All-cause mortality among males living with and without HIV initiating long-term opioid therapy, and its association with opioid dose, opioid interruption and other factors.

BACKGROUND: While the relationship between long-term opioid therapy (LTOT) dose and overdose is well-established, LTOT's association with all-cause mortality is less understood, especially among people living with HIV (PLWH). There is also limited information regarding the association of LTOT cessation or interruption with mortality. METHODS: Among PLWH and matched uninfected male veterans in care, we identified those who initiated LTOT. Using time-updated cox regression, we examined the association between all-cause mortality, unnatural death, and overdose, and opioid use categorized as 1-20 (reference group), 21-50, 51-90, and ≥ 91 mg morphine equivalent daily dose (MEDD). RESULTS: There were 22,996 patients on LTOT, 6,578 (29 %) PLWH and 16,418 (71 %) uninfected. Among 5,222 (23 %) deaths, 12 % were unnatural deaths and 6 % overdoses. MEDD was associated with risk of all 3 outcomes; compared to patients on 1-20 mg MEDD, adjusted risk for all-cause mortality monotonically increased (Hazard Ratios (HR) [95 % CI] for 21-50 mg MEDD = 1.36 [1.21, 1.52], 51-90 mg MEDD = 2.06 [1.82, 2.35], and ≥ 91 mg MEDD = 3.03 [2.71, 3.39]). Similar results were seen in models stratified by HIV. LTOT interruption was also associated with all-cause, unnatural, and overdose mortality (HR [95 % CI] 2.30 [2.09, 2.53], 1.47 [1.13, 1.91] and 1.52 [1.04, 2.23], respectively). CONCLUSIONS: Among PLWH and uninfected patients on LTOT we observed a strong dose-response relationship with all 3 mortality outcomes. Opioid risk mitigation approaches should be expanded to address the potential effects of higher dose on all-cause mortality in addition to unnatural and overdose fatalities.

The impact of prescribed opioids on CD4 cell count recovery among HIV-infected patients newly initiating antiretroviral therapy.

OBJECTIVES: Certain prescribed opioids have immunosuppressive properties, yet their impact on clinically relevant outcomes, including antiretroviral therapy (ART) response among HIV-infected patients, remains understudied. METHODS: Using the Veterans Aging Cohort Study data, we conducted a longitudinal analysis of 4358 HIV-infected patients initiating ART between 2002 and 2010 and then followed them for 24 months. The primary independent variable was prescribed opioid duration, categorized using pharmacy data as none prescribed, short-term (< 90 days) and long-term (≥ 90 days). Outcomes included CD4 cell count over time. Analyses adjusted for demographics, comorbid conditions, ART type and year of initiation, and overall disease severity [ascertained with the Veterans Aging Cohort Study (VACS) Index]. Sensitivity analyses examined whether effects varied according to baseline CD4 cell count, achievement of viral load suppression, and opioid properties (i.e. dose and known immunosuppressive properties). RESULTS: Compared to those with none, patients with short-term opioids had a similar increase in CD4 cell count (mean rise per year: 74 vs. 68 cells/µL; P = 0.11), as did those with long-term prescribed opioids (mean rise per year: 74 vs. 75 cells/µL; P = 0.98). In sensitivity analysis, compared with no opioids, the effects of short-term prescribed opioids were statistically significant among those with a baseline CD4 cell count ≥ 500 cells/µL (mean rise per year: 52 cells/µL for no opioids vs. 20 cells/µL for short-term opioids; P = 0.04); findings were otherwise unchanged. CONCLUSIONS: Despite immunosuppressive properties intrinsic to opioids, prescribed opioids appeared to have no effect on CD4 cell counts over 24 months among HIV-infected patients initiating ART.

Towards a combined prognostic index for survival in HIV infection: the role of 'non-HIV' biomarkers.

