Importance

Human immunodeficiency virus (HIV)-positive patients treated with antiretroviral therapy now have increased life expectancy and develop chronic illnesses that are often seen in older HIV-negative patients.

Objective

To address emerging issues related to aging with HIV. Screening older adults for HIV, diagnosis of concomitant diseases, management of multiple comorbid medical illnesses, social isolation, polypharmacy, and factors associated with end-of-life care are reviewed.

Evidence acquisition

Published guidelines and consensus statements were reviewed. PubMed and PsycINFO were searched between January 2000 and February 2013. Articles not appearing in the search that were referenced by reviewed articles were also evaluated.

Findings

The population of older HIV-positive patients is rapidly expanding. It is estimated that by 2015 one-half of the individuals in the United States with HIV will be older than age 50. Older HIV-infected patients are prone to having similar chronic diseases as their HIV-negative counterparts, as well as illnesses associated with co-infections. Medical treatments associated with these conditions, when added to an antiretroviral regimen, increase risk for polypharmacy. Care of aging HIV-infected patients involves a need to balance a number of concurrent comorbid medical conditions.

Conclusions and relevance

HIV is no longer a fatal disease. Management of multiple comorbid diseases is a common feature associated with longer life expectancy in HIV-positive patients. There is a need to better understand how to optimize the care of these patients.

Objective

Despite viral suppression and immune response on antiretroviral therapy, people with HIV infection experience excess mortality compared with uninfected individuals. The Veterans Aging Cohort Study (VACS) Index incorporates clinical biomarkers of general health with age, CD4 cell count, and HIV-1 RNA to discriminate mortality risk in a variety of HIV-positive populations. We asked whether additional biomarkers further enhance discrimination.

Design and methods

Using patients from VACS for development and from the Antiretroviral Therapy Cohort Collaboration (ART-CC) for validation, we obtained laboratory values from a randomly selected visit from 2000 to 2014, at least 1 year after antiretroviral therapy initiation. Patients were followed for 5-year, all-cause mortality through September 2016. We fitted Cox models with established predictors and added new predictors based on model fit and Harrell's c-statistic. We converted all variables to continuous functional forms and selected the best model (VACS Index 2.0) for validation in ART-CC patients. We compared discrimination using c-statistics and Kaplan-Meier plots.

Results

Among 28 390 VACS patients and 12 109 ART-CC patients, 7293 and 722 died, respectively. Nadir CD4, CD8, and CD4 : CD8 ratio did not improve discrimination. Addition of albumin, white blood count, and BMI, improved c-statistics in VACS from 0.776 to 0.805 and in ART-CC from 0.800 to 0.831. Results were robust in all nine ART-CC cohorts, all lengths of follow-up and all subgroups.

Conclusion

VACS Index 2.0, adding albumin, white blood count, and BMI to version 1.0 and using continuous variables, provides improved discrimination and is highly transportable to external settings.

Noncommunicable diseases (NCDs) account for a growing burden of morbidity and mortality among people living with HIV in low- and middle-income countries (LMICs). HIV infection and antiretroviral therapy interact with NCD risk factors in complex ways, and research into this "web of causation" has so far been largely based on data from high-income countries. However, improving the understanding, treatment, and prevention of NCDs in LMICs requires region-specific evidence. Priority research areas include: (1) defining the burden of NCDs among people living with HIV, (2) understanding the impact of modifiable risk factors, (3) evaluating effective and efficient care strategies at individual and health systems levels, and (4) evaluating cost-effective prevention strategies. Meeting these needs will require observational data, both to inform the design of randomized trials and to replace trials that would be unethical or infeasible. Focusing on Sub-Saharan Africa, we discuss data resources currently available to inform this effort and consider key limitations and methodological challenges. Existing data resources often lack population-based samples; HIV-negative, HIV-positive, and antiretroviral therapy-naive comparison groups; and measurements of key NCD risk factors and outcomes. Other challenges include loss to follow-up, competing risk of death, incomplete outcome ascertainment and measurement of factors affecting clinical decision making, and the need to control for (time-dependent) confounding. We review these challenges and discuss strategies for overcoming them through augmented data collection and appropriate analysis. We conclude with recommendations to improve the quality of data and analyses available to inform the response to HIV and NCD comorbidity in LMICs.

