The mean Quan-Charlson comor-bidity index for patients in the first, second, third, and fourth quartiles of healthcare
costs were 0.3, 0.5, 0.5, and 0.8, respectively. Greater than 90 %of patients in each quartile were non-cirrhotic. The corresponding proportion of patients with cirrhosis at baseline was 0.9%, 1.6%, 1.5%, and 2.5 %and end stage liver disease (ESLD) at baseline was 0.9%, 1.6%, 2.8 selleck inhibitor %and 6.3%, respectively. Compared to the lowest costs quartile group, the highest quartile group had a higher proportion of patients with diabetes (17.2 %vs. 6.1%), psychiatric disease (11.8 %vs. 5.3%), depression (11.9 %vs. 2.8%), substance abuse (6.9 %vs. 3.0%), ≥2 CHC-related conditions (16.4 %vs. 3.2%), and ≥2 non-CHC conditions (4.9 %vs. 1.6%). The strongest predictors of being in the highest cost quartile were ESLD (odds ratio relative to first quartile [OR; 95%CI]; 3.00 [1.45-6.21]), having two or more non-CHC conditions find more (OR: 1.92 [1.25-2.96]), and medical visits to a gastroenterologist (OR: 1.32 [1.05-1.66]). Conclusions: This real-world study suggests that CHC patients with the highest healthcare resource utilization and costs had a high level
of comorbidity at baseline, and that non-CHC conditions are strong predictors of high healthcare costs. Since the majority of patients across quartiles of HRU were non-cirrhotic, liver disease severity alone does not fully predict high HRU consumption, although when present it is a predictor of high HRU. Disclosures: Joyce LaMori – Employment: Janssen Scientific Affairs, LLC; Stock Shareholder: Johnson & Johnson Neeta Tandon – Employment: Johnson & Johnson Co Francois Laliberte – Grant/Research Support: Janssen Scientific Affairs 上海皓元医药股份有限公司 Guillaume
Germain – Grant/Research Support: Janssen Scientific Affairs, LLC D. Pilon – Employment: Analysis Group Patrick Lefebvre – Grant/Research Support: Janssen Scientific Affairs Avinash Prabhakar – Employment: Janssen Scientific Affairs, LLC Background: More than 200,000 individuals are estimated to have chronic HCV infection in Poland; however, only 15 %have been diagnosed. A modeling approach was used to examine HCV-related disease progression and evaluate the strategies required to control disease burden or eliminate HCV disease. Methods: The infected population and associated disease progression were modeled using 36 age- and gender-defined cohorts to track HCV incidence, prevalence, hepatic complications and mortality. Baseline assumptions and transition probabilities were extracted from the literature. The impacts of two scenarios on HCV-related disease burden were considered through increases in SVR, treatment and diagnosis (elimination only). Results: Under the baseline scenario, 201,000 individuals were chronically infected in Poland in 2013. In 2013, it is estimated that 76 %of the infected population was born between 1949 and 1988.