1. Time-varying predictors for clinical surveillance of small hepatocellular carcinoma.
- Author
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Liao CS, Yang KC, Yen MF, and Hsiu-Hsi Chen T
- Subjects
- Follow-Up Studies, Humans, Models, Theoretical, Predictive Value of Tests, Prognosis, Sensitivity and Specificity, Survival Analysis, Time Factors, Biomarkers, Tumor analysis, Carcinoma, Hepatocellular pathology, Liver Neoplasms pathology, alpha-Fetoproteins analysis
- Abstract
Purpose: Prognosis of small hepatocellular carcinoma depends on a constellation of time-varying predictors in association with liver function. We aimed to elucidate the impact of these time-dependent predictors on survival., Patients and Methods: A total of 108 patients with hepatocellular carcinoma smaller than 5 cm in diameter were recruited. Series of laboratory data and clinical assessments were retrieved from medical records. The time-dependent scoring system for the prediction of death was developed in accordance with a time-dependent Cox regression model., Results: Time trends for biologic predictors parallel cumulative survival of small hepatocellular carcinoma cases. Higher serum alpha-fetoprotein level was identified as the most significant time-dependent predictor. Other significant predictors included aspartate transaminase, bilirubin, alkaline phosphatase, and albumin levels and prothrombin time. Time-dependent surveillance scoring system shows the cutoff points of scores at 6 months, 1 year, 2 years, and 3 years were 42, 21, 19, and 31, respectively; the estimates of sensitivity, 100%, 100%, 100%, and 87.5%, respectively; and the estimates of specificity, 91.26%, 67.02%, 60.27%, and 78.26%, respectively. Predictive validity for this time-dependent Cox regression model, particularly within 1-year of follow-up, is good., Discussion: The dynamic relationships between time-dependent predictors and risk of death were illustrated. A time-dependent predictive scoring system using these dynamic relationships was developed for real-time surveillance.
- Published
- 2005
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