Despite achieving human immunodeficiency virus type 1 (HIV-1) RNA suppression below levels of detection and, for most, improved CD4+ T-cell counts, those aging with HIV experience excess low-level inflammation, hypercoagulability, and immune dysfunction (chronic inflammation), compared with demographically and behaviorally similar uninfected individuals. A host of biomarkers that are linked to chronic inflammation are also associated with HIV-associated non-AIDS-defining events, including cardiovascular disease, many forms of cancer, liver disease, renal disease, neurocognitive decline, and osteoporosis. Furthermore, chronic HIV infection may interact with long-term treatment toxicity and weight gain after ART initiation. These observations suggest that future biomarker-guided discovery and treatment may require attention to multiple biomarkers and, possibly, weighted indices. We are clinical trialists, epidemiologists, pragmatic trialists, and translational scientists. Together, we offer an operational definition of a biomarker and consider how biomarkers might facilitate progress along the translational pathway from therapeutic discovery to intervention trials and clinical management among people aging with or without HIV infection.

Background & aims

Universal one-time antibody testing for hepatitis C virus (HCV) infection has been recommended by the centers for disease control (CDC) and the United States preventative services task force (USPSTF) for Americans born 1945-1965 (birth cohort). Limited data exists addressing national HCV testing practices. We studied patterns and predictors of HCV testing across the U.S. within the birth cohort utilizing data from the national corporate data warehouse of the U.S. Veterans Administration (VA) health system.

Methods

Testing was defined as any HCV test including antibody, RNA or genotype performed during 2000-2013.

Results

Of 6,669,388 birth cohort veterans, 4,221,135 (63%) received care within the VA from 2000-2013 with two or more visits. Of this group, 2,139,935 (51%) had HCV testing with 8.1% HCV antibody and 5.4% RNA positive. Significant variation in testing was observed across centers (range: 7-83%). Older, male, African-Americans, with established risk factors and receiving care from urban centers of excellence were more likely to be tested. Among veterans free of other established risk factors (HIV negative, HBV negative, ALT ⩽40U/L, FIB-4 ⩽1.45, or APRI <0.5), HCV antibody and RNA were positive in 2.8% and 0.9%, respectively, comparable to established national average. At least 2.4-4.4% of veterans had scores suggesting advanced fibrosis (APRI ⩾1.5 or FIB-4 >3.25) with >30-43% having positive HCV RNA but >16-20% yet to undergo testing for HCV.

Conclusions

Significant disparities are observed in HCV testing within the United States VA health system. Examination of the predictors of testing and HCV positivity may help inform national screening policies.

Lay summary

Analysis of United States Veterans Administration data show significant disparities in hepatitis C virus testing of veterans born 1945-1965 (birth cohort). A fifth of those not tested had evidence of advanced liver fibrosis. Our data suggests some predictors for this disparity and will potentially help inform future policy measures in the era of universal birth cohort testing for HCV.

Objectives

To compare levels of social isolation in aging veterans with and without the human immunodeficiency virus (HIV) and determine associations with hospital admission and mortality.

Design

Longitudinal data analysis.

Setting

The Veterans Aging Cohort Study (VACS), at eight VA Medical Centers nationally.

Participants

Veterans aged 55 and older enrolled in VACS from 2002 to 2008 (N = 1,836).

Measurements

A Social Isolation Score (SIS) was created using baseline survey responses about relationship status; number of friends and family and frequency of visits; and involvement in volunteer work, religious or self-help groups, and other community activities. Scores were compared according to age and HIV status, and multivariable regression was used to assess effects of SIS on hospital admission and all-cause mortality.

