Mortality of Patients Lost to Follow-Up in Antiretroviral
Treatment Programmes in Resource-Limited Settings:
Systematic Review and Meta-Analysis
Martin W. G. Brinkhof1*, Mar Pujades-Rodriguez1,2, Matthias Egger1,3
1Division of International and Environmental Health, Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland, 2Epicentre, Me ´decins Sans
Frontie `res, Paris, France, 3Department of Social Medicine, University of Bristol, Bristol, United Kingdom
Background: The retention of patients in antiretroviral therapy (ART) programmes is an important issue in resource-limited
settings. Loss to follow up can be substantial, but it is unclear what the outcomes are in patients who are lost to
Methods and Findings: We searched the PubMed, EMBASE, Latin American and Caribbean Health Sciences Literature
(LILACS), Indian Medlars Centre (IndMed) and African Index Medicus (AIM) databases and the abstracts of three conferences
for studies that traced patients lost to follow up to ascertain their vital status. Main outcomes were the proportion of
patients traced, the proportion found to be alive and the proportion that had died. Where available, we also examined the
reasons why some patients could not be traced, why patients found to be alive did not return to the clinic, and the causes
of death. We combined mortality data from several studies using random-effects meta-analysis. Seventeen studies were
eligible. All were from sub-Saharan Africa, except one study from India, and none were conducted in children. A total of
6420 patients (range 44 to 1343 patients) were included. Patients were traced using telephone calls, home visits and
through social networks. Overall the vital status of 4021 patients could be ascertained (63%, range across studies: 45% to
86%); 1602 patients had died. The combined mortality was 40% (95% confidence interval 33%–48%), with substantial
heterogeneity between studies (P,0.0001). Mortality in African programmes ranged from 12% to 87% of patients lost to
follow-up. Mortality was inversely associated with the rate of loss to follow up in the programme: it declined from around
60% to 20% as the percentage of patients lost to the programme increased from 5% to 50%. Among patients not found,
telephone numbers and addresses were frequently incorrect or missing. Common reasons for not returning to the clinic
were transfer to another programme, financial problems and improving or deteriorating health. Causes of death were
available for 47 deaths: 29 (62%) died of an AIDS defining illness.
Conclusions: In ART programmes in resource-limited settings a substantial minority of adults lost to follow up cannot be
traced, and among those traced 20% to 60% had died. Our findings have implications both for patient care and the
monitoring and evaluation of programmes.
Citation: Brinkhof MWG, Pujades-Rodriguez M, Egger M (2009) Mortality of Patients Lost to Follow-Up in Antiretroviral Treatment Programmes in Resource-
Limited Settings: Systematic Review and Meta-Analysis. PLoS ONE 4(6): e5790. doi:10.1371/journal.pone.0005790
Editor: Sean Emery, University of New South Wales, Australia
Received February 6, 2009; Accepted May 1, 2009; Published June 4, 2009
Copyright: ? 2009 Brinkhof et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This project was supported by UNAIDS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org
In industrialized countries the prognosis of HIV infection has
improved considerably since highly active antiretroviral therapy
(ART) was introduced from 1995 onwards [1–3]. In low-income
countries with a high burden of HIV and AIDS, ART has become
more widely available in recent years. The World Health
Organisation (WHO) estimates that about 3 million people were
receiving ART in low- and middle-income countries by the end of
2007, a 7.5-fold increase during the past four years .
ART of individual patients and the monitoring and evaluation of
treatment programmes critically depend on regular patient follow-
up. Individual treatment decisions can then be made and treatment
response, complication and mortality rates can be accurately
estimated at the programme level [5,6]. Using data from a network
of ART treatment programmes in resource-limited settings, we
found that on average 21% of patients had been lost to programmes
in the first six months after starting ART . Similarly, a systematic
review of ART programmes in sub-Saharan Africa found that about
40% of patients were lost at two years, with large variation in
retention rates between programmes .
The outcome of patients lost to follow has received relatively
little attention. Patients not returning to the clinic where they
initiated ART may have stopped taking antiretroviral drugs,
resulting in high mortality. Alternatively, with increasing avail-
ability of ART, patients may have transferred to another
programme, for example a programme closer to their place of
residence. We performed a systematic review and meta-analysis of
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studies that determined the vital status of patients who were lost to
follow-up (LTFU) after starting ART in low or middle-income
countries. Our objectives were to describe mortality and causes of
death among patients LTFU, to examine the reasons why patients
LTFU could not be traced and why those traced alive had not
returned to the clinic. Our aims were to inform the adjustment of
mortality estimates for LTFU, to identify critical issues in patient
registration and follow-up and inform strategies to improve patient
retention and ascertainment of outcomes.
