Natalia L Oliveira1,2, Edward H Kennedy1, Ryan Tibshirani1,2, Andrew Levine3, Eileen Martin4, Cynthia Munro5, Ann B Ragin6, Leah H Rubin5,7, Ned Sacktor7, Eric C Seaberg8, Andrea Weinstein9, James T Becker9,7,10. 1. Department of Statistics and Data Science. 2. Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania. 3. Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, California. 4. Department of Psychiatry, Rush University School of Medicine, Chicago, Illinois. 5. Department of Psychiatry, The Johns Hopkins University School of Medicine, Baltimore, Maryland. 6. Department of Radiology, Northwestern University, Evanston, Illinois. 7. Department of Neurology. 8. Department of Epidemiology, Bloomberg School of Public Health, The Johns Hopkins University, Baltimore, Maryland. 9. Department of Psychiatry. 10. Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Abstract
BACKGROUND: Although combination antiretroviral therapy reduced the prevalence of HIV-associated dementia, milder syndromes persist. Our goals were to predict cognitive impairment of the Multicenter AIDS Cohort Study (MACS) participants 5 years ahead and from a large pool of factors, select the ones that mostly contributed to our predictions. DESIGN: Longitudinal, natural and treated history of HIV infection among MSM. METHODS: The MACS is a longitudinal study of the natural and treated history of HIV disease in MSM; the neuropsychological substudy aims to characterize cognitive disorders in men with HIV disease. RESULTS: We modeled on an annual basis the risk of cognitive impairment 5 years in the future. We were able to predict cognitive impairment at individual level with high precision and overperform default methods. We found that while a diagnosis of AIDS is a critical risk factor, HIV infection per se does not necessarily convey additional risk. Other infectious processes, most notably hepatitis B and C, are independently associated with increased risk of impairment. The relative importance of an AIDS diagnosis diminished across calendar time. CONCLUSION: Our prediction models are a powerful tool to help clinicians address dementia in early stages for MACS paticipants. The strongest predictors of future cognitive impairment included the presence of clinical AIDS and hepatitis B or C infection. The fact that the pattern of predictive power differs by calendar year suggests a clinically critical change to the face of the epidemic.
BACKGROUND: Although combination antiretroviral therapy reduced the prevalence of HIV-associated dementia, milder syndromes persist. Our goals were to predict cognitive impairment of the Multicenter AIDS Cohort Study (MACS) participants 5 years ahead and from a large pool of factors, select the ones that mostly contributed to our predictions. DESIGN: Longitudinal, natural and treated history of HIV infection among MSM. METHODS: The MACS is a longitudinal study of the natural and treated history of HIV disease in MSM; the neuropsychological substudy aims to characterize cognitive disorders in men with HIV disease. RESULTS: We modeled on an annual basis the risk of cognitive impairment 5 years in the future. We were able to predict cognitive impairment at individual level with high precision and overperform default methods. We found that while a diagnosis of AIDS is a critical risk factor, HIV infection per se does not necessarily convey additional risk. Other infectious processes, most notably hepatitis B and C, are independently associated with increased risk of impairment. The relative importance of an AIDS diagnosis diminished across calendar time. CONCLUSION: Our prediction models are a powerful tool to help clinicians address dementia in early stages for MACS paticipants. The strongest predictors of future cognitive impairment included the presence of clinical AIDS and hepatitis B or C infection. The fact that the pattern of predictive power differs by calendar year suggests a clinically critical change to the face of the epidemic.
Authors: N Sacktor; R H Lyles; R Skolasky; C Kleeberger; O A Selnes; E N Miller; J T Becker; B Cohen; J C McArthur Journal: Neurology Date: 2001-01-23 Impact factor: 9.910
Authors: Zheng Wang; Samantha A Molsberry; Yu Cheng; Lawrence Kingsley; Andrew J Levine; Eileen Martin; Cynthia A Munro; Ann Ragin; Leah H Rubin; Ned Sacktor; Eric C Seaberg; James T Becker Journal: AIDS Date: 2019-11-15 Impact factor: 4.177
Authors: James T Becker; Lawrence A Kingsley; Samantha Molsberry; Sandra Reynolds; Aaron Aronow; Andrew J Levine; Eileen Martin; Eric N Miller; Cynthia A Munro; Ann Ragin; Ned Sacktor; Ola A Selnes Journal: Int J Epidemiol Date: 2014-04-24 Impact factor: 7.196