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European journal of clinical investigation, 2021-07, Vol.51 (7), p.e13542-n/a
2021
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Autor(en) / Beteiligte
Titel
Pattern of macrovascular invasion in hepatocellular carcinoma
Ist Teil von
  • European journal of clinical investigation, 2021-07, Vol.51 (7), p.e13542-n/a
Ort / Verlag
England: Blackwell Publishing Ltd
Erscheinungsjahr
2021
Quelle
MEDLINE
Beschreibungen/Notizen
  • Background and aims In patients with hepatocellular carcinoma (HCC), macrovascular invasion (MaVI) limits treatment options and decreases survival. Detailed data on the relationship between MaVI extension and patients' characteristics, and its impact on patients' outcome are limited. We evaluated the prevalence and extension of MaVI in a large cohort of consecutive HCC patients, analysing its association with liver disease and tumour characteristics, as well as with treatments performed and patients' survival. Methods We analysed data of 4774 patients diagnosed with HCC recorded in the Italian Liver Cancer (ITA.LI.CA) database (2008‐2018). Recursive partition analysis (RPA) was performed to evaluate interactions between MaVI, clinical variables and treatment, exploring the inter‐relationship determining overall survival. Results MaVI prevalence was 11.1%, and median survival of these patients was 6.0 months (95% CI, 5.1‐7.1). MaVI was associated with younger age at diagnosis, presence of symptoms, worse Performance Status (PS) and liver function, high alphafetoprotein levels and large HCCs. MaVI extension was associated with worse PS, ascites and greater impairment in liver function. RPA identified patients' categories with different treatment indications and survival, ranging from 2.4 months in those with PS > 1 and ascites, regardless of MaVI extension (receiving best supportive care in 90.3% of cases), to 14.1 months in patients with PS 0‐1, no ascites and Vp1‐Vp2 MaVI (treated with surgery in 19.1% of cases). Conclusions MaVI presence and extension, together with PS and ascites, significantly affect patients' survival and treatment selection. The decision tree based on these parameters may help assess patients' prognosis and inform therapeutic decisions.

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