Background

We estimated and characterized the proportion of patients living with HIV (PLWH) who missed hepatitis C (HCV) intake appointments and subsequently failed to establish HCV care.

Methods

Logistic regression analyses were used to identify factors associated with missed HCV intake appointments and failure to establish HCV care among PLWH referred for HCV treatment between January 2014 and December 2017. In addition to demographics, variables included HIV treatment characteristics, type of insurance, liver health status, active alcohol or illicit drug use, unstable housing, and history of a mental health disorder (MHD).

Results

During the study period, 349 new HCV clinic appointments were scheduled for 202 unduplicated patients. Approximately half were nonwhite, and 80% had an undetectable HIV viral load. Drug use (31.7%), heavy alcohol use (32.8%), and MHD (37.8%) were prevalent. Over the 4-year period, 21.9% of PLWH referred for HCV treatment missed their HCV intake appointment. The proportion increased each year, from 17.2% in 2014 to 25.4% in 2017 (P = .021). Sixty-six of the 202 newly referred HCV patients (32.7%) missed their first HCV appointment, and 28 of these (42.4%) failed to establish HCV care. Having a history of MHD, CD4 <200, ongoing drug use, and being nonwhite were independent predictors of missing an intake HCV appointment. The strongest predictor of failure to establish HCV care was having a detectable HIV viral load.

Conclusions

The proportion of PLWH with missed HCV appointments increased over time. HCV elimination among PLWH may require integrated treatment of MHD and substance use.

Cause-specific mortality is an important outcome in studies of interventions to improve survival, yet causes of death can be misclassified. Here, we present an approach to performing sensitivity analyses for misclassification of cause of death in the parametric g-formula. The g-formula is a useful method to estimate effects of interventions in epidemiologic research because it appropriately accounts for time-varying confounding affected by prior treatment and can estimate risk under dynamic treatment plans. We illustrate our approach using an example comparing acquired immune deficiency syndrome (AIDS)-related mortality under immediate and delayed treatment strategies in a cohort of therapy-naive adults entering care for human immunodeficiency virus infection in the United States. In the standard g-formula approach, 10-year risk of AIDS-related mortality under delayed treatment was 1.73 (95% CI: 1.17, 2.54) times the risk under immediate treatment. In a sensitivity analysis assuming that AIDS-related death was measured with sensitivity of 95% and specificity of 90%, the 10-year risk ratio comparing AIDS-related mortality between treatment plans was 1.89 (95% CI: 1.13, 3.14). When sensitivity and specificity are unknown, this approach can be used to estimate the effects of dynamic treatment plans under a range of plausible values of sensitivity and specificity of the recorded event type.

Background

It is unknown whether gaining inpatient health care coverage had an effect on hospitalization rates among persons with HIV (PWH) after implementation of the Affordable Care Act in 2014.

Methods

Hospitalization data from 2015 were obtained for 1634 adults receiving longitudinal HIV care at 3 US HIV clinics within the HIV Research Network. All patients were engaged in care and previously uninsured and supported by the Ryan White HIV/AIDS Program in 2013. We evaluated whether PWH who transitioned to either Medicaid or private insurance in 2014 tended to have a change in hospitalization rate compared with PWH who remained uncovered and Ryan White HIV/AIDS Program supported. Analyses were performed by negative binomial regression with robust standard errors, adjusting for gender, race/ethnicity, age, HIV risk factor, CD4 count, viral load, clinic site, and 2013 hospitalization rate.

Results

Among PWH without inpatient health care coverage in 2013, transitioning to Medicaid [adjusted incidence rate ratio 1.26, (0.71, 2.23)] or to private insurance [0.48 (0.18, 1.28)] in 2014 was not associated with 2015 hospitalization rates, after accounting for demographics, HIV characteristics, and prior hospitalization rates. The factors significantly associated with higher hospitalization rates include age 55-64, CD4 <200 cells/µL, viral load >400 copies/mL, and 2013 hospitalization rate.

Conclusions

Acquiring inpatient coverage was not associated with a change in hospitalization rates. These results provide some evidence to allay the concern that acquiring inpatient coverage would lead to increased inpatient utilization.

Among 1942 persons with human immunodeficiency virus (HIV) without healthcare coverage in 2012-2015, transitioning to Medicaid (adjusted prevalence ratio, 0.95 [0.87, 1.04]) or to private health insurance (1.04 [0.95, 1.13]) was not associated with a change in consistent HIV viral suppression compared to continued reliance on the Ryan White HIV/AIDS Program.

Background

Antiretroviral therapy (ART) durability, time to modification or cessation, has declined. The study objective was to determine whether kidney dysfunction is contributing to reduced durability.

Methods

This retrospective follow-up study of CNICS evaluated treatment-naive PLWH initiating ART between 2007 and 2014. Regimen modification was defined as cessation/modification of any part of the 3-drug ART regimen. We evaluated the role of kidney dysfunction in initial regimen modification as both a mediator and effect measure modifier. Associations of the variables with the ART modification were examined using univariable and multivariable Cox proportional hazard models.

Results

Of 4515 PLWH included in the analysis, 1967 modified their ART. Of those receiving TDF-based ART (n = 3888), 1580 (41%) modified their regimen compared with 387 (62%) receiving other regimens. Overall, the median eGFR decreased by 5 mL/min/1.73 m (quartiles: first = -16, third = 0) from baseline to follow-up. Of the 128 patients with low baseline eGFR (<60 mL/min/1.73 m), the final eGFR remained low in 73% while it increased to above 60 mL/min/1.73 m in 27%. Of the 4387 with normal baseline eGFR, only 135 (3%) had a final eGFR <60 mL/min/1.73 m. Those with low eGFR at the baseline and/or final visits were more likely to modify ART than others (hazards ratio = 1.75, 95% confidence interval: 1.39 to 2.19, P < 0.001). Relative to other regimens, TDF-based ART was less likely to be modified when accounting for numerous clinical and demographic traits.

