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Laboratory Measures as Proxies for Primary Care Encounters: Implications for Quantifying Clinical Retention Among HIV-Infected Adults in North America22h
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由 Rebeiro, P. F., Althoff, K. N., Lau, B., Gill, J., Abraham, A. G., Horberg, M. A., Kitahata, M. M., Yehia, B. R., Samji, H., Brooks, J. T., Buchacz, K., Napravnik, S., Silverberg, M. J., Rachlis, A., Gebo, K. A., Sterling, T. R., Moore, R. D., Gange, S. J., for the North American AIDS Cohort Collaboration on Research and Design, for the North American AIDS Cohort Collaboration on Research and Design, Rebeiro, Sterling, Althoff, Lau, Abraham, Gebo, Moore, Gange, Gill, Horberg, Kitahata, Yehia, Samji, Brooks, Buchacz, Napravnik, Silverberg, Rachlis[url=][/url] 通过 American Journal of Epidemiology - current issue[url=][/url]
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 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 RLBthroughout (P < 0.01). RLB agreed well with REB (80%–86% agreement; = 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 (Cstatistic: 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%.
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