Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health Administration
IntroductionAs 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...
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Frontiers Media S.A.
2024-01-01
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| author | Kathleen A. McGinnis Amy C. Justice Amy C. Justice Vincent C. Marconi Vincent C. Marconi Maria C. Rodriguez-Barradas Maria C. Rodriguez-Barradas Ronald G. Hauser Ronald G. Hauser Krisann K. Oursler Krisann K. Oursler Sheldon T. Brown Kendall J. Bryant Janet P. Tate Janet P. Tate for the Veterans Aging Cohort Study |
| author_facet | Kathleen A. McGinnis Amy C. Justice Amy C. Justice Vincent C. Marconi Vincent C. Marconi Maria C. Rodriguez-Barradas Maria C. Rodriguez-Barradas Ronald G. Hauser Ronald G. Hauser Krisann K. Oursler Krisann K. Oursler Sheldon T. Brown Kendall J. Bryant Janet P. Tate Janet P. Tate for the Veterans Aging Cohort Study |
| author_sort | Kathleen A. McGinnis |
| collection | DOAJ |
| description | IntroductionAs 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.MethodsTo 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 </≥65 years, race/ethnicity, and CCI score). We then applied VACS-CCI in PWH and compared its accuracy to age, VACS Index 2.0, CCI and VACS-CCI with CD4 and HIV RNA added.ResultsThe 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).DiscussionAmong 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. |
| format | Article |
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| institution | Kabale University |
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| language | English |
| publishDate | 2024-01-01 |
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| series | Frontiers in Medicine |
| spelling | doaj-art-17888072cf5445f1b1049cf560d471832025-01-07T16:21:09ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2024-01-011010.3389/fmed.2023.13424661342466Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health AdministrationKathleen A. McGinnis0Amy C. Justice1Amy C. Justice2Vincent C. Marconi3Vincent C. Marconi4Maria C. Rodriguez-Barradas5Maria C. Rodriguez-Barradas6Ronald G. Hauser7Ronald G. Hauser8Krisann K. Oursler9Krisann K. Oursler10Sheldon T. Brown11Kendall J. Bryant12Janet P. Tate13Janet P. Tate14for the Veterans Aging Cohort StudyVA Connecticut Healthcare System, West Haven, CT, United StatesVA Connecticut Healthcare System, West Haven, CT, United StatesYale School of Medicine, New Haven, CT, United StatesThe Atlanta Veterans Affairs Medical Center, Emory University School of Medicine and Rollins School of Public Health, Atlanta, GA, United StatesVA Medical Center, Decatur, GA, United StatesInfectious Diseases Section, Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, United StatesDepartment of Medicine, Baylor College of Medicine, Houston, TX, United StatesVA Connecticut Healthcare System, West Haven, CT, United StatesDepartment of Laboratory Medicine, Yale University School of Medicine, New Haven, CT, United StatesDepartment of Internal Medicine, Virginia Tech Carilion School of Medicine, Roanoke, VA, United StatesVA Salem Healthcare System, Salem, VA, United States0James J. Peters VA Medical Center, Bronx, NY, United States1National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, United StatesVA Connecticut Healthcare System, West Haven, CT, United StatesYale School of Medicine, New Haven, CT, United StatesIntroductionAs 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.MethodsTo 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 </≥65 years, race/ethnicity, and CCI score). We then applied VACS-CCI in PWH and compared its accuracy to age, VACS Index 2.0, CCI and VACS-CCI with CD4 and HIV RNA added.ResultsThe 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).DiscussionAmong 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.https://www.frontiersin.org/articles/10.3389/fmed.2023.1342466/fullVACS IndexCharlson Comorbidity IndexHIVmortalityprediction |
| spellingShingle | Kathleen A. McGinnis Amy C. Justice Amy C. Justice Vincent C. Marconi Vincent C. Marconi Maria C. Rodriguez-Barradas Maria C. Rodriguez-Barradas Ronald G. Hauser Ronald G. Hauser Krisann K. Oursler Krisann K. Oursler Sheldon T. Brown Kendall J. Bryant Janet P. Tate Janet P. Tate for the Veterans Aging Cohort Study Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health Administration Frontiers in Medicine VACS Index Charlson Comorbidity Index HIV mortality prediction |
| title | Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health Administration |
| title_full | Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health Administration |
| title_fullStr | Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health Administration |
| title_full_unstemmed | Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health Administration |
| title_short | Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health Administration |
| title_sort | combining charlson comorbidity and vacs indices improves prognostic accuracy for all cause mortality for patients with and without hiv in the veterans health administration |
| topic | VACS Index Charlson Comorbidity Index HIV mortality prediction |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2023.1342466/full |
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