Initial clinical radiological findings and staging to predict prognosis of primary hepatic angiosarcoma: A retrospective analysis.

2019 
Objective Primary hepatic angiosarcoma (PHA) is extremely rare and most patients die within 12 months of diagnosis. The object of the study is to determine the association of initial clinical-radiological features and staging with outcomes in patients with PHA. Methods The medical records of adult patients with PHA were retrieved from an electronic medical record database and a pathology database and retrospectively reviewed. During 10 years, 22 eligible patients were included. Data extracted focused on the information before the first formal treatment with a pathological proof, including demographic characteristics, medical history, laboratory data, preliminary images, histopathological records, treatment, and follow-up survival period. Two radiologists blindly re-analyzed preliminary images of all 22 patients together and recorded tumor features and imaging stage based on the American Joint Committee on Cancer (AJCC) 8th edition tumor-node-metastasis (TNM) Staging System for hepatocellular carcinoma. A radiologist compiled the initial clinical data and preliminary image stage to analyze the association with patients’ survival outcome. Results Higher aspartate aminotransferase (AST), higher total bilirubin (TB), lower albumin (ALB), longer prothrombin time (PT) and lower platelet count of serum relative to the normal reference range were more common in patients who survived ≤ 90 days (all P < 0.05). Overall survival was much better in patients with single PHA than in those with other tumor patterns of multiple PHA (all P < 0.05). Overall survival determined by preliminary imaging showed significant differences between stage I and stage III (P = 0.044), stage I and stage IV (P = 0.011), and stage III and IV (P = 0.047). No patients were at stage II. Conclusions Initial serum levels of ALT, TB, ALB, and PT, platelet count, single mass in liver, and preliminary imaging staging could help predict survival outcomes of patients with PHA.
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