Analysis reveals improved HIV-1 RNA data quality across cohorts, suggesting better research reliability.
Plasma HIV-1 RNA viral loads (VL) are measured via laboratory assays with changing lower limits of quantification over time. We described an approach to produce an analytic-ready dataset of VLs over time and across longitudinal cohorts of adults. A three-step approach was used: 1) initial data cleaning; 2) data checking with visualization; and 3) final data cleaning. Assumptions, data-driven decisions, and information from cohort-specific data managers produce an analytic-ready dataset of VLs with minimal missing data for date of blood draw, HIV-1 RNA result (copies/mL), below the lower limit of quantification (BLLQ) indicator, and the lower limit of quantification (LLQ). Among 3 663 786 VLs from 186 990 participants (median number of VLs per participant = 12, interquartile range 4-27) measured from 1988 to 2021, 61% of VL records were harmonized via the three-step approach. The proportion of VLs below the lower limit of quantification increased from 39% to 60% after application of this approach. Changes to LLQ, VL result, and BLLQ indicator variables were made to 45%, 36%, and 22% of VLs, respectively. Stated assumptions, visualized data distributions, and a documented approach to preparing an analytic-ready dataset of pooled individual-level longitudinal data revealed data idiosyncrasies, informed assumptions, and improved the data for research inference.
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Lee et al. (2026) studied this question.
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