Comparative effectiveness research of chronic hepatitis B and C cohort study (CHeCS): improving data collection and cohort identification

BACKGROUND AND AIMS

The Chronic Hepatitis Cohort Study (CHeCS) is a longitudinal observational study of risks and benefits of treatments and care in patients with chronic hepatitis B (HBV) and C (HCV) infection from four US health systems. We hypothesized that comparative effectiveness methods-including a centralized data management system and an adaptive approach for cohort selection-would improve cohort selection while controlling data quality and reducing the cost.

METHODS

Cohort selection and data collection were performed primarily via the electronic health record (EHR); cases were confirmed via chart abstraction. Two parallel sources fed data to a centralized data management system: direct EHR data collection with common data elements, and chart abstraction via electronic data capture. An adaptive Classification and Regression Tree (CART) identified a set of electronic variables to improve case ascertainment accuracy.

RESULTS

Over 16 million patient records were collected on 23 case report forms in 2006-2008. The vast majority of data (99.2%) were collected electronically from EHR; only 0.8% was collected via chart abstraction. Initial electronic criteria identified 12,144 chronic hepatitis patients; 10,098 were confirmed via chart abstraction with positive predictive values (PPV) 79 and 83% for HBV and HCV, respectively. CART-optimized models significantly increased PPV to 88 for HBV and 95% for HCV.

CONCLUSIONS

CHeCS is a comparative effectiveness research project that leverages electronic centralized data collection and adaptive cohort identification approaches to enhance study efficiency. The adaptive CART model significantly improved the positive predictive value of cohort identification methods.

The validity of serum markers for fibrosis staging in chronic hepatitis B and C

Assessment of liver fibrosis is critical for successful individualized disease management in persons with chronic hepatitis B (CHB) or chronic hepatitis C (CHC). We expanded and validated serum marker indices to provide accurate, reproducible and easily applied methods of fibrosis assessment. Liver biopsy results from over 284 CHB and 2304 CHC patients in the Chronic Hepatitis Cohort Study ('CHeCS') were mapped to a F0-F4 equivalent scale. APRI and FIB-4 scores within a 6-month window of biopsy were mapped to the same scale. A novel algorithm was applied to derive and validate optimal cut-offs for differentiating fibrosis levels. For the prediction of advanced fibrosis and cirrhosis, the FIB-4 score outperformed the other serum marker indices in the CHC cohort and was similar to APRI in the CHB cohort. The area under the receiver operating characteristic curves (AUROC) for FIB-4 in differentiating F3-F4 from F0-F2 was 0.86 (95% CI: 0.80-0.92) for CHB and 0.83 (95% CI: 0.81-0.85) for CHC. The suggested cut-offs based on FIB-4 model produced high positive predictive values [CHB: 90.0% for F0-F2, 100.0% for cirrhosis (F4); CHC: 89.7% for F0-F2; 82.9% for cirrhosis (F4)]. In this large observational cohort, FIB-4 predicted the upper and lower end of liver fibrosis stage (cirrhosis and F0-F2, respectively) with a high degree of accuracy in both CHB and CHC patients.