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In several studies of antiretroviral treatment (ART) programs for persons with human immunodeficiency virus infection, investigators have reported that there has been a higher rate of loss to follow-up (LTFU) among patients initiating ART in recent years than among patients who initiated ART during earlier time periods. This finding is frequently interpreted as reflecting deterioration of patient retention in the face of increasing patient loads. However, in this paper we demonstrate by simulation that transient gaps in follow-up could lead to bias when standard survival analysis techniques are applied. We created a simulated cohort of patients with different dates of ART initiation. Rates of ART interruption, ART resumption, and mortality were assumed to remain constant over time, but when we applied a standard definition of LTFU, the simulated probability of being classified LTFU at a particular ART duration was substantially higher in recently enrolled cohorts. This suggests that much of the apparent trend towards increased LTFU may be attributed to bias caused by transient interruptions in care. Alternative statistical techniques need to be used when analyzing predictors of LTFU--for example, using "prospective" definitions of LTFU in place of "retrospective" definitions. Similar considerations may apply when analyzing predictors of LTFU from treatment programs for other chronic diseases., (© The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: Treatment as prevention depends on retaining HIV-infected patients in care. We investigated the effect on HIV transmission of bringing patients lost to follow-up (LTFU) back into care., Design: Mathematical model., Methods: Stochastic mathematical model of cohorts of 1000 HIV-infected patients on antiretroviral therapy, based on the data from 2 clinics in Lilongwe, Malawi. We calculated cohort viral load (sum of individual mean viral loads each year) and used a mathematical relationship between viral load and transmission probability to estimate the number of new HIV infections. We simulated 4 scenarios: "no LTFU" (all patients stay in care), "no tracing" (patients LTFU are not traced), "immediate tracing" (after missed clinic appointment), and "delayed tracing" (after 6 months)., Results: About 440 of 1000 patients were LTFU over 5 years. Cohort viral loads (million copies/mL per 1000 patients) were 3.7 [95% prediction interval (PrI), 2.9-4.9] for no LTFU, 8.6 (95% PrI, 7.3-10.0) for no tracing, 7.7 (95% PrI, 6.2-9.1) for immediate, and 8.0 (95% PrI, 6.7-9.5) for delayed tracing. Comparing no LTFU with no tracing, the number of new infections increased from 33 (95% PrI, 29-38) to 54 (95% PrI, 47-60) per 1000 patients. Immediate tracing prevented 3.6 (95% PrI, -3.3 to 12.8) and delayed tracing 2.5 (95% PrI, -5.8 to 11.1) new infections per 1000. Immediate tracing was more efficient than delayed tracing: to 116 and 142 tracing efforts, respectively, were needed prevent 1 new infection., Conclusions: Tracing of patients LTFU enhances the preventive effect of antiretroviral therapy, but the number of transmissions prevented is small.

Loss to follow-up (LTFU) is a common problem in many epidemiological studies. In antiretroviral treatment (ART) programs for patients with human immunodeficiency virus (HIV), mortality estimates can be biased if the LTFU mechanism is non-ignorable, that is, mortality differs between lost and retained patients. In this setting, routine procedures for handling missing data may lead to biased estimates. To appropriately deal with non-ignorable LTFU, explicit modeling of the missing data mechanism is needed. This can be based on additional outcome ascertainment for a sample of patients LTFU, for example, through linkage to national registries or through survey-based methods. In this paper, we demonstrate how this additional information can be used to construct estimators based on inverse probability weights (IPW) or multiple imputation. We use simulations to contrast the performance of the proposed estimators with methods widely used in HIV cohort research for dealing with missing data. The practical implications of our approach are illustrated using South African ART data, which are partially linkable to South African national vital registration data. Our results demonstrate that while IPWs and proper imputation procedures can be easily constructed from additional outcome ascertainment to obtain valid overall estimates, neglecting non-ignorable LTFU can result in substantial bias. We believe the proposed estimators are readily applicable to a growing number of studies where LTFU is appreciable, but additional outcome data are available through linkage or surveys of patients LTFU., (Copyright © 2013 John Wiley & Sons, Ltd.)

Objectives: To assess the proportion of patients lost to programme (died, lost to follow-up, transferred out) between HIV diagnosis and start of antiretroviral therapy (ART) in sub-Saharan Africa, and determine factors associated with loss to programme., Methods: Systematic review and meta-analysis. We searched PubMed and EMBASE databases for studies in adults. Outcomes were the percentage of patients dying before starting ART, the percentage lost to follow-up, the percentage with a CD4 cell count, the distribution of first CD4 counts and the percentage of eligible patients starting ART. Data were combined using random-effects meta-analysis., Results: Twenty-nine studies from sub-Saharan Africa including 148,912 patients were analysed. Six studies covered the whole period from HIV diagnosis to ART start. Meta-analysis of these studies showed that of the 100 patients with a positive HIV test, 72 (95% CI 60-84) had a CD4 cell count measured, 40 (95% CI 26-55) were eligible for ART and 25 (95% CI 13-37) started ART. There was substantial heterogeneity between studies (P < 0.0001). Median CD4 cell count at presentation ranged from 154 to 274 cells/μl. Patients eligible for ART were less likely to become lost to programme (25%vs. 54%, P < 0.0001), but eligible patients were more likely to die (11%vs. 5%, P < 0.0001) than ineligible patients. Loss to programme was higher in men, in patients with low CD4 cell counts and low socio-economic status and in recent time periods., Conclusions: Monitoring and care in the pre-ART time period need improvement, with greater emphasis on patients not yet eligible for ART., (© 2012 Blackwell Publishing Ltd.)

Objectives: To analyse mortality, loss to follow-up (LTFU) and retention on antiretroviral treatment (ART) in the first year of ART across all age groups in the Malawi national ART programme., Design: Cohort study including all patients who started ART in Malawi's public sector clinics between 2004 and 2007., Methods: ART registers were photographed, information entered into a database and merged with data from clinics with electronic records. Rates per 100 patient-years and cumulative incidence of retention were calculated. Subhazard ratios (sHRs) of outcomes adjusted for patient and clinic-level characteristics were calculated in multivariable analysis, applying competing risk models., Results: A total of 117,945 patients contributed 85,246 person-years: 1.0% were infants below 2 years, 7.4% children 2-14, 7.5% young people 15-24, and 84.2% adults 25 years and above. Sixty percent of patients were female: women outnumbered men from age 14 to 35 years. Mortality and LTFU were higher in men from age 20 years. Infants and young people had the highest rates per 100 person-years for mortality (23.0 and 19.4) and LTFU (24.7 and 19.3), and the highest adjusted relative risks compared to age group 25-34 years: sHRs were 1.37 [95% confidence interval (CI) 1.17-1.60] and 1.17 (95% CI 1.10-1.25) for death and 1.37 (95% CI 1.18-1.59) and 1.27 (95% CI 1.19-1.35) for LTFU, respectively., Conclusion: In this country-wide study patients aged 0-1 and 15-24 years had the highest risk of death and LTFU, and from age 20 men were at higher risk than women. Interventions to improve outcomes in these patient groups are required.