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Validation of a Hierarchical Deterministic Record-Linkage Algorithm Using Data From 2 Different Cohorts of Human Immunodeficiency Virus-Infected Persons and Mortality Databases in Brazil

By Antonio G. Pacheco, Valeria Saraceni, Suely H. Tuboi, Lawrence H. Moulton, Richard E. Chaisson, Solange C. Cavalcante, Betina Durovni, José C. Faulhaber, Jonathan E. Golub, Bonnie King, Mauro Schechter and Lee H. Harrison

Abstract

Loss to follow-up is a major source of bias in cohorts of patients with human immunodeficiency virus (HIV) and could lead to underestimation of mortality. The authors developed a hierarchical deterministic linkage algorithm to be used primarily with cohorts of HIV-infected persons to recover vital status information for patients lost to follow-up. Data from patients known to be deceased in 2 cohorts in Rio de Janeiro, Brazil, and data from the Rio de Janeiro State mortality database for 1999–2006 were used to validate the algorithm. A fully automated procedure yielded a sensitivity of 92.9% and specificity of 100% when no information was missing. When the automated procedure was combined with clerical review, in a scenario of 5% death prevalence and 20% missing mothers’ names, sensitivity reached 96.5% and specificity 100%. In a practical application, the algorithm significantly increased death rates and decreased the rate of loss to follow-up in the cohorts. The finding that 23.9% of matched records did not give HIV or acquired immunodeficiency syndrome as the cause of death reinforces the need to search all-cause mortality databases and alerts for possible underestimation of death rates. These results indicate that the algorithm is accurate enough to recover vital status information on patients lost to follow-up in cohort studies

Topics: Practice of Epidemiology
Publisher: Oxford University Press
OAI identifier: oai:pubmedcentral.nih.gov:2638543
Provided by: PubMed Central

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