studies

1138A AASLD ABSTRACTS HEPATOLOGY, October, 2015
1905
WITHDRAWN
1906
LI-RADS hepatocellular carcinoma diagnostic classification
system: utilization by community radiologists, and
results of second opinion reading by staff radiologists at
a transplant center
Jesse M. Civan 1 , Aaron Martin 2 , Raza Hasan 2 , Flavius Guglielmo
3 , Sandeep Deshmukh 3 , Christopher G. Roth 3 , Donald G.
Mitchell 3 ; 1 Gastroenterology & Hepatology, Thomas Jefferson University
Hospital, Philadelphia, PA; 2 Internal Medicine, Thomas Jefferson
University, Philadelphia, PA; 3 Radiology, Thomas Jefferson
University, Philadelphia, PA
Background: LI-RADS (Liver Imaging Reporting and Data System)
was created to clarify radiographic degree of concern
for hepatocellular carcinoma (HCC). In 2013, UNOS adopted
criteria analogous to LI-RADS category 5 (definite HCC) for
lesions to qualify for HCC MELD exception. We evaluated
LI-RADS utilization by community radiologists, inter-operator
agreement of LI-RADS scoring, and prediction of LI-RADS classification
by descriptive language. Methods: We reviewed 150
outside abdominal MRI and CT studies that were overread
(formal consultation) by radiology specialists at a transplant
center. Studies performed at other academic centers were
excluded. We abstracted qualitative phrases used by outside
radiologists in lieu of LI-RADS to convey degree of concern
for HCC. Statistical analysis was performed using SPSS v23.
Results: LI-RADS classification was provided in 13% of cases by
outside radiologists and 88% of internal re-reads. For outside
reports utilizing LI-RADS, correlation with our LI-RADS classification
was poor, Spearman 0.00 (p=0.99) for combined
LI-RADS 4/5, Spearman 0.07 (p=0.82) for LI-RADS 5. For outside
reports not utilizing LI-RADS, 16 distinct qualitative phrases
were used to convey degree of concern for HCC, many of
which did not map clearly to a LI-RADS category (e.g. “in
keeping with HCC”, “could represent HCC”). Overall, descriptive
terms did not predict a combined outcome of the presence
of LI-RADS 4 or 5 lesions (Cramer’s V=0.48, p=0.27),
or presence of LI-RADS 5 lesions alone (Cramer’s V=0.56,
p=0.06). Correlation between individual descriptive phrases
and LI-RADS classification is depicted in figure 1. Conclusion:
The LI-RADS classification system is under-utilized in the community
setting. Qualitative language used in outside radiology
reports poorly predicted diagnosis of probable or definite HCC
by LI-RADS criteria.
Disclosures:
Jesse M. Civan - Consulting: Merck
The following authors have nothing to disclose: Aaron Martin, Raza Hasan,
Flavius Guglielmo, Sandeep Deshmukh, Christopher G. Roth, Donald G. Mitchell
1907
A Model to Estimate Survival in Ambulatory Patients
with Hepatocellular Carcinoma: Can It Predict the Natural
Course of Hepatocellular Carcinoma?
Won-Mook Choi 1 , Su Jong Yu 2 , Young Youn Cho 2 , Eun Ju Cho 2 ,
Jeong-Hoon Lee 2 , Yoon Jun Kim 2 , Jung-Hwan Yoon 2 , June Sung
Lee 3 ; 1 Graduate School of Medical Science and Engineering,
Korea Advanced Institute of Science and Technology(KAIST), Daejeon,
Korea (the Republic of); 2 Department of Internal Medicine
and Liver Research Institute, Seoul National University College of
Medicine, Seoul, Korea (the Republic of); 3 Department of Internal
Medicine, Ilsan Paik Hospital, Inje University College of Medicine,
Goyang, Korea (the Republic of)
Objectives: Several hepatocellular carcinoma (HCC) staging
systems are available; however, whether these staging systems
could predict the natural course of HCC is largely unknown.
This study aimed to investigate whether the various HCC staging
systems could reflect the natural course of HCC. Methods:
1116 patients with history of HCC treatment and 111 patients
without any history of treatment till death or last follow-up at a
single tertiary hospital were included. To minimize selection
bias, patients with treatment were matched using propensity-score
matching at a 1:1 ratio with patients without treatment.
The model’s performance was assessed and compared to other
staging systems using C-statistics and Akaike information criterion
(AIC). Results: In the group of treated patients before
propensity score matching, the Model to Estimate Survival
in Ambulatory HCC patients (MESIAH) score showed higher
predictive performance, with a C-statistic of 0.832 (95% confidence
interval [CI], 0.808-0.856), when compared to the
Barcelona Clinic Liver Cancer staging system and the seventh
edition of the American Joint Committee on Cancer TNM staging
system. However, in the group of untreated patients, all
staging systems including the MESIAH score failed to predict
survival. After propensity score matching, although the MESIAH
score was balanced between the two groups (5.89±1.35 and
5.94±1.45, P=0.60), the treated group survived longer than
the untreated group, which suggests that treatment by itself did
prolong survival. Moreover, even the MESIAH score failed to
predict outcome of not only the untreated group but also the
treated group after propensity score matching. Conclusions:
Although the MESIAH score provided better prognostic stratification
than other staging systems, it also was not helpful
in predicting the natural course of HCC. Since the preferred
treatment modality is varied by multiple factors, it is necessary
to develop a new staging system that reflects the natural course
of HCC regardless of treatment.