)
GALAD
B).
Randomization
stratified
by
site,
liver
disease
severity
(per
Child-Pugh
class),
etiology
(viral,
nonviral,
noncirrhotic
HBV),
sex.
Patients
being
recruited
15
sites
(a
mix
tertiary
care
academic
referral
centers,
safety-net
health
systems,
community
systems)
over
3-year
period,
primary
endpoint,
reduction
late-stage
HCC,
will
be
assessed
at
end
year
5.5.
Discussion:
results
inform
best
for
early-stage
detection
diseases.
If
shows
superiority,
would
primarily
shift
panel.
Registration:
NCT06084234.
Status:
TRACER
Study
actively
enrolling.
Diagnostics,
Год журнала:
2025,
Номер
15(3), С. 252 - 252
Опубликована: Янв. 22, 2025
In
recent
years,
novel
findings
have
progressively
and
promisingly
supported
the
potential
role
of
Artificial
intelligence
(AI)
in
transforming
management
various
neoplasms,
including
hepatocellular
carcinoma
(HCC).
HCC
represents
most
common
primary
liver
cancer.
Alarmingly,
incidence
is
dramatically
increasing
worldwide
due
to
simultaneous
“pandemic”
spreading
metabolic
dysfunction-associated
steatotic
disease
(MASLD).
MASLD
currently
constitutes
leading
cause
chronic
hepatic
damage
(steatosis
steatohepatitis),
fibrosis,
cirrhosis,
configuring
a
scenario
where
an
onset
has
been
reported
even
early
stage.
On
other
hand,
serious
plague,
significantly
burdening
outcomes
hepatitis
B
(HBV)
C
(HCV)
virus-infected
patients.
Despite
progress
this
cancer,
overall
prognosis
for
advanced-stage
patients
continues
be
poor,
suggesting
absolute
need
develop
personalized
healthcare
strategies
further.
“cold
war”,
machine
learning
techniques
neural
networks
are
emerging
as
weapons,
able
identify
patterns
biomarkers
that
would
normally
escaped
human
observation.
Using
advanced
algorithms,
AI
can
analyze
large
volumes
clinical
data
medical
images
(including
routinely
obtained
ultrasound
data)
with
elevated
accuracy,
facilitating
diagnosis,
improving
performance
predictive
models,
supporting
multidisciplinary
(oncologist,
gastroenterologist,
surgeon,
radiologist)
team
opting
best
“tailored”
individual
treatment.
Additionally,
contribute
enhancing
effectiveness
metabolomics–radiomics-based
promoting
identification
specific
HCC-pathogenetic
molecules
new
targets
realizing
therapeutic
regimens.
era
precision
medicine,
integrating
into
routine
practice
appears
promising
frontier,
opening
avenues
cancer
research
Gut,
Год журнала:
2024,
Номер
73(11), С. 1870 - 1882
Опубликована: Июль 25, 2024
Circulating
tumour
DNA
(ctDNA)
is
a
promising
non-invasive
biomarker
in
cancer.
We
aim
to
assess
the
dynamic
of
ctDNA
patients
with
hepatocellular
carcinoma
(HCC).
