Outcome after Resection for Hepatocellular Carcinoma in Noncirrhotic Liver-A Single Centre Study.
Lea PenzkoferJens MittlerStefan HeinrichNicolas WachterBeate Katharina StraubRoman KlöcknerFabian StoehrSimon Johannes GairingFabian BartschHauke LangPublished in: Journal of clinical medicine (2022)
Liver cirrhosis is the most common risk factor for the development of hepatocellular carcinoma (HCC). However, 10 to 15% of all HCC arise in a non-cirrhotic liver. Few reliable data exist on outcome after liver resection in a non-cirrhotic liver. The aim of this single-centre study was to evaluate the outcome of resection for HCC in non-cirrhotic liver (NC-HCC) and to determine prognostic factors for overall (OS) and intrahepatic recurrence-free (RFS) survival. From 2008 to 2020, a total of 249 patients were enrolled in this retrospective study. Primary outcome was OS and RFS. Radiological and pathological findings, such as tumour size, number of nodules, Tumour-, Nodes-, Metastases- (TNM) classification and vascular invasion as well as extent of surgical resection and laboratory liver function were collected. Here, 249 patients underwent liver resection for NC-HCC. In this case, 50% of patients underwent major liver resection, perioperative mortality was 6.4%. Median OS was 35.4 months (range 1-151 months), median RFS was 10.5 months (range 1-128 moths). Tumour diameter greater than three centimetres, multifocal tumour disease, vascular invasion, preoperative low albumin and increased alpha-fetoprotein (AFP) values were associated with significantly worse OS. Our study shows that resection for NC-HCC is an acceptable treatment approach with comparatively good outcome even in extensive tumours.
Keyphrases
- prognostic factors
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- deep learning
- squamous cell carcinoma
- radiation therapy
- cardiovascular disease
- early stage
- cardiac surgery
- patient reported outcomes
- cell migration
- artificial intelligence
- big data
- rectal cancer
- locally advanced
- data analysis