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Predicting
Cirrhosis in Patients with Hepatitis C Based on Use of Standard
Laboratory Tests
Knowledge
of the presence of cirrhosis
is important for the management of patients with
chronic hepatitis C (CHC). Most models for predicting cirrhosis
were derived from small numbers of patients and included subjective
variables or laboratory tests that are not readily available.
The
aim of this study was to develop a predictive model of cirrhosis
in patients with CHC based on standard laboratory tests.
Data
from 1,141 CHC patients including 429 with cirrhosis were
analyzed. All biopsies were read by a panel of pathologists
(blinded to clinical features), and fibrosis
stage was determined by consensus.
The
cohort was divided into a training set (n = 783) and a validation
set (n = 358).
The
area under the receiver-operating characteristic curve of
the final model comprising
platelet count, AST/ALT
ratio, and INR in the training and validation sets was 0.78
and 0.81, respectively.
A
cutoff of less than 0.2 to exclude cirrhosis would misclassify
only 7.8% of patients with cirrhosis, while a cutoff of greater
than 0.5 to confirm cirrhosis would misclassify 14.8% of patients
without cirrhosis.
The
model performed equally well in fragmented and non-fragmented
biopsies and in biopsies of varying lengths.
Use
of this model might obviate the requirement for a liver biopsy
in 50% of patients with CHC, according to the authors.
Based
on these results, the authors conclude, “A model based on
standard laboratory test results can be used to predict histological
cirrhosis with a high degree of accuracy in 50% of patients
with CHC.”
Commentary
“Our
model should perform well in clinical practice,” state the
authors. However, they also note that the formula is complex,
requiring access to a calculator or computer, which might
not be available in a busy clinic.
For
this reason they have also included the model prediction according
to convenient levels of platelet count, AST/ALT
ratio, and INR. The resulting table provided predicted
probabilities of cirrhosis that were close to the observed
prevalence. “Thus these simple algorithms could be applied
with a fair degree of accuracy in practice to make informed
decisions regarding the need for a liver
biopsy,” according to the authors.
“In
conclusion,” write the authors, “we demonstrated that a model
based on a few standard laboratory tests can be used to predict
histological cirrhosis with a high degree of accuracy in patients
with CHC and advanced fibrosis. Relying on cutoff values of
less than 0.2 and more than 0.5, we could have distinguished
between the presence and absence of cirrhosis with sufficient
reliability to avoid a liver biopsy in half of our patients.”
“Theoretically,
application of this model in practice could be cost-saving
and helpful in identifying patients with CHC who require surveillance
for hepatocellular
carcinoma and varices as well as closer monitoring during
antiviral therapy.”
Finally,
the authors emphasize, “Clearly, our model needs to be validated
by other investigators. Our results and those of similar studies
underscore the need for development of noninvasive methods
that reflect histological findings in patients with all forms
of chronic liver disease.”
07/18/05
Reference
A
S Lok and others. Predicting cirrhosis
in patients with hepatitis C based on standard laboratory
tests: Results of the HALT-C cohort. Hepatology 42(2):
282-292. August 2005.
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