Laboratory Measures as Proxies for Primary Care Encounters: Implications for Quantifying Clinical Retention Among HIV-Infected Adults in North America

Abstract

Because of limitations in the availability of data on primary care encounters, patient retention in human immunodeficiency virus (HIV) care is often estimated using laboratory measurement dates as proxies for clinical encounters, leading to possible outcome misclassification. This study included 83,041 HIV-infected adults from 14 clinical cohorts in the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) who had ≥1 HIV primary care encounters during 2000-2010, contributing 468,816 person-years of follow-up. Encounter-based retention (REB) was defined as ≥2 encounters in a calendar year, ≥90 days apart. Laboratory-based retention (RLB) was defined similarly, using the dates of CD4-positive cell counts or HIV-1 RNA measurements. Percentage of agreement and the κ statistic were used to characterize agreement between RLB and REB. Logistic regression with generalized estimating equations and stabilized inverse-probability-of-selection weights was used to elucidate temporal trends and the discriminatory power of RLB as a predictor of REB, accounting for age, sex, race/ethnicity, primary HIV risk factor, and cohort site as potential confounders. Both REB and RLB increased from 2000 to 2010 (from 67% to 78% and from 65% to 77%, respectively), though REB was higher than RLB throughout (P < 0.01). RLB agreed well with REB (80%-86% agreement; κ = 0.55-0.62, P < 0.01) and had a strong, imperfect ability to discriminate between persons retained and not retained in care by REB (C statistic: C = 0.81, P < 0.05). As a proxy for REB, RLB had a sensitivity and specificity of 84% and 77%, respectively, with misclassification error of 18%.

Keywords: HIV; clinical encounters; clinical retention; laboratory measurements; measurement error; misclassification; proxies.

Figure 1.

Temporal trends in encounter- and laboratory-based measures of retention in care (R_EB and R_LB, respectively) and agreement between measures (% agreement and κ coefficient) in the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD), 2000–2010. Dashed-and-dotted lines across R_EB and R_LB percentages are locally weight scatterplot smoothing (LOESS) curves for trend. κ estimates (diamonds) are plotted with 95% confidence intervals (bars).

Figure 2.

Receiver operating characteristic (ROC) curves quantifying the discrimination of an encounter-based measure of retention of human immunodeficiency virus (HIV)-positive patients in care (R_EB) by a laboratory-based measure of retention in care (R_LB), North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD), 2000–2010. The curves were derived from regression models with generalized estimating equations and inverse-probability-of-selection weights (IPW). A) ROC curve with IPW based on site, age, sex, race/ethnicity, and primary HIV risk factor. B) ROC curve derived from a model with robust adjustment for clinic site with IPW. Predicted probabilities of retention by R_EB are thresholds on the ROC curves.

Figure 3.

Ratios of odds ratios (RORs) and 95% confidence intervals (CIs) for the probability of retaining human immunodeficiency virus (HIV)-positive patients in care as assessed by an encounter-based measure (R_EB), conditional on retention assessed by a laboratory-based measure (R_LB), among subpopulations of concern (joint-effects interactions), North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD), 2000–2010. Reference groups: for age, ≤50 years; for sex, male; for black race, nonblack race; for injection drug use (IDU) as the primary HIV risk factor, a non-IDU primary HIV risk factor. GEE, generalized estimating equations.