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Treating Chronic Hepatitis C Infection in the Elderly: Estimated Impact onLife ExpectancyKali Zhou, Jessica Ferguson, David Elashoff, Sammy Saab

Hepatitis C virus (HCV) infection continues to be a significant contributor to morbidity andmortality in the United States and throughout the world. Due to latency of infection, HCVis expected to cause an increasing number of liver-related deaths over the next 10 yearsdespite a dramatic drop in incidence over the last 20 years. The present recommendedtreatment for patients with chronic HCV infection is triple therapy with pegylated interferonα, ribavirin and a protease inhibitor (PI). There are no guidelines for treatment in the elderly(defined as 65 years and older). As the largest cohort with HCV ages, it has become criticalto evaluate the effect of treatment on life expectancy in elderly patients. We used a simpledecision analysis model to simulate the impact of HCV treatment on life expectancy. Cohortsseparated by gender entered the model at five age groups (60 to 80) and at the five stagesof liver fibrosis (F0 to F4). The primary outcome was mean life expectancy and number oflife years gained. Hazard ratios for all-cause mortality in cirrhosis before and after achievingsustained virologic response (SVR) were applied to baseline annual mortality rates to obtainF4-specific mortality rates. Sensitivity analysis was performed to ensure results were robustover a wide range of values. Our model demonstrated that the greatest life expectancy benefitof treatment was derived from treatment of younger patients with higher levels of fibrosis.Overall, men benefitted more than woman, with equalization of this benefit in cirrhosis. Inour base-case scenario with a SVR rate of 70%, the mean years of life expectancy gainedacross all ages and stages of fibrosis were 2.18 years for women and 2.95 years for men.Based on a treatment threshold of 6 months of life expectancy gained, only men between60 and 70 should be treated in the F0 cohort. From F2 and above, all cohorts reached ourthreshold value. The rate of SVR affected number of life years gained but did not substantiallyalter treatment decisions. Elderly patients have higher rates of progression of liver fibrosisand are more likely to present with complications of liver disease. Although prior studieson treatment of patients older on 65 are limited, data exists that these patients respondwith similar rates of SVR as younger patients. Furthermore, recent studies have shown aclear decrease in liver-related morbidity and mortality if SVR is achieved. Given our findingsof improved survival, this study highlights the importance of treatment in this at-risk cohortespecially as shorter regimens and higher SVR rates are anticipated with upcoming PIs. Ourresults provide evidence for consideration of HCV treatment in clinical practice for all menbetween 60- and 70-years of age and any patient of either gender with advanced fibrosisor cirrhosis.Life expectancy gains and treatment recommendations stratified by age, gender and fibrosis

LE = life expectancy; LE values expressed in number of years and based on 70% SVR rate

S-969 AASLD Abstracts

Comparison of life expectancy gains with varying rates of sustained virologic responsebetween F0 and F4 stages of fibrosis. Dotted line represents the treatment threshold of 0.5years of life expectancy gained.

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Regression Model to Predict the Future Prevalence of HCV in HemodialysisHussien Elsiesy, Mohamed Shoukri, Hazem H. Mohamed, Talaat Zakareya, AlmoutazHashim, Mohammed Al Sebayel, Faisal Abaalkhail

Background: Patients undergoing hemodialysis (HD) are at increased risk of contractingHCV infection (HCV). Adherence to infection control measures has resulted in decreasingthe prevalence of HCV in HD patients in Kingdom of Saudi Arabia (KSA) overtime from68% in 1995 to 21% In2011. The number of patients on HD in Saudi Arabia has increasedfrom 3737 patients in 1995 to 12116 patients in 2011 with an annual increase of 7.9%.Aim: Use the pattern of prevalence change in to develop a mathematical model predictingthe future prevalence of HCV infection among HD patients in Saudi Arabia in order to helphealth care delivery and resource allocation. Method: The yearly prevalence of HCV in HDfrom large epidemiologic studies and the Saudi council of organ transplantation from 1995until 2011 were plotted in a graph. Least square simple regression was used to find thebest prediction equation relating the percentage of HCV positive among the Hemodialysispatients. Figure 1 shows both the observed percentages and the fitted straight line. On thehorizontal axis, the year code is 1 for the 1995, 2 for 1996, and 17 for the year 2011. Thepercentage of HCV positives denoted by Y is represented on the vertical axis. As a measureof goodness of fit of the model R2 =0.93, indicating excellent fit. (Figure 1) Result: Theestimated regression equation is: Y= 71.942-3.033 X (year code). This equation may beused to obtain future predictions, a summary of which is shown in table 1: This mathematicalmodel predicted a prevalence of 18.04% in 2012, very close to the actual prevalence reportedlast month for the same year of 18.7% Conclusion: This mathematical model predict thefuture prevalence with high precision, it predict that the prevalence will be as low as theprevalence in general population in year 2018. This will help in planning health care deliveryand resource allocation.Prediction of future prevalence of HCV in HD in KSA

* (the prevalence will equal to the prevalence in the general population, not zero

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