BACKGROUND: True treatment rates and the impact of comorbidities on treatment rates for hepatitis C virus in the HCV-HIV-coinfected subjects are unknown. AIM: To quantify the rates of treatment prescription and the effect of comorbidities on hepatitis C virus treatment rates in HCV-HIV-coinfected veterans. METHODS: The Veterans Affairs National Patient Care Database was used to identify all hepatitis C virus-infected subjects between 1999 and 2003 using ICD-9 codes. Demographics, comorbidities and pharmacy data were retrieved. We used logistic regression to compare the predictors of hepatitis C virus treatment in hepatitis C virus-monoinfected and HCV-HIV-coinfected subjects. FINDINGS: We identified 120 507 hepatitis C virus-infected subjects, of which 6502 were HIV coinfected. 12% of the hepatitis C virus-monoinfected and 7% of the -coinfected subjects were prescribed hepatitis C virus treatment (P < 0.0001). Those not prescribed treatment were older (48.6 years vs. 47.7 years, P = 0.007) and more likely to be black (52% vs. 32%, P < 0.0001). HIV coinfected was less likely to be prescribed hepatitis C virus treatment (OR 0.74, 95% CI: 0.67-0.82). Among the coinfected subjects, the following were associated with non-treatment (OR, 95% CI): black race (0.45, 0.35-0.57); Hispanic race (0.56, 0.38-0.82); drug use (0.68, 0.53-0.88); anaemia (0.17, 0.11-0.26); bipolar disorder (0.63, 0.40-0.99); major depression (0.72, 0.53-0.99); mild depression (0.47, 0.35-0.62). CONCLUSIONS: A small number of HCV-HIV-coinfected veterans are prescribed treatment for hepatitis C virus. Non-treatment is associated with increasing age, minority race, drug use and psychiatric illness. Further studies are needed to determine the eligibility for treatment and reasons for non-treatment for hepatitis C virus.
BACKGROUND: True treatment rates and the impact of comorbidities on treatment rates for hepatitis C virus in the HCV-HIV-coinfected subjects are unknown. AIM: To quantify the rates of treatment prescription and the effect of comorbidities on hepatitis C virus treatment rates in HCV-HIV-coinfected veterans. METHODS: The Veterans Affairs National Patient Care Database was used to identify all hepatitis C virus-infected subjects between 1999 and 2003 using ICD-9 codes. Demographics, comorbidities and pharmacy data were retrieved. We used logistic regression to compare the predictors of hepatitis C virus treatment in hepatitis C virus-monoinfected and HCV-HIV-coinfected subjects. FINDINGS: We identified 120 507 hepatitis C virus-infected subjects, of which 6502 were HIV coinfected. 12% of the hepatitis C virus-monoinfected and 7% of the -coinfected subjects were prescribed hepatitis C virus treatment (P < 0.0001). Those not prescribed treatment were older (48.6 years vs. 47.7 years, P = 0.007) and more likely to be black (52% vs. 32%, P < 0.0001). HIV coinfected was less likely to be prescribed hepatitis C virus treatment (OR 0.74, 95% CI: 0.67-0.82). Among the coinfected subjects, the following were associated with non-treatment (OR, 95% CI): black race (0.45, 0.35-0.57); Hispanic race (0.56, 0.38-0.82); drug use (0.68, 0.53-0.88); anaemia (0.17, 0.11-0.26); bipolar disorder (0.63, 0.40-0.99); major depression (0.72, 0.53-0.99); mild depression (0.47, 0.35-0.62). CONCLUSIONS: A small number of HCV-HIV-coinfected veterans are prescribed treatment for hepatitis C virus. Non-treatment is associated with increasing age, minority race, drug use and psychiatric illness. Further studies are needed to determine the eligibility for treatment and reasons for non-treatment for hepatitis C virus.
Authors: K W Chew; D Bhattacharya; T B Horwich; P Yan; K A McGinnis; C Tseng; M S Freiberg; J S Currier; A A Butt Journal: J Viral Hepat Date: 2017-04-10 Impact factor: 3.728
Authors: Kara W Chew; Debika Bhattacharya; Kathleen A McGinnis; Tamara B Horwich; Chi-Hong Tseng; Judith S Currier; Adeel A Butt Journal: AIDS Res Hum Retroviruses Date: 2015-05-11 Impact factor: 2.205
Authors: Jeffrey J Weiss; Sarah Prieto; Norbert Bräu; Douglas T Dieterich; Sue M Marcus; Alicia Stivala; Jack M Gorman Journal: Int J Psychiatry Med Date: 2018-01-03 Impact factor: 1.210
Authors: Adeel A Butt; Joel Tsevat; Anthony C Leonard; Obaid S Shaikh; Deborah McMahon; Uzma A Khan; Zachariah Dorey-Stein; Vincent Lo Re Journal: Int J Infect Dis Date: 2008-11-06 Impact factor: 3.623
Authors: Souvik Sarkar; Denise A Esserman; Melissa Skanderson; Forrest L Levin; Amy C Justice; Joseph K Lim Journal: J Hepatol Date: 2016-04-27 Impact factor: 25.083