Discrimination and Calibration of the Veterans Aging Cohort Study Index 2.0 for Predicting Mortality Among People With Human Immunodeficiency Virus in North America

Adaption and National Validation of a Tool for Predicting Mortality from Other Causes Among Men with Nonmetastatic Prostate Cancer

BACKGROUND

An electronic health record-based tool could improve accuracy and eliminate bias in provider estimation of the risk of death from other causes among men with nonmetastatic cancer.

OBJECTIVE

To recalibrate and validate the Veterans Aging Cohort Study Charlson Comorbidity Index (VACS-CCI) to predict non-prostate cancer mortality (non-PCM) and to compare it with a tool predicting prostate cancer mortality (PCM).

DESIGN, SETTING, AND PARTICIPANTS

An observational cohort of men with biopsy-confirmed nonmetastatic prostate cancer, enrolled from 2001 to 2018 in the national US Veterans Health Administration (VA), was divided by the year of diagnosis into the development (2001-2006 and 2008-2018) and validation (2007) sets.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Mortality (all cause, non-PCM, and PCM) was evaluated. Accuracy was assessed using calibration curves and C statistic in the development, validation, and combined sets; overall; and by age (<65 and 65+ yr), race (White and Black), Hispanic ethnicity, and treatment groups.

RESULTS AND LIMITATIONS

Among 107 370 individuals, we observed 24 977 deaths (86% non-PCM). The median age was 65 yr, 4947 were Black, and 5010 were Hispanic. Compared with CCI and age alone (C statistic 0.67, 95% confidence interval [CI] 0.67-0.68), VACS-CCI demonstrated improved validated discrimination (C statistic 0.75, 95% CI 0.74-0.75 for non-PCM). The prostate cancer mortality tool also discriminated well in validation (C statistic 0.81, 95% CI 0.78-0.83). Both were well calibrated overall and within subgroups. Owing to missing data, 18 009/125 379 (14%) were excluded, and VACS-CCI should be validated outside the VA prior to outside application.

CONCLUSIONS

VACS-CCI is ready for implementation within the VA. Electronic health record-assisted calculation is feasible, improves accuracy over age and CCI alone, and could mitigate inaccuracy and bias in provider estimation.

PATIENT SUMMARY

Veterans Aging Cohort Study Charlson Comorbidity Index is ready for application within the Veterans Health Administration. Electronic health record-assisted calculation is feasible, improves accuracy over age and Charlson Comorbidity Index alone, and might help mitigate inaccuracy and bias in provider estimation of the risk of non-prostate cancer mortality.

Discrimination of the Veterans Aging Cohort Study Index 2.0 for Predicting Cause-specific Mortality Among Persons With HIV in Europe and North America

Background

Predicting cause-specific mortality among people with HIV (PWH) could facilitate targeted care to improve survival. We assessed discrimination of the Veterans Aging Cohort Study (VACS) Index 2.0 in predicting cause-specific mortality among PWH on antiretroviral therapy (ART).

Methods

Using Antiretroviral Therapy Cohort Collaboration data for PWH who initiated ART between 2000 and 2018, VACS Index 2.0 scores (higher scores indicate worse prognosis) were calculated around a randomly selected visit date at least 1 year after ART initiation. Missingness in VACS Index 2.0 variables was addressed through multiple imputation. Cox models estimated associations between VACS Index 2.0 and causes of death, with discrimination evaluated using Harrell's C-statistic. Absolute mortality risk was modelled using flexible parametric survival models.

Results

Of 59 741 PWH (mean age: 43 years; 80% male), the mean VACS Index 2.0 at baseline was 41 (range: 0-129). For 2425 deaths over 168 162 person-years follow-up (median: 2.6 years/person), AIDS (n = 455) and non-AIDS-defining cancers (n = 452) were the most common causes. Predicted 5-year mortality for PWH with a mean VACS Index 2.0 score of 38 at baseline was 1% and approximately doubled for every 10-unit increase. The 5-year all-cause mortality C-statistic was .83. Discrimination with the VACS Index 2.0 was highest for deaths resulting from AIDS (0.91), liver-related (0.91), respiratory-related (0.89), non-AIDS infections (0.87), and non-AIDS-defining cancers (0.83), and lowest for suicides/accidental deaths (0.65).