Conclusions

For patients in our study initiated on ART, including TDF-based ART, in the last decade, kidney dysfunction is not a major factor leading to regimen modification.

The disparity in viral suppression rates between Latino and non-Latino White patients in HIV care appears to be narrowing, but it is unclear if depression and substance use perpetuate this disparity. We analyzed electronic medical records from the CFAR network of integrated clinical systems cohort. First observations/enrollment data collected between 2007 and 2013 were analyzed, which included survey (race/ethnicity, depression, substance use, adherence) and clinical data (viral suppression). We estimated indirect effects with a regression-based bootstrapping method. In 3129 observations, Latinos and non-Latino Whites did not differ in depression or alcohol use (ORs 1.11, 0.99, ns), but did in drug use (OR 1.13, p < .001). For all patients, depression and substance use were indirectly associated with small increases (ORs 1.02-1.66) in the odds for a detectable viral load, via worse adherence. We conclude that variables not captured in EMR systems (e.g., health literacy, structural factors) may better explain viral suppression disparities that persist.

Marginal structural models for time-fixed treatments fit using inverse-probability weighted estimating equations are increasingly popular. Nonetheless, the resulting effect estimates are subject to finite-sample bias when data are sparse, as is typical for large-sample procedures. Here we propose a semi-Bayes estimation approach which penalizes or shrinks the estimated model parameters to improve finite-sample performance. This approach uses simple symmetric data-augmentation priors. Limited simulation experiments indicate that the proposed approach reduces finite-sample bias and improves confidence-interval coverage when the true values lie within the central "hill" of the prior distribution. We illustrate the approach with data from a nonexperimental study of HIV treatments.

Background

The clinical management of low-level viremia (LLV) remains unclear. The objective of this study was to investigate the association of blips and LLV with virologic failure.

Methods

We enlisted patients who newly enrolled into the HIV Research Network between 2005 and 2015, had HIV-1 RNA more than 200 copies/ml, and were either antiretroviral therapy (ART)-naive or ART-experienced and not on ART. Patients were included who achieved virologic suppression (≤50 on two consecutive viral loads) and had at least two viral loads following suppression. Blips and LLV (≥2 consecutive >51 copies/ml) were categorized separately into three categories: no blips/LLV, 51-200, 201-500. Cox proportional hazards regression was used to assess association between rates of blips/LLV and virologic failure (two consecutive >500).

Results

The 2795 patients were mostly male (75.4%), black (50.3%), and MSM (52.9%). Median age was 38 years old (interquartile range 29-48). Most patients (88.8%) were ART-naive at study entry. Overall, 283 (10.1%) patients experienced virologic failure. A total of 152 (5.4%) patients experienced LLV to 51-200 and 110 (3.9%) patients experienced LLV to 201-500. Both LLV 51-200 [adjusted hazard ratio (aHR) 1.83 (1.10,3.04)] and LLV 201-500 [aHR 4.26 (2.65,6.86)] were associated with virologic failure. In sensitivity analysis excluding ART-experienced patients, the association between LLV 51 and 200 and virologic failure was not statistically significant.

Conclusion

LLV between 201 and 500 was associated with virologic failure, as was LLV between 51 and 200, particularly among ART-experienced patients. Patients with LLV below the current Department of Health and Human Services threshold for virologic failure (persistent viremia ≥200) may require more intensive monitoring because of increased risk for virologic failure.

Objective

To explore the effectiveness of raltegravir-based antiretroviral therapy (ART) on treatment response among ART-naive patients seeking routine clinical care.

Design

Cohort study of adults enrolled in HIV care in the United States.

Methods

We compared virologic suppression and CD4 cell count recovery over a 2.5 year period after initiation of an ART regimen containing raltegravir or efavirenz using observational data from a US clinical cohort, generalized to the US population of people with diagnosed HIV. We accounted for nonrandom treatment assignment, informative censoring, and nonrandom selection from the US target population using inverse probability weights.

Results

Of the 2843 patients included in the study, 2476 initiated the efavirenz-containing regimen and 367 initiated the raltegravir-containing regimen. In the weighted intent-to-treat analysis, patients spent an average of 74 (95% confidence interval: 41, 106) additional days alive with a suppressed viral load on the raltegravir regimen than on the efavirenz regimen over the 2.5-year study period. CD4 cell count recovery was also superior under the raltegravir regimen.

Conclusion

Patients receiving raltegravir spent more time alive and suppressed than patients receiving efavirenz, but the probability of viral suppression by 2.5 years after treatment was similar between groups. Optimizing the amount of time spent in a state of viral suppression is important to improve survival among people living with HIV and to reduce onward transmission.

Missed HIV medical visits predict poor clinical outcomes. We sought to identify patients at high risk of missing visits. We analyzed 2002-2014 data from six large US HIV clinics. At each visit, we predicted the likelihood of missing the next scheduled visit using demographic, clinical, and patient-reported psychosocial variables. Overall, 10,374 participants contributed 105,628 HIV visits. For 17% of visits, the next scheduled appointment was missed. The strongest predictor of a future missed visit was past-year missed visits. A model with only this predictor had area under the receiver operator curve = 0.65; defining "high risk" as those with any past-year missed visits had 73% sensitivity and 51% specificity in correctly identifying a future missed visit. Inclusion of other clinical and psychosocial predictors only slightly improved performance. Past visit attendance can identify those at increased risk for future missed visits, allowing for proactive allocation of resources to those at greatest risk.