An empirical approach to defining loss to follow-up among patients enrolled in antiretroviral treatment programs

Am J Epidemiol. 2010 Apr 15;171(8):924-31. doi: 10.1093/aje/kwq008. Epub 2010 Mar 10.

Abstract

In many programs providing antiretroviral therapy (ART), clinicians report substantial patient attrition; however, there are no consensus criteria for defining patient loss to follow-up (LTFU). Data on a multisite human immunodeficiency virus (HIV) treatment cohort in Lusaka, Zambia, were used to determine an empirical "days-late" definition of LTFU among patients on ART. Cohort members were classified as either "in care" or LTFU as of December 31, 2007, according to a range of days-late intervals. The authors then looked forward in the database to determine which patients actually returned to care at any point over the following year. The interval that best minimized LTFU misclassification was described as "best-performing." Overall, 33,704 HIV-infected adults on ART were included. Nearly one-third (n = 10,196) were at least 1 day late for an appointment. The best-performing LTFU definition was 56 days after a missed visit, which had a sensitivity of 84.1% (95% confidence interval (CI): 83.2, 85.0), specificity of 97.5% (95% CI: 97.3, 97.7), and misclassification of 5.1% (95% CI: 4.8, 5.3). The 60-day threshold performed similarly well, with only a marginal difference (<0.1%) in misclassification. This analysis suggests that > or =60 days since the last appointment is a reasonable definition of LTFU. Standardization to empirically derived definitions of LTFU will permit more reliable comparisons within and across programs.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Anti-HIV Agents / therapeutic use*
  • Appointments and Schedules
  • Cohort Studies
  • Data Interpretation, Statistical*
  • Drug Monitoring / statistics & numerical data
  • HIV Infections / drug therapy*
  • HIV Infections / mortality
  • Humans
  • Medical Records Systems, Computerized
  • Medication Adherence / statistics & numerical data
  • Patient Dropouts* / classification
  • Patient Dropouts* / statistics & numerical data
  • ROC Curve
  • Sensitivity and Specificity
  • Time Factors
  • Zambia / epidemiology

Substances

  • Anti-HIV Agents