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Assessing linear CD4 decline quantifying diagnosis delay after HIV seroconversion: assessing the linearity assumption
McKaylee M Robertson1, Sarah L Braunstein2, Donald R Hoover3
1Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY), New York City; Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (CUNY), New York City.
Annals of Epidemiology
|August 14, 2020
Summary
Estimating diagnosis delay using early CD4 counts is reliable. The CD4 depletion model
Area of Science:
- Immunology
- Epidemiology
- Public Health
Background:
- Estimating time from HIV seroconversion to diagnosis is crucial for public health interventions.
- Previous models assumed a linear decrease in the square root of CD4 count before antiretroviral treatment (ART).
Purpose of the Study:
- To evaluate if CD4 counts from different time points in the pre-ART period yield similar estimates of diagnosis delay.
- To validate the CD4 depletion model's linearity assumption for population-level analysis.
Main Methods:
- Applied CD4 depletion model parameters from seroconverter cohorts to New York City residents diagnosed between 2006-2015.
- Analyzed individuals with at least two pre-ART CD4 counts.
Main Results:
- Median diagnosis delays were similar whether estimated from the first or second pre-ART CD4 count (2.8 years).
- No significant difference in diagnosis delay was observed when comparing first and second pre-ART CD4 counts, even when the second count was >6 months post-diagnosis.
Conclusions:
- Findings support the linearity assumption of the CD4 depletion model.
- Pre-ART CD4 counts obtained more than 6 months post-diagnosis can be reliably used for estimating population-level diagnosis delay.
