COMBINING REGRESSION ANALYSES AND MARKOV MODELS TO INFER AGE-SPECIFIC MORTALITY RATES BY HEPATITIS C INFECTION AND RISK FACTOR STATUS

Purpose: Nearly 2 million Americans are unaware that they are infected with chronic hepatitis C (HCV). HCV screening and treatment may be more efficient in identifiable subgroups with higher HCV prevalence, especially when coupled with programs to reduce mortality risks from comorbidities. No single study contains data needed to estimate subgroup-specific prevalence of HCV, risk factor status, and mortality risks. We developed a combined modeling approach to infer necessary risk-group-specific mortality rates for chronically HCV-infected U.S. adults.

Method: We used logistic regression to estimate age-, sex-, and race-specific HCV infection and risk-factor prevalence using the 2001-08 National Health and Nutrition Examination Survey (NHANES). We defined high-risk status as prior injection drug use, transfusion before 1992, or >20 lifetime sex partners. We analyzed NHANES III (1988-94) linked mortality data using Cox proportional hazards model to obtain hazard ratios (HR) by sex, race, risk, and HCV infection status. We incorporated these estimates into a Markov model to infer the age-, sex-, race-, risk-, and HCV infection status-specific mortality rates that best fit overall age-specific population mortality rates (2006 life tables).

Result: We estimated HCV antibody prevalence for subgroups above age 40. For example, in 50-59 year-olds, prevalence is higher for blacks (7.3% males; 4.8% females) than for non-blacks (4.9% males; 3.2% females). Depending on subgroup, 15-31% are high-risk, and HCV antibody prevalence is higher for high-risk individuals (11-17%) compared to low-risk individuals (2-3%). Adjusting for age in a multivariate model, all-cause mortality rates are higher in men (HR: 1.3 [1.1-1.7]); blacks (HR: 1.7 [1.5-2.1]); high-risk individuals (HR: 1.4 [1.0-1.9]); and HCV infected individuals (HR: 3.5 [2.0-6.0]). We also estimated that for HCV-infected individuals, 20% of mortality is liver-related. Combining these estimates in a Markov model, we inferred sixteen life tables by sex, race, risk, and HCV infection status. Within each subgroup, the life expectancy of high-risk individuals is up to 3 years shorter; similarly, the life expectancy of chronically HCV-infected individuals is up to 9 years shorter.

Conclusion: Quantifying mortality rates of high-risk HCV-infected individuals permits more accurate estimates of the potential benefits of HCV screening and treatment. With 5% of older Americans infected with HCV, cost-effectiveness analyses of expanded HCV screening and treatment require methods to appropriately quantify differential mortality risks.