期刊
CLINICAL GASTROENTEROLOGY AND HEPATOLOGY
卷 19, 期 1, 页码 162-+出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.cgh.2020.04.084
关键词
Liver Cancer; Stratification; Prognostic Factor; Biomarker
资金
- Medical Research Council [MR/R024847/1]
- United Kingdom Research and Innovation Innovation Fellowship
- Medical Research Council research project [MR/R024847/1]
- UK Engineering and Physical Sciences Research Council [EP/N014499/1]
- Wellcome Trust grant [WT107492/Z/15/Z]
- Scottish Government Chief Scientist Office grant [CGA/17/19]
- EPSRC [EP/N014499/1] Funding Source: UKRI
- MRC [MR/L010909/1, MR/R024847/1, MR/M013227/1] Funding Source: UKRI
This study developed and validated a model to assess the risk of hepatocellular carcinoma (HCC) in patients with chronic liver disease based on longitudinal analysis of serum alpha-fetoprotein (AFP) measurements. The model showed good performance in identifying patients who developed HCC, allowing for classification into high-risk and low-risk groups. This model could help in selecting patients for surveillance and improving detection of HCC.
BACKGROUND & AIMS: Ultrasound (US)-based screening has been recommended for patients with an increased risk of hepatocellular carcinoma (HCC). US analysis, however, is limited in patients who are obese or have small tumors. The addition of serum level of alpha-fetoprotein (AFP) measurements to US analysis can increase detection of HCC. We analyzed data from patients with chronic liver disease, collected over 15 years in an HCC surveillance program, to develop a model to assess risk of HCC. METHODS: We collected data from 3450 patients with chronic liver disease undergoing US surveillance in Japan from March 1998 through April 2014, and followed them up for a median of 8.83 years. We performed longitudinal discriminant analysis of serial AFP measurements (median number of observations/patient, 56; approximately every 3 months) to develop a model to determine the risk of HCC. We validated the model using data from 2 cohorts of patients with chronic liver disease in Japan (404 and 2754 patients) and 1 cohort in Scotland (1596 patients). RESULTS: HCC was detected in 413 patients (median tumor diameter, 1.8 cm), during a median follow-up time of 6.60 years. In the development data set, the model identified patients who developed HCC with an area under the curve of 0.78; it correctly identified 74.3% of patients who did develop HCC, and 72.9% of patients who did not. Overall, 73.1% of patients were classified correctly. The model could be used to assign patients to a high-risk group (27.5 HCCs/1000 patient-years) vs a low-risk group (4.9 HCCs/1000 patient-years). A similar performance was observed when the model was used to assess patients with cirrhosis. Analysis of the validation cohorts produced similar results. CONCLUSIONS: We developed and validated a model to identify patients with chronic liver disease who are at risk for HCC based on change in serum AFP level over time. The model could be used to assign patients to high-risk vs low-risk groups, and might be used to select patients for surveillance.
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