BACKGROUND: As those with HIV infection live longer, 'non-AIDS' condition associated with immunodeficiency and chronic inflammation are more common. We ask whether 'non-HIV' biomarkers improve differentiation of mortality risk among individuals initiating combination antiretroviral therapy (cART). METHODS: Using Poisson models, we analysed data from the Veterans Aging Cohort Study (VACS) on HIV-infected veterans initiating cART between 1 January 1997 and 1 August 2002. Measurements included: HIV biomarkers (CD4 cell count, HIV RNA and AIDS-defining conditions); 'non-HIV' biomarkers (haemoglobin, transaminases, platelets, creatinine, and hepatitis B and C serology); substance abuse or dependence (alcohol or drug); and age. Outcome was all cause mortality. We tested the discrimination (C statistics) of each biomarker group alone and in combination in development and validation data sets, over a range of survival intervals, and adjusting for missing data. RESULTS: Of veterans initiating cART, 9784 (72%) had complete data. Of these, 2566 died. Subjects were middle-aged (median age 45 years), mainly male (98%) and predominantly black (51%). HIV and 'non-HIV' markers were associated with each other (P < 0.0001) and discriminated mortality (C statistics 0.68-0.73); when combined, discrimination improved (P < 0.0001). Discrimination for the VACS Index was greater for shorter survival intervals [30-day C statistic 0.86, 95% confidence interval (CI) 0.80-0.91], but good for intervals of up to 8 years (C statistic 0.73, 95% CI 0.72-0.74). Results were robust to adjustment for missing data. CONCLUSIONS: When added to HIV biomarkers, 'non-HIV' biomarkers improve differentiation of mortality. When evaluated over similar intervals, the VACS Index discriminates as well as other established indices. After further validation, the VACS Index may provide a useful, integrated risk assessment for management and research.

Co-morbid medical and psychiatric illness and substance abuse in HCV-infected and uninfected veterans.

Comorbidities may affect the decision to treat chronic hepatitis C virus (HCV) infection. We undertook this study to determine the prevalence of these conditions in the HCV-infected persons compared with HCV-uninfected controls. Demographic and comorbidity data were retrieved for HCV-infected and -uninfected subjects from the VA National Patient Care Database using ICD-9 codes. Logistic regression was used to determine the odds of comorbid conditions in the HCV-infected subjects. HCV-uninfected controls were identified matched on age, race/ethnicity and sex. We identified 126 926 HCV-infected subjects and 126 926 controls. The HCV-infected subjects had a higher prevalence of diabetes, anaemia, hypertension, chronic obstructive pulmonary disease (COPD)/asthma, cirrhosis, hepatitis B and cancer, but had a lower prevalence of coronary artery disease and stroke. The prevalence of all psychiatric comorbidities and substance abuse was higher in the HCV-infected subjects. In the HCV-infected persons, the odds of being diagnosed with congestive heart failure, diabetes, anaemia, hypertension, COPD/asthma, cirrhosis, hepatitis B and cancer were higher, but lower for coronary artery disease and stroke. After adjusting for alcohol and drug abuse and dependence, the odds of psychiatric illness were not higher in the HCV-infected persons. The prevalence and patterns of comorbidities in HCV-infected veterans are different from those in HCV-uninfected controls. The association between HCV and psychiatric diagnoses is at least partly attributable to alcohol and drug abuse and dependence. These factors should be taken into account when evaluating patients for treatment and designing new intervention strategies.

Impact of hepatitis C virus infection and other comorbidities on survival in patients on dialysis.

The impact of hepatitis C virus (HCV) and other comorbid conditions upon survival is not well quantified in patients on dialysis. We identified HCV-infected and uninfected persons in the USRDS using claims data in 1997-1998 and followed until September 22, 2002 or death. We used Gray's time-varying coefficients model to examine factors associated with survival. Subjects with a renal transplant were excluded. A total of 5737 HCV-infected and 11 228 HCV-uninfected persons were identified. HCV-infected subjects were younger (mean age 57.8 vs 65.3 years), more likely to be male (57.6%vs 49.6%) and black (54.0%vs 36.4%). They were more likely to have a diagnosis of drug (16.5%vs 4.6%) and alcohol use (14.0%vs 3.1%), and to be human immunodeficiency virus (HIV) co-infected (7.4%vs 1.8%) (all comparisons, P < 0.0005). In an adjusted Gray's time-varying coefficient model, HCV was associated with an increased risk of mortality (P < 0.0005). The hazards were highest at the time of HCV diagnosis and decreased to a stable level 2 years after diagnosis. Other factors associated with increased risk of mortality were (P < 0.0005 unless stated) HIV coinfection; diagnosis of drug use (P = 0.001); coronary artery disease (P = 0.006); stroke; diabetes as the primary cause for renal failure; peripheral vascular disease; depression and presence of anaemia. HCV was associated with higher risk of death in patients on dialysis, even after adjusting for concurrent comorbidities. The risk was highest at the time of HCV diagnosis and stabilized over time. Clinical trials of HCV screening and treatment to reduce mortality in this population are warranted.

Rates and predictors of hepatitis C virus treatment in HCV-HIV-coinfected subjects.

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.