Conclusions

For deaths among PWH, discrimination with the VACS Index 2.0 was highest for deaths with measurable physiological causes and was lowest for suicide/accidental deaths.

The Association of Prescribed Opioids and Incident Cardiovascular Disease

Opioid prescribing remains common despite known overdose-related harms. Less is known about links to nonoverdose morbidity. We determined the association between prescribed opioid receipt with incident cardiovascular disease (CVD) using data from the Veterans Aging Cohort Study, a national prospective cohort of Veterans with/without Human Immunodeficiency Virus (HIV) receiving Veterans Health Administration care. Selected participants had no/minimal prior exposure to prescription opioids, no opioid use disorder, and no severe illness 1 year after the study start date (baseline period). We ascertained prescription opioid exposure over 3 years after the baseline period using outpatient pharmacy fill/refill data. Incident CVD ascertainment began at the end of the prescribed opioid exposure ascertainment period until the first incident CVD event, death, or September 30, 2015. We used adjusted Cox proportional hazards regression models with matching weights using propensity scores for opioid receipt to estimate CVD risk. Among 49,077 patients, 30% received opioids; the median age was 49 years, 97% were male, 49% were Black, and 47% were currently smoking. Prevalence of hypertension, diabetes, current smoking, alcohol and cocaine use disorder, and depression was higher in patients receiving opioids versus those not but were well-balanced by matching weights. Unadjusted CVD incidence rates per 1,000-person-years were higher among those receiving opioids versus those not: 17.4 (95% confidence interval [CI], 16.5-18.3) versus 14.7 (95% CI, 14.2-15.3). In adjusted analyses, those receiving opioids versus those not had an increased hazard of incident CVD (adjusted hazard ratio 1.16 [95% CI, 1.08-1.24]). Prescribed opioids were associated with increased CVD incidence, making opioids a potential modifiable CVD risk factor. PERSPECTIVE: In a propensity score weighted analysis of Veterans Administration data, prescribed opioids compared to no opioids were associated with an increased hazard of incident CVD. Higher opioid doses compared with lower doses were associated with increased hazard of incident CVD. Opioids are a potentially modifiable CVD risk factor.

"Call 911 - That's my [Advance Care] Plan": Factors that Inform Advance Care Planning Conversation Readiness Among Aging Persons Living With HIV

Antiretroviral therapy has dramatically increased the lifespan of people living with HIV (PLWH), but advance care planning (ACP) and hospice services are underutilized in this population. The purpose of this study was to understand barriers and facilitators to ACP among this group. PLWH (n = 25) were recruited from an HIV Clinic at a Veterans Affairs (VA) Medical Center in Atlanta, GA to represent a range of sociodemographic characteristics and experiences. Semi-structured interviews were analyzed using thematic analysis. More than half of participants (64%) indicated not engaging in ACP. We identified four key barriers to ACP: (1) a self-image among PLWH as "survivors" (and a reluctance to think about ACP); (2) a history of mistrust and mistreatment; (3) weak social ties and a desire to avoid disclosure of HIV status; and (4) a value for self-reliance. Findings have important implications for interventions to overcome these barriers.

Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health Administration

Introduction

As people age with HIV (PWH), many comorbid diseases are more common than among age matched comparators without HIV (PWoH). While the Veterans Aging Cohort (VACS) Index 2.0 accurately predicts mortality in PWH using age and clinical biomarkers, the only included comorbidity is hepatitis C. We asked whether adding comorbid disease groupings from the Charlson Comorbidity Index (CCI) improves the accuracy of VACS Index.

