Nicole L De La Mata ; Mi-Young Ahn ; Nagalingeswaran Kumarasamy ; Penh Sun Ly ; Oon Tek Ng ; Kinh Van Nguyen ; Tuti Parwati Merati ; Thuy Thanh Pham ; Man Po Lee ; Nicolas Durier ; Matthew G Law
Citation
JOURNAL OF CLINICAL EPIDEMIOLOGY, Vol.81 : 129-139, 2017-01
Adult ; Anti-HIV Agents / therapeutic use* ; Asia ; CD4 Lymphocyte Count / statistics & numerical data ; Cohort Studies ; Databases, Factual / statistics & numerical data ; Demography / statistics & numerical data ; Epidemiologic Research Design* ; Female ; HIV Infections / drug therapy* ; HIV Infections / epidemiology* ; Humans ; Male ; Middle Aged ; Observational Studies as Topic / statistics & numerical data ; Population Surveillance / methods* ; Risk Factors ; Survival Analysis ; Viral Load / statistics & numerical data
Keywords
Asia ; Cohort ; HIV ; Observational data ; Patient sampling ; Selection bias
Abstract
Objectives: To compare two human immunodeficiency virus (HIV) cohorts to determine whether a pseudo-random sample can represent the entire study population.
Study design and setting: HIV-positive patients receiving care at eight sites in seven Asian countries. The TREAT Asia HIV Observational database (TAHOD) pseudo-randomly selected a patient sample, while TREAT Asia HIV Observational database-Low Intensity Transfer (TAHOD-LITE) included all patients. We compared patient demographics, CD4 count, and HIV viral load testing for each cohort. Risk factors associated with CD4 count response, HIV viral load suppression (<400 copies/mL), and survival were determined for each cohort.
Results: There were 2,318 TAHOD patients and 14,714 TAHOD-LITE patients. Patient demographics, CD4 count, and HIV viral load testing rates were broadly similar between the cohorts. CD4 count response and all-cause mortality were consistent among the cohorts with similar risk factors. HIV viral load response appeared to be superior in TAHOD and many risk factors differed, possibly due to viral load being tested on a subset of patients.
Conclusion: Our study gives the first empirical evidence that analysis of risk factors for completely ascertained end points from our pseudo-randomly selected patient sample may be generalized to our larger, complete population of HIV-positive patients. However, results can significantly vary when analyzing smaller or pseudo-random samples, particularly if some patient data are not completely missing at random, such as viral load results.