Impact of large regenerative, low grade and high

liver411

[B]grade dysplastic nodules in hepatocellular carcinoma development.[/B]

Hepatol. 2003 Aug;39(2):208-14.
Borzio M, Fargion S, Borzio F, Fracanzani AL, Croce AM, Stroffolini T,
Oldani S, Cotichini R, Roncalli M.

Department of Medicine, Gastroenterology Unit, Ospedale Fatebenefratelli,
C.so Porta Nuova 23, 20121, Milan, Italy

BACKGROUND/AIMS: The natural outcome of ultrasound-detected macronodules in
cirrhosis is still poorly understood. In this study we assessed the
incidence and predictors of malignant transformation in a prospective study
of 90 consecutive ultrasound-detected macronodules in cirrhosis.METHODS:
Macronodules classification was based on recently proposed histological
criteria. Extranodular large (LCC) and small cell changes were also
evaluated. The follow-up included ultrasound and serum alfa-fetoprotein
determination every 3 months. Independent predictors of hepatocellular
carcinoma were evaluated by Cox proportional hazards regression
analysis.RESULTS: During a mean follow-up of 33 months, 28 (31%) nodules
transformed into hepatocellular carcinoma. The incidence of hepatocellular
carcinoma per 100 person-years of follow-up was 11.3%, with a malignant
transformation rate of 3.5, 15.5, 31 and 48.5% at 1, 2, 3, and 5 years
respectively. High-grade dysplastic nodules (HGDN) (hazard risk=2.4; CI
95%=1.1-5.0) and LCC (hazard risk=3.1; CI 95%=1.2-7.8) were independent
predictors of malignant transformation. Eight additional hepatocellular
carcinomas developed outside the original lesions raising the overall
malignant transformation rate to 40% while 15 macronodules (17%) became
undetectable at ultrasound (US).CONCLUSIONS: Macronodules characterize a
cirrhotic subpopulation with high risk of hepatocellular carcinoma. HGDN and
LCC are strong predictors of malignant transformation; subjects with
simultaneous presence of both these two conditions are at highest risk of
cancer development. The management of cirrhotics with macronodules should be
based on morphologic features detected on liver microsamples.

PMID: 12873817 [PubMed - in process]