Analyzing Longitudinally Collected Viral Load Measurements in Youth With Perinatally Acquired HIV Infection : Problems and Possible Remedies
© Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2022. This work is written by (a) US Government employee(s) and is in the public domain in the US..
Human immunodeficiency virus (HIV) viral load (VL) is an important quantitative marker of disease progression and treatment response in people living with HIV infection, including children with perinatally acquired HIV. Measures of VL are often used to predict different outcomes of interest in this population, such as HIV-associated neurocognitive disorder. One popular approach to summarizing historical viral burden is the area under a time-VL curve (AUC). However, alternative historical VL summaries (HVS) may better answer the research question of interest. In this article, we discuss and contrast the AUC with alternative HVS, including the time-averaged AUC, duration of viremia, percentage of time with suppressed VL, peak VL, and age at peak VL. Using data on youth with perinatally acquired HIV infection from the Pediatric HIV/AIDS Cohort Study Adolescent Master Protocol, we show that HVS and their associations with full-scale intelligence quotient depend on when the VLs were measured. When VL measurements are incomplete, as can be the case in observational studies, analysis results may be subject to selection bias. To alleviate bias, we detail an imputation strategy, and we present a simulation study demonstrating that unbiased estimation of a historical VL summary is possible with a correctly specified imputation model.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:191 |
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| Enthalten in: |
American journal of epidemiology - 191(2022), 10 vom: 28. Sept., Seite 1820-1830 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Brummel, Sean S [VerfasserIn] |
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| Links: |
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| Themen: |
Bias |
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| Anmerkungen: |
Date Completed 07.10.2022 Date Revised 10.05.2024 published: Print Citation Status MEDLINE |
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| doi: |
10.1093/aje/kwac125 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a © Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2022. This work is written by (a) US Government employee(s) and is in the public domain in the US. | ||
| 520 | |a Human immunodeficiency virus (HIV) viral load (VL) is an important quantitative marker of disease progression and treatment response in people living with HIV infection, including children with perinatally acquired HIV. Measures of VL are often used to predict different outcomes of interest in this population, such as HIV-associated neurocognitive disorder. One popular approach to summarizing historical viral burden is the area under a time-VL curve (AUC). However, alternative historical VL summaries (HVS) may better answer the research question of interest. In this article, we discuss and contrast the AUC with alternative HVS, including the time-averaged AUC, duration of viremia, percentage of time with suppressed VL, peak VL, and age at peak VL. Using data on youth with perinatally acquired HIV infection from the Pediatric HIV/AIDS Cohort Study Adolescent Master Protocol, we show that HVS and their associations with full-scale intelligence quotient depend on when the VLs were measured. When VL measurements are incomplete, as can be the case in observational studies, analysis results may be subject to selection bias. To alleviate bias, we detail an imputation strategy, and we present a simulation study demonstrating that unbiased estimation of a historical VL summary is possible with a correctly specified imputation model | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
| 650 | 4 | |a HIV | |
| 650 | 4 | |a bias | |
| 650 | 4 | |a imputation | |
| 650 | 4 | |a missing data | |
| 650 | 4 | |a viral load | |
| 650 | 4 | |a viremia copy-years | |
| 650 | 4 | |a youth | |
| 700 | 1 | |a Van Dyke, Russell B |e verfasserin |4 aut | |
| 700 | 1 | |a Patel, Kunjal |e verfasserin |4 aut | |
| 700 | 1 | |a Purswani, Murli |e verfasserin |4 aut | |
| 700 | 1 | |a Seage, George R |e verfasserin |4 aut | |
| 700 | 1 | |a Yao, Tzy-Jyun |e verfasserin |4 aut | |
| 700 | 1 | |a Hazra, Rohan |e verfasserin |4 aut | |
| 700 | 1 | |a Karalius, Brad |e verfasserin |4 aut | |
| 700 | 1 | |a Williams, Paige L |e verfasserin |4 aut | |
| 700 | 0 | |a Pediatric HIV/AIDS Cohort Study |e verfasserin |4 aut | |
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