Results

Mean SIS was higher for HIV-positive (HIV+) individuals, with increasing difference according to age (P = .01 for trend). Social isolation was also more prevalent for HIV+ (59%) than uninfected participants (51%, P < .001). In multivariable regression analysis of HIV+ and uninfected groups combined, adjusted for demographic and clinical features, isolation was independently associated with greater risk of incident hospitalization (hazard rate (HR) = 1.25, 95% confidence interval (CI) = 1.09-1.42) and risk of all-cause mortality (HR=1.28, 95% CI = 1.06-1.54). Risk estimates calculated for HIV+ and uninfected groups separately were not significantly different.

Conclusion

Social isolation is associated with greater risk of hospitalization and death in HIV+ and uninfected older veterans. Despite similar effects in both groups, the population-level effect of social isolation may be greater in those who are HIV+ because of the higher prevalence of social isolation, particularly in the oldest individuals.

Background

Genome-wide Association Studies (GWAS) aims to uncover the link between genomic variation and phenotype. They have been actively applied in cancer biology to investigate associations between variations and cancer phenotypes, such as susceptibility to certain types of cancer and predisposed responsiveness to specific treatments. Since GWAS primarily focuses on finding associations between individual genomic variations and cancer phenotypes, there are limitations in understanding the mechanisms by which cancer phenotypes are cooperatively affected by more than one genomic variation.

Results

This paper proposes a network representation learning approach to learn associations among genomic variations using a prostate cancer cohort. The learned associations are encoded into representations that can be used to identify functional modules of genomic variations within genes associated with early- and late-onset prostate cancer. The proposed method was applied to a prostate cancer cohort provided by the Veterans Administration's Million Veteran Program to identify candidates for functional modules associated with early-onset prostate cancer. The cohort included 33,159 prostate cancer patients, 3181 early-onset patients, and 29,978 late-onset patients. The reproducibility of the proposed approach clearly showed that the proposed approach can improve the model performance in terms of robustness.

Conclusions

To our knowledge, this is the first attempt to use a network representation learning approach to learn associations among genomic variations within genes. Associations learned in this way can lead to an understanding of the underlying mechanisms of how genomic variations cooperatively affect each cancer phenotype. This method can reveal unknown knowledge in the field of cancer biology and can be utilized to design more advanced cancer-targeted therapies.

Introduction

Despite major progress in controlling HIV disease through antiretroviral therapy, changes in immune phenotype and function persist in individuals with chronic HIV, raising questions about accelerated aging of the immune system.

Methods

We conducted a cross-sectional study (2005-2007) of HIV-infected (n = 111) and uninfected (n = 114) men from the Veterans Aging Cohort Study. All HIV-infected subjects were on antiretroviral therapy with VL <400 copies/mL for at least 3 years. T-cell markers were examined using flow cytometry. We evaluated the impact of HIV serostatus and age on T-cell phenotypes (expressed as percentages of the total CD4 and CD8 T-cell population) using multivariate linear regression, adjusted for smoking, alcohol, and race/ethnicity. We tested for interactions between HIV and age by including interaction terms.

Results

Among both HIV-infected and uninfected subjects, increasing age was associated with a decreased proportion of naive CD4 T cells (P = 0.014) and CD8 T cells (P < 0.0001). Both HIV infection and increasing age were associated with higher proportions of effector memory CD4 T cells (P < 0.0001 for HIV; P = 0.04 for age) and CD8 T cells (P = 0.0001 for HIV; P = 0.0004 for age). HIV infection, but not age, was associated with a higher proportion of activated CD8 T cells (P < 0.0001). For all T-cell subsets tested, there were no significant interactions between HIV infection and age.

Conclusions

Age and HIV status independently altered the immune system, but we found no conclusive evidence that HIV infection and advancing age synergistically result in accelerated changes in age-associated T-cell markers among virally suppressed individuals.

