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H I V / A I D S M A J O R A R T I C L E
Incidence and Predictors of Death, Retention, and
Switch to Second-Line Regimens in Antiretroviral-
Treated Patients in Sub-Saharan African Sites with
Comprehensive Monitoring Availability
Leonardo Palombi,1Maria Cristina Marazzi,2Giovanni Guidotti,3Paola Germano,4Ersilia Buonomo,1
Paola Scarcella,1Annamaria Doro Altan,1Ines Da Vitoria M. Zimba,6Massimo Magnano San Lio,4
and Andrea De Luca,5for the DREAM Program
1Department of Public Health, University Tor Vergata,
Community of Sant’Egidio, and
2Libera Universita ` Maria SS Assunta,
3Istituto Superiore di Sanita `,
5Institute of Clinical Infectious Diseases, Catholic University, Rome, Italy; and
6DREAM Program, Maputo,
loss to follow-up. Switching to second-line regimens is often delayed because of limited access to laboratory
Retrospective analysis was performed of a cohort of adults who initiated a standard first-line anti-
retroviral treatment at 5 public sector sites in 3 African countries. Monitoring included routine CD4 cell counts,
human immunodeficiency virus RNA measures, and records of whether appointments were kept. Incidence and
predictors of death, loss to follow-up, and switch to second-line regimens were analyzed by time-to-event
A total of 3749 patients were analyzed; at baseline, 37.1% were classified as having World Health
Organization disease stage 3 or 4, and the median CD4 cell count was 192 cells/mL. First-line regimens were
nevirapine based in 96.5% of patients; 17.7% of patients attended !95% of their drug pickup appointments.
During 4545 person-years of follow-up, mortality was 8.6 deaths per 100 person-years and was predicted by lower
baseline CD4 cell count, lower hemoglobin level, and lower body mass index (calculated as weight in kilograms
divided by the square of height in meters); more-advanced clinical stage of infection; male sex; and more missed
drug pickup appointments. Dropouts (which accrued at a rate of 2.1 dropouts per 100 person-years) werepredicted
by a lower body mass index, more missed visits and missed drug pickup appointments, and later calendar year.
Incidence of switches to second-line regimens was 4.9 per 100 person-years; increased hazards were observed with
lower CD4 cell count and earlier calendar year at baseline. In patients who switched,virologicalfailurewaspredicted
by combined clinical and CD4 criteria with 74% sensitivity and 30% specificity.
In an antiretroviral treatment program employing comprehensive monitoring, the probability of
switching to second-line therapy was limited. Regular pickup of medication was a predictor of survival and was
also strongly predictive of patient retention.
Antiretroviral treatment programs in sub-Saharan Africa have high rates of early mortality and
The majority of HIV-1–infected individuals live in sub-
Saharan Africa . In these countries, AIDS-related
morbidity and mortality remain the highest in the
Received 12 June 2008; accepted 7 August 2008; electronically published 24
Reprints or correspondence: Dr. Andrea De Luca, Istituto di ClinicadelleMalattie
Infettive, Universita ` Cattolica S. Cuore, L. go F, Vito 1-00168 Rome, Italy (andrea
Clinical Infectious Diseases2009;48:115–22
? 2008 by the Infectious Diseases Society of America. All rights reserved.
world because of limited access to HIV diagnosis and
treatment. In recent years, efforts have been made to
expand access to antiretroviral treatment (ART) in sev-
eral low-income countries. Short-term observations on
the efficacy of ART in resource-limited settings show
encouraging results [2–5]. Nevertheless, major con-
cerns and unanswered questions remain regarding the
durability of treatment response, the long-term effect
Presented in part: 15th Conference on Retroviruses and Opportunistic Infections,
Boston, MA, February 2008 (abstract 835).
by guest on December 24, 2015
122 • CID 2009:48 (1 January) • HIV/AIDS
HIV-infected South African adults. J Acquir Immune Defic Syndr
34. Lima VD, Geller J, Bangsberg DR, et al. The effect of adherence on
the association between depressive symptoms and mortality among
HIV-infected individuals first initiating HAART. AIDS 2007;21:
35. Geng E, Bangsberg D, Musinguzi N, et al. What becomes of the de-
faulters? A sampling-based approach to determineoutcomesofpatients
who become lost to follow-up in ART scale-up programs in Africa
[abstract 842]. In: Program and abstracts of the 15th Conference on
Retroviruses and Opportunistic Infections (Boston, MA). 2008.