Methods

To maximize our ability to model mortality among older age groups, we began with PWoH in Veterans Health Administration (VA) from 2007-2017, divided into development and validation samples. Baseline predictors included age, and components of CCI and VACS Index (excluding CD4 count and HIV RNA). Patients were followed until December 31, 2021. We used Cox models to develop the VACS-CCI score and estimated mortality using a parametric (gamma) survival model. We compared accuracy using C-statistics and calibration curves in validation overall and within subgroups (gender, age

Results

The analytic sample consisted of 6,588,688 PWoH and 30,539 PWH. Among PWoH/PWH, median age was 65/55 years; 6%/3% were women; 15%/48% were Black and 5%/7% Hispanic. VACS-CCI provided the best discrimination (C-statistic = 0.81) with excellent calibration (predicted and observed mortality largely overlapped) overall and within subgroups. When VACS-CCI was applied to PWH it demonstrated similar discrimination as VACS Index 2.0 (C-statistic = 0.77 for both) but superior calibration among those with CD4 < 200. Discrimination was improved when CD4 and HIV RNA were added VACS-CCI (C-statistic = 0.79). Liver and kidney disease, congestive heart failure, malignancy, and dementia were negatively associated with CD4 (p-trends all <0.0001).

Discussion

Among PWH and PWoH in VA care, age alone weakly discriminates risk of mortality. VACS Index 2.0, CCI, and VACS-CCI all provide better discrimination, but VACS-CCI is more consistently calibrated. The association of comorbid diseases with lower CD4 underscores the likely role of HIV in non-AIDS conditions. Future work will include adding CD4 and HIV RNA to VACS-CCI and validating it in independent data.

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Key Words

• Charlson Comorbidity Index
• HIV
• VACS Index
• mortality
• prediction

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Affiliation(s)

Kathleen A. McGinnis VA Connecticut Healthcare System, West Haven, CT, United States
Amy C. Justice VA Connecticut Healthcare System, West Haven, CT, United States Yale School of Medicine, New Haven, CT, United States
Vincent C. Marconi The Atlanta Veterans Affairs Medical Center, Emory University School of Medicine and Rollins School of Public Health, Atlanta, GA, United States VA Medical Center, Decatur, GA, United States
Maria C. Rodriguez-Barradas Infectious Diseases Section, Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, United States Department of Medicine, Baylor College of Medicine, Houston, TX, United States
Ronald G. Hauser VA Connecticut Healthcare System, West Haven, CT, United States Department of Laboratory Medicine, Yale University School of Medicine, New Haven, CT, United States
Krisann K. Oursler Department of Internal Medicine, Virginia Tech Carilion School of Medicine, Roanoke, VA, United States VA Salem Healthcare System, Salem, VA, United States
Sheldon T. Brown James J. Peters VA Medical Center, Bronx, NY, United States
Kendall J. Bryant National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, United States
Janet P. Tate VA Connecticut Healthcare System, West Haven, CT, United States Yale School of Medicine, New Haven, CT, United States
for the Veterans Aging Cohort Study

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Alcohol use and the longitudinal HIV care continuum for people with HIV who enrolled in care between 2011 and 2019

PURPOSE

We described the impact of alcohol use on longitudinal engagement in HIV care including loss to follow-up, durability of viral suppression, and death.

METHODS

We followed a cohort of 1781 people with HIV from enrolled in care at one of seven US clinics, 2011-2019 through 102 months. We used a multistate, time-varying Markov process and restricted mean time to summarize engagement in HIV care over follow-up according to baseline self-reported alcohol use (none, moderate, or unhealthy).

RESULTS

Our sample (86% male, 54% White) had median age of 35 years. Over 102 months, people with no, moderate, and unhealthy alcohol use averaged 62.3, 61.1, and 59.5 months virally suppressed, respectively. People who reported unhealthy or moderate alcohol use spent 5.1 (95% confidence intervals (CI): 0.8, 9.3) and 7.6 (95%CI: 3.1, 11.7) more months lost to care than nondrinkers. Compared to no use, unhealthy alcohol use was associated with 3.4 (95%CI: -5.6, -1.6) fewer months in care, not virally suppressed. There were no statistically significant differences after adjustment for demographic and clinical characteristics.

CONCLUSIONS

Moderate or unhealthy drinking at enrollment in HIV care was associated with poor retention in care. Alcohol use was not associated with time spent virally suppressed.