We aimed to identify studies that determined the vital status of
all or a subset of patients lost to follow-up after starting ART in
treatment programmes in Africa, Asia or Latin America. We
searched the PubMed, EMBASE, Latin American and Caribbean
Health Sciences Literature (LILACS), Indian Medlars Centre
(IndMed) and African Index Medicus (AIM) databases. We limited
the search to studies in humans; studies from Africa, Asia or Latin
America; and studies published between January 1, 2000 and
January 9, 2009. In PubMed we used a combination of free text
and Medical Subject Headings (MeSH) and then adapted the
search to the other databases. The searches of LILACS and AIM
included Spanish, Portuguese and French terms. Further details
are given in the Appendix S1.
Using similar keywords we searched the abstract databases of
the Conference on Retroviruses and Opportunistic Infections
(CROI, 1997–2008) ; the Conference on HIV Pathogenesis and
Treatment of the International AIDS Society (IAS, 2001–2008)
and the International AIDS Conference (AIDS; 2001–2008) .
We used Google Scholar  to identify electronic publications
ahead of print of eligible studies presented at CROI, IAS or AIDS.
Finally, we included a study that was accepted for presentation at
CROI 2009 conference and co-authored by one of us (M.P-R.).
We included all articles reporting studies where patients LTFU
in ART programmes in Africa, Asia or Latin America were
actively traced to establish their vital status. We excluded studies
from high-income countries, case reports, and studies of patients
who were LTFU while not on ART. Two reviewers (M.B. and
M.P-R.) independently assessed the eligibility of articles and
abstracts. Discrepancies were resolved in consultation with a third
Data were extracted in duplicate by the same two reviewers
using a standardised questionnaire that covered the characteristics
of the ART programme, including location and country; the
number of patients enrolled and on ART; the setting (urban, semi-
urban or rural); and whether the programme was public or
private. We also extracted the definition of LTFU used in the
different studies; the total number of patients LTFU and the
number of patients traced; the methods used to trace patients
(letter, telephone call, and/or home visits); and whether the study
involved both patients on ART and not on ART. Discrepancies
were resolved by consensus.
The main outcomes were the number of patients who could not
be traced, the number who were found to be alive and the number
who had died. For patients LTFU who could not be traced, we
examined data on possible reasons. For patients found to be alive
we extracted the reasons reported for not returning to the clinic.
We classified reasons as transfer to another clinic; stopping
treatment because of improved health; hospitalised or being too
sick to come to the clinic; stigma and social problems; adverse
effects of drugs; logistic problems and economic reasons (including
cost for transport) and other reasons. Finally, for patients who were
known to have died, we extracted information on the likely cause
of death. Causes of death were classified as AIDS defining illness;
condition not related to AIDS; unnatural cause; and unknown.
We expressed results as percentages and calculated exact
binomial 95% confidence intervals for these percentages. We
combined data from several studies using random-effects meta-
analysis on the logit scale, and transformed combined estimates
back to percentages. We then investigated, for the programmes
from sub-Saharan Africa, associations between study characteris-
tics and mortality in patients LTFU using random effects meta-
regression. Study characteristics considered were: setting (2
categories: urban vs. rural/urban-rural); definition of LTFU (3
categories: missed 1 or 2 scheduled visits, missed last scheduled
visit by 2–6 weeks; missed last scheduled visit by .3 months);
method of tracing (3 categories: telephone call, home visit,
telephone call and home visit); percentage of patients LTFU
included in the survey; and percentage of patients traced and
actually retrieved during the survey. Data were analysed using
STATA version 10.1 (StataCorp, Texas, USA).
Figure 1 describes the process of identifying eligible studies.
