Monitoring of antiretroviral therapy and mortality in HIV programmes in Malawi, South Africa and Zambia: mathematical modelling study

OBJECTIVES Mortality in patients starting antiretroviral therapy (ART) is higher in Malawi and Zambia than in South Africa. We examined whether different monitoring of ART (viral load [VL] in South Africa and CD4 count in Malawi and Zambia) could explain this mortality difference. DESIGN Mathematical modelling study based on data from ART programmes. METHODS We used a stochastic simulation model to study the effect of VL monitoring on mortality over 5 years. In baseline scenario A all parameters were identical between strategies except for more timely and complete detection of treatment failure with VL monitoring. Additional scenarios introduced delays in switching to second-line ART (scenario B) or higher virologic failure rates (due to worse adherence) when monitoring was based on CD4 counts only (scenario C). Results are presented as relative risks (RR) with 95% prediction intervals and percent of observed mortality difference explained. RESULTS RRs comparing VL with CD4 cell count monitoring were 0.94 (0.74-1.03) in scenario A, 0.94 (0.77-1.02) with delayed switching (scenario B) and 0.80 (0.44-1.07) when assuming a 3-times higher rate of failure (scenario C). The observed mortality at 3 years was 10.9% in Malawi and Zambia and 8.6% in South Africa (absolute difference 2.3%). The percentage of the mortality difference explained by VL monitoring ranged from 4% (scenario A) to 32% (scenarios B and C combined, assuming a 3-times higher failure rate). Eleven percent was explained by non-HIV related mortality. CONCLUSIONS VL monitoring reduces mortality moderately when assuming improved adherence and decreased failure rates.

Do Increasing Rates of Loss to Follow-up in Antiretroviral Treatment Programs Imply Deteriorating Patient Retention?

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.

Franceschina Prevosti, Mary Prevosti, Doppelbildnis

Signatur des Originals: S 36/F01550

Mary Brand als Salomé, Rollenbild, in: Oscar Wilde: Salomé

Signatur des Originals: S 36/F03149

Mary Brand als Salomé, Rollenbild, in: Oscar Wilde: Salomé

Signatur des Originals: S 36/F03150

Mary Grasenick, Brustbild

Signatur des Originals: S 36/F04225

Käthe Hartmann, Arthur Hellmer, Georg Lengbach, Mary Urban, Rollenbild, Gruppenbildnis

Signatur des Originals: S 36/F04363

Mary Muenchhoff, Ganzfigurbildnis

Signatur des Originals: S 36/F05541

Mary Muenchhoff, Kniestück

Signatur des Originals: S 36/F05542

Mary Muenchhoff, Kniestück

Signatur des Originals: S 36/F05543

Mary Muenchhoff, Ganzfigurbildnis

Signatur des Originals: S 36/F05544