36. Muwanga A, Easterbrook P, Schaefer P, et al. Losses to follow-up in a
large ART program in Uganda [abstract 840].In:Programandabstracts
of the 15th Conference on Retroviruses and Opportunistic Infections
(Boston, MA). 2008.
37. Nash D, Korves C, Saito S, et al. Characteristics of facilities and pro-
grams delivering HIV care and treatment services are associated with
loss to follow-up rates in programs from 7 sub-Saharan African coun-
tries [abstract 838]. In: Program and Abstracts of the 15th Conference
on Retroviruses and Opportunistic Infections (Boston, MA). 2008.
38. Wang B, Losina E, Stark R, et al. Loss to follow-up in community
clinics in South Africa: role of CD4 count, gender, and pregnancy
[abstract 841]. In: Program and abstracts of the 15th Conference on
Retroviruses and Opportunistic Infectionsin (Boston, MA). 2008.
39. Ramadhani HO, Thielman NM, Landman KZ, et al. Predictors of
incomplete adherence, virologic failure, and antiviral drug resistance
among HIV-infected adultsreceivingantiretroviraltherapyinTanzania.
Clin Infect Dis 2007;45:1492–8.
40. Maskew M, MacPhail P, Menezes C, Rubel D. Lost to follow up: con-
tributing factors and challenges in South African patients on antiret-
roviral therapy. S Afr Med J 2007;97:853–7.
41. Dalal RP, Macphail C, Mqhayi M, et al. Characteristics and outcomes
of adult patients lost to follow-up at an antiretroviral treatment clinic
in Johannesburg, South Africa. J Acquir Immune Defic Syndr 2008;
42. Yu JK, Chen SC, Wang KY, et al. True outcomes for patients on an-
tiretroviral therapy who are “lost to follow-up” in Malawi. Bull WHO
43. Orrell C, Harling G, Lawn SD, et al. Conservation of first-line anti-
retroviral treatment regimen where therapeutic options are limited.
Antivir Ther 2007;12:83–8.
44. Kantor R, Diero L, DeLong A, et al. Immunological monitoring as an
indicator of virological failure may lead to premature switch tosecond-
line ART regimens [abstract 834]. In: Program and abstracts of the
45. Meya D, Tibenderana H, John L, et al. Evaluation of clinical and
laboratory parameters to predict viral response to ART in Uganda
[abstract 531]. In: Program and abstracts of the 14th Conference on
Retroviruses and Opportunistic Infections (Los Angeles, CA). 2007.
46. An S, Koole O, Haverkamp M, Sculier D, Thai S, Lynen L. Predictors
of virological failure in a Cambodian setting: findings from a cross-
sectional study at Sihanouk Hospital Centre of HOPE, Phnom Penh.
In: Program and abstracts of the 4th IAS Conference on HIV Path-
ogenesis, Treatment and Prevention (Sydney, Australia). 2007.
47. Cozzi-Lepri A, Phillips AN, Ruiz L, et al. Evolution of drug resistance
in HIV-infected patients remaining on a virologically failing combi-
nation antiretroviral therapy regimen. AIDS 2007;21:721–32.
48. Phillips AN, Pillay D, Miners AH, Bennett DE, Gilks CF, Lundgren
JD. Outcomes from monitoring of patients on antiretroviral therapy
in resource-limited settings with viral load, CD4 cell count, or clinical
observation alone: a computer simulation model. Lancet 2008;371:
by guest on December 24, 2015