Cognitive concerns are a risk factor for mortality in people with HIV and coronavirus disease 2019

BACKGROUND

Data supporting dementia as a risk factor for coronavirus disease 2019 (COVID-19) mortality relied on ICD-10 codes, yet nearly 40% of individuals with probable dementia lack a formal diagnosis. Dementia coding is not well established for people with HIV (PWH), and its reliance may affect risk assessment.

METHODS

This retrospective cohort analysis of PWH with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR positivity includes comparisons to people without HIV (PWoH), matched by age, sex, race, and zipcode. Primary exposures were dementia diagnosis, by International Classification of Diseases (ICD)-10 codes, and cognitive concerns, defined as possible cognitive impairment up to 12 months before COVID-19 diagnosis after clinical review of notes from the electronic health record. Logistic regression models assessed the effect of dementia and cognitive concerns on odds of death [odds ratio (OR); 95% CI (95% confidence interval)]; models adjusted for VACS Index 2.0.

RESULTS

Sixty-four PWH were identified out of 14 129 patients with SARS-CoV-2 infection and matched to 463 PWoH. Compared with PWoH, PWH had a higher prevalence of dementia (15.6% vs. 6%, P  = 0.01) and cognitive concerns (21.9% vs. 15.8%, P  = 0.04). Death was more frequent in PWH ( P  < 0.01). Adjusted for VACS Index 2.0, dementia [2.4 (1.0-5.8), P  = 0.05] and cognitive concerns [2.4 (1.1-5.3), P  = 0.03] were associated with increased odds of death. In PWH, the association between cognitive concern and death trended towards statistical significance [3.92 (0.81-20.19), P  = 0.09]; there was no association with dementia.

CONCLUSION

Cognitive status assessments are important for care in COVID-19, especially among PWH. Larger studies should validate findings and determine long-term COVID-19 consequences in PWH with preexisting cognitive deficits.

Alcohol use, physical activity, and muscle strength moderate the relationship between body composition and frailty risk among people living with HIV

BACKGROUND

Antiretroviral therapy has improved life expectancy among people living with HIV (PLWH). Despite increased longevity, PLWH are at increased risk of age-related comorbidities, including frailty. We examined the relationship between body composition and frailty among PLWH, and moderation of this relationship by substance use, physical activity (PA), and physical function.

METHODS

Participants (n = 341; 71% male, 48 ± 10 years, body mass index (BMI) = 27.3 ± 7.0 kg/m2 ) enrolled in the New Orleans Alcohol Use in HIV (NOAH) study underwent measures of body composition, muscle strength, and gait speed. Whole blood phosphatidylethanol (PEth) was measured, and substance use and PA were self-reported. Frailty risk measures included the 58-Item Deficit Index (DI58) and the Veterans Aging Cohort Study (VACS) Index 1.0, where higher scores indicate greater frailty risk.

RESULTS

Multivariable linear regression adjusted for age, sex, and race showed that higher fat-free mass index (FFMI), body fat (%), waist-to-hip ratio, and body mass index (BMI) ≥ 25.0 kg/m2 vs. < 25.0 kg/m2 were significantly (p < 0.05) associated with decreased frailty risk measured by the VACS Index, whereas adjusted analyses showed no association between body composition variables and the DI58 score. Recent alcohol use, muscle strength, and PA, but not lifetime alcohol use or gait speed, significantly moderated associations between body composition variables and frailty risk with medium-to-large effect sizes. Subgroup analyses revealed a negative relationship between DI58 and FFMI among people with PEth > 8 ng/ml and negative relationships of VACS Index with FFMI and WHR in people with lower muscle strength. Overweight or obese BMI categories were positively associated with DI58 in people with lower muscle strength or higher PA level but negatively associated in those with higher muscle strength.

CONCLUSIONS

Our findings indicate that body composition has significant modulatory effects on frailty risk in PLWH, where obesity increases the risk of frailty and greater muscle mass may be protective, even in individuals who use alcohol. These results highlight the importance of considering body composition, physical activity, and physical function in assessing frailty risk in PLWH, particularly among individuals who use alcohol. Moreover, they support the implementation of physical activity interventions to ameliorate the risk of frailty in aging PLWH.