92 research outputs found

    Antitumour necrosis factor-α agents and development of new-onset cirrhosis or non-alcoholic fatty liver disease: a retrospective cohort.

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    Objective Elevated tumour necrosis factor (TNF)-α has been implicated in the progression of liver fibrosis and pathogenesis of non-alcoholic fatty liver disease (NAFLD). We aim to investigate the impact of anti-TNF-α agents on the development of cirrhosis and NAFLD. Design This retrospective cohort study used a US claims database between 1 January 2010 and 31 December 2016. We identified adult patients with ankylosing spondylitis, inflammatory bowel disease, psoriatic arthritis or rheumatoid arthritis. Anti-TNF-α agents of interest included adalimumab, certolizumab, etanercept, golimumab and infliximab. The primary composite outcome was the development of new-onset cirrhosis, NAFLD or non-alcoholic steatohepatitis (NASH). The secondary outcomes were the development of (1) cirrhosis and (2) NAFLD or NASH. Propensity score for anti-TNF-α agent use was generated by logistic regression. Cox proportional hazard models adjusting for the propensity score were used with regard to time-varying anti-TNF-α agent exposure. Results This study included 226 555 incident patients with immune-related diseases. During the median 1.5 years follow-up, there was an increased hazard with anti-TNF-α agent use in regard to liver outcomes (composite outcome HR: 1.47, 95% CI 1.27 to 1.70; cirrhosis HR 1.47, 95% CI 0.96 to 2.23; NAFLD or NASH HR 1.53, 95% CI 1.32 to 1.77). The composite outcome hazard was increased for each immune-related disease (HR 1.25-1.90). Conclusion In the short term, we did not observe a beneficial effect of anti-TNF-α agent use for development of cirrhosis, NAFLD or NASH in patients with immune-related diseases

    Overuse Index reported by state

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    We examined overuse among Medicare beneficiaries at the state level by generating the Overuse Index, for each U.S. state and the District of Columbia. We previously created an Overuse Index that uses billing codes for diverse clinical services that act as indicators to reflect the latent tendency of a region to overuse health care resources relative to other regions. We newly operationalized our approach to first measure overuse among Medicare beneficiaries within hospitals and their associated outpatient clinics, before we apply the model to generate the Overuse Index at the levels of interest (health systems, regions, or states.) We accessed 100% of the inpatient and outpatient claims, and the Master Beneficiary Summary files of Medicare beneficiaries from July 2015 through December 2018 through the Center for Medicare and Medicaid Services’ (CMS) Virtual Research Data Center (VRDC). Seventeen indicator procedures contributed to the Overuse Index. This set included five new indicators compared to our earlier work. We ran a model across the 17 indicators with fixed effects for states, indictors, and year-quarter; hospital-level random effects, and hospital-level patient characteristics. The fixed effects for the states are the Overuse Index for that state, and represent the tendency for state-wide overuse of healthcare relative to the average state. This was then normalized so the average is 0 with a S.D. of 1
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