Among the 323 published items and 659 conference abstracts
retrieved, we identified 16 eligible reports (six published articles,
one published research letter, one article published electronically
ahead of print and eight abstracts), which included data on 17
Table 1 summarises the characteristics of the 17 studies. One
article  reported two studies, one from a public ART
programme (No. 12 in Table 1) and one from a workplace
programme (No. 13) in South Africa. Sixteen were performed in
nine sub-Saharan African countries: South Africa (5 studies),
Malawi (3 studies), Uganda (2 studies), Zambia, Botswana,
Ethiopia, Kenya, Tanzania, and Mali (one study each). One
study was from India. Figure 2 shows the geographical location of
studies. Two studies (Nos. 4 and 8) [13,14] included both patients
on ART and not on ART. We did not identify any studies in
children. Most settings were urban or semi-urban; five studies were
from a rural setting. Definitions of LTFU varied. Missing
appointments for more than 1 month or more than 3 months
was used in several studies (Table 1). Patients were traced using
telephone calls, home visits or through social networks. The
median duration of follow up from start of ART to last contact in
patients LTFU was 1.5 months , 2.7 months , 4.3 months
, 13.9 months , and not reported in the remaining 12
studies. Median times from start of ART to death in patients
LTFU ranged from 1.5 to 2.9 months in the four studies
[16,17,19,20] that reported this information. In addition, it is clear
that in a further two studies [14,18] deaths among patients LTFU
occurred predominantly in the first 6 months after start of ART.
Vital status of patients
The number of patients traced and their vital status are
summarized in Table 2. Nine studies traced all patients LTFU
during the study period and six included a subset of patients
representing 15% to 53% of all patients LTFU. Two studies
Loss to Follow-Up & Mortality
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[21,22] only included patients who had agreed to being traced if
[14,18,23,24] did not report any criteria for inclusion of patients
in the tracing effort. In two other studies [13,15] the proportion of
patients LTFU included in the study was unclear. A total of 6420
patients were traced. Overall, vital status of 4021 patients (63%)
could be ascertained; the percentage ascertained ranged from 45%
to 87%. A total of 1602 patients had died (40%, range across
studies 12% to 87%). The combined mortality from random
effects meta-analysis was 40% (95% CI 33%–48%). When
removing the two studies that included patients not on ART,
The remainingfour studies
mortality increased to 42% (95% CI 34%–50%). When further
restricting the analysis to public ART programmes in sub-Saharan
Africa (12 studies), mortality was 46% (95% CI: 39%–54%). In all
three meta-analyses the between-study heterogeneity was substan-
tial, with I2values .90% and P from tests of heterogeneity
,0.0001 (Figure 3).
In the studies from sub-Saharan Africa, the percentage of
patients LTFU in a programme was associated with mortality in
the patients LTFU (p from meta-regression model=0.02). The
estimated mortality in patients LTFU declined from around 60%
to 20% as the percentage of patients LTFU in the programme
Figure 1. Identification and selection of eligible studies.
Loss to Follow-Up & Mortality
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increased from 5% to 50% (Figure 4). The association was similar
when excluding the two studies [13,14] that included some
patients not on ART, or the study in a South African mine .
There was little evidence that in addition to the percentage of
patients LTFU mortality varied with other characteristics,
including the setting of the programme (p=0.51), definition of
LTFU used (p=0.90), method of tracing (p=0.75), the proportion
of patients LTFU included in the survey (p=0.73), and the
proportion of patients successfully traced (p=0.80).
Reasons why patients were not found
Seven studies [15–17,20,23,25,26] provided information on the
reasons why the tracing of 401 patients was unsuccessful. The
majority of patients (333, 83%) were not found because of an
incorrect, incomplete or missing telephone number or home
address in the patient file. Sixty-four patients (16%) had moved to
an unknown location, or a location too far from the clinic to allow
a home visit. Reasons were unknown in the remaining patients.
Two studies [13,27] mentioned inadequate contact information as
the main reason why tracing failed, but did not give any figures.
Three studies compared the characteristics of patients who were
found to those who could not be traced [13,16,21]. Two of the
three studies reported that the patients not found had distributions
of clinical stage, CD4 counts and viral load similar to patients
found to be alive [13,16]. However, Hochgesang et al. 
reported that patients who could not be found had low initial CD4
counts and suggested that many of these might have died.
Reasons for not returning to the clinic
Reasons for not returning to the clinic among patients found
alive were assessed in 11 studies, for 1096 (75%) of the 1464
surviving patients (Table 3). Not all reasons were considered in all
programmes, and the importance of different reasons varied across
programmes. Common reasons included the transfer to another
ART programme, financial problems (for example with costs of
transport), and improved or deteriorating health. Stigma and
Table 1. Characteristics of ART programmes tracing patients LTFU in low- and middle-income countries.