Objectives

In 2016, the Department of Veterans Affairs (VA) and the Department of Energy (DOE) established an Interagency Agreement (IAA), the Million Veteran Program-Computational Health Analytics for Medical Precision to Improve Outcomes Now (MVP-CHAMPION) research collaboration.

Materials and methods

Oversight fell under the VA Office of Research Development (VA ORD) and DOE headquarters. An Executive Committee and 2 senior scientific liaisons work with VA and DOE leadership to optimize efforts in the service of shared scientific goals. The program supported centralized data management and genomic analysis including creation of a scalable approach to cataloging phenotypes. Cross-cutting methods including natural language processing, image processing, and reusable code were developed.

Results

The 79.6 million dollar collaboration has supported centralized data management and genomic analysis including a scalable approach to cataloging phenotypes and launched over 10 collaborative scientific projects in health conditions highly prevalent in veterans. A ground-breaking analysis on the Summit and Andes supercomputers at the Oak Ridge National Laboratory (ORNL) of the genetic underpinnings of over 2000 health conditions across 44 million genetic variants which resulted in the identification of 38 270 independent genetic variants associating with one or more health traits. Of these, over 2000 identified associations were unique to non-European ancestry. Cross-cutting methods have advanced state-of-the-art artificial intelligence (AI) including large language natural language processing and a system biology study focused on opioid addiction awarded the 2018 Gordon Bell Prize for outstanding achievement in high-performance computing. The collaboration has completed work in prostate cancer, suicide prevention, and cardiovascular disease, and cross-cutting data science. Predictive models developed in these projects are being tested for application in clinical management.

Discussion

Eight new projects were launched in 2023, taking advantage of the momentum generated by the previous collaboration. A major challenge has been limitations in the scope of appropriated funds at DOE which cannot currently be used for health research.

Conclusion

Extensive multidisciplinary interactions take time to establish and are essential to continued progress. New funding models for maintaining high-performance computing infrastructure at the ORNL and for supporting continued collaboration by joint VA-DOE research teams are needed.

Background

Given the growing interest in the cancer burden in persons living with HIV/AIDS, we examined the validity of data sources for cancer diagnoses (cancer registry versus International Classification of Diseases, Ninth Revision [ICD-9 codes]) and compared the association between HIV status and cancer risk using each data source in the Veterans Aging Cohort Study (VACS), a prospective cohort of HIV-infected and uninfected veterans from 1996 to 2008.

Methods

We reviewed charts to confirm potential incident cancers at four VACS sites. In the entire cohort, we calculated cancer-type-specific age-, sex-, race/ethnicity-, and calendar-period-standardized incidence rates and incidence rate ratios (IRR) (HIV-infected versus uninfected). We calculated standardized incidence ratios (SIR) to compare VACS and Surveillance, Epidemiology, and End Results rates.

Results

Compared to chart review, both Veterans Affairs Central Cancer Registry (VACCR) and ICD-9 diagnoses had approximately 90% sensitivity; however, VACCR had higher positive predictive value (96% versus 63%). There were 6,010 VACCR and 13,386 ICD-9 incident cancers among 116,072 veterans. Although ICD-9 rates tended to be double VACCR rates, most IRRs were in the same direction and of similar magnitude, regardless of data source. Using either source, all cancers combined, most viral-infection-related cancers, lung cancer, melanoma, and leukemia had significantly elevated IRRs. Using ICD-9, eight additional IRRs were significantly elevated, most likely due to false positive diagnoses. Most ICD-9 SIRs were significantly elevated and all were higher than the corresponding VACCR SIR.

Conclusions

ICD-9 may be used with caution for estimating IRRs, but should be avoided when estimating incidence or SIRs. Elevated cancer risk based on VACCR diagnoses among HIV-infected veterans was consistent with other studies.