No. StudyLocation Setting LTFU definition Contact methodStudy period
on ART% LTFU
1Yu 2007 Four facilities in
RuralNo visit for .3 months Home visit2004–200550095.0
2Maskew 2007 Johannesburg, South
3 Dalal 2008 Johannesburg, South
UrbanMissed appointments .6
Telephone & home
4 Krebs 2008 #
Lusaka, ZambiaUrban &
Missed appointments .1
week or month
Home visit2005 n.r. 21.0*
5 Bisson 2008  Gaborone, BotswanaUrban Missed appointments .30
Telephone & home
6 Geng 2008  Mbarara, UgandaRural Missed appointments $6
Home visit2004–20073628 22.9
7Deribe 2008  Jimma, EthiopiaUrban Missed $2 appointmentsTelephone & home
8An 2008 #
Eldoret, KenyaUrban & ruralMissed appointmentsTelephone & home
9 Ive 2005 Johannesburg, South
UrbanStopped attending the
Lilongwe, Malawi UrbanMissed appointments .2
11Billy 2007  Bukoba, TanzaniaRuralNo visit for .3 monthsHome visit2005–2007156217.5
12Dahab 2008 Public programme,
Gauteng, South Africa
UrbanMissed appointments .1
Telephone & home
13Dahab 2008  Mine programme,
WorkplaceMissed appointments .1
Telephone & home
14Lurton 2008 Segu region, MaliRuralNo visit for .3 monthsTelephone, social
network & home visit
15Joshi 2008 Jodhpur, India Urban & RuralNo visit for .3 months Telephone, social
16Muwanga 2008  Kampala, UgandaUrbanMissed appointments .3
17McGuire 2009  Chiradzulu, MalawiRuralMissed appointments .1
Home visit2008 1105711.4
n.r.: not reported.
#studies including patients not on ART.
*estimate from Stringer et al. 2006 .
Loss to Follow-Up & Mortality
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social problems and adverse effects were less frequently men-
tioned. Other reasons reported in single studies were pregnancy or
childbirth , advice from care provider , administrative
problems (for example loss of patient cards)  or religious beliefs
Causes of death in patients LTFU
The cause of death was investigated for 128 deaths in three
studies from Johannesburg, South Africa [15,16,20], using verbal
autopsy. For 81 patients (63%) the cause of death remained
unknown. For the other 47 deaths, the reported cause of death was
an AIDS defining illness in 29 patients (62%), a condition not
related to AIDS in 16 patients (34%) and an unnatural cause in
two patients (4%).
This systematic review and meta-analysis of studies that traced
patients who were LTFU in ART programmes in resource-limited
settings showed that the outcome of over a third of patients
remained unknown. All studies except one were conducted in sub-
Saharan Africa and no study was done in children. Among African
adults who were LTFU after starting ART and successfully traced,
the combined mortality was 46%. Mortality ranged from 12% to
87% across studies, and was inversely associated with the rate of
LTFU in the programmes. Incorrect or missing telephone
numbers and addresses were often the reason why patients could
not be located. Transfer to another programme, financial
constraints and improving or deteriorating health were common
reasons for not returning to the clinic.
We performed a comprehensive search of the literature, including
of abstracts presented at three major HIV/AIDS conferences, thus
minimizing possible publication bias. We identified studies of over
6,000 patients who were LTFU in ART programmes in 10 low- or
middle-income countries. Sites were heterogeneous and included
both rural and urban locations. The approach used to trace patients
varied and included telephone calls, home visits and social networks.
Our findings should therefore be applicable to other ART
programmes, particularly in sub-Saharan Africa.
Definitions of LTFU and the assessment of reasons for not
returning to the clinic were not standardized across studies, which
precluded formal meta-analysis of these data, and information on
causes of death was limited. Other limitations include the lack of
information, in most studies, on the time of death. The limited
information that is available from some studies [16,17,19,20]
indicates that patients were lost in the first few months of ART,
Figure 2. Map of study locations. The numbers refer to Table 1.
Loss to Follow-Up & Mortality
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and died soon thereafter. Data from the ART in Lower Income
Countries (ART-LINC) collaboration and other treatment
programmes, for example the Me ´decins Sans Frontie `res (MSF)
programmes in Malawi , and South Africa , showed that
loss to follow-up and death mostly occur in the first six months
after ART initiation.
A high risk of death in the first few months after starting ART is
characteristic of resource-limited settings where most patients start
therapy late with advanced disease [5,29,30]. However, mortality
in patients LTFU is substantially higher than the mortality
commonly reported in the first year of ART based on routinely
recorded deaths and, censoring of follow-up in patients LTFU
[5,29,31]. ART programmes with high rates of LTFU and poor
ascertainment of deaths may therefore seriously underestimate
mortality. Furthermore, mortality among patients LTFU differs
depending on the rate of LTFU of the treatment programme:
mortality declined with increasing rates of LTFU. In programmes
with high rates of LTFU those LTFU might thus include a sizeable
group of low-risk patients who self-transferred to another
programme, for example because of a more convenient location
of the new clinic, to avoid stigma or due to work-related reasons.
The results of dedicated studies tracing patients LTFU can be used
to correct naı ¨ve estimates of mortality in a given programme
[6,14,18]. In the absence of such studies, the data from this
systematic review provide a sensible range of estimates of mortality
in patients LTFU which can be used in sensitivity analyses to
adjust overall mortality.
In most studies an important proportion of patients could not be
located, and mortality of those whose vital status could be
ascertained may not be representative of all patients LTFU.
Contact information that is absent, incorrect or out-of-date could
be related to the risk of death. For example, healthier individuals
may be more mobile than sicker patients, and more likely to leave
the catchment area of the clinic in search of work. Conversely,
patients providing incorrect details may be part of a vulnerable
group, with little social support and low adherence to ART. If
results of tracing studies are likely to be affected by selection bias,
correction of mortality is again best done in sensitivity analyses,
using a range of plausible values. Clearly, the quality and
completeness of patient’s contact details should be improved and
regularly updated during follow-up. Of note, a recent survey 
of electronic medical record systems used in ART programmes in
lower-income countries found that well managed databases might
contribute to retaining patients in programmes.
An understanding of the reasons for not returning to care is
important to the design of effective and cost-effective ART
programmes. Outreach teams that routinely trace patients,
combined with other measures, can substantially reduce LTFU
, but such teams are costly, and the emphasis should be on the
prevention of LTFU. Transfer to another programme was
common among patients found to be alive. Strengthening of
referral systems and regular exchange of information between
clinics, together with patient education could increase the
recording of transfers and ensure continuity of care. Unsurpris-
Table 2. Vital status of patients lost to follow up in ART programmes in resource-limited settings.
Number of patientsVital status of patients lost to follow-up (%)
LTFU Included (%) Unknown (n)Alive (n) Dead (n)
Yu 2007 253253 (100%)27% (68)23% (58) 50% (127) 69%
Maskew 2007154154 (100%) 55% (84) 33% (51)12% (19) 27%
Dalal 2008 267267 (100%)35% (94)34% (90)31% (83) 48%
n.r. 1343 (-)41% (554)32% (430)27% (359) 46%
Bisson 2008 6868 (100%)32% (22)9% (6)59% (40)87%
Geng 2008 829128 (15%) 13% (17) 62% (79) 25% (32)29%
Deribe 2008 355355 (100%) 18% (65) 61% (215)21% (75) 27%
35281143 (32%)46% (522)43% (497)11% (124) 20%
Ive 2005 n.r.74 (-)35% (26) 30% (22) 35% (26)54%
Hochgesang 2006 1843727 (39%) 26% (189)44% (320)30% (218) 41%
Billy 2007273113 (41%) 14% (16) 55% (62)31% (35)36%
Dahab 2008 4444 (100%) 20% (9)39% (17)41% (18) 51%
5353 (100%)23% (12)68% (36)9% (5)12%
Lurton 2008 23661 (26%)16% (10)43% (26) 41% (25)49%
152152 (100%)30% (46)61% (93) 9% (13) 12%
Muwanga 2008 831831 (100%) 55% (459) 26% (213)19% (159)43%
McGuire 20091233654 (53%)32% (206)31% (204)37% (244)54%
Overall 6420 (100%)37%38% 25%40%
Patients on ART (excluding#)393434%38% 28%42%
On ART, Africa, public
programme, (excluding#, $)
372934%37% 29% 46%
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Loss to Follow-Up & Mortality
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ingly, financial constraints were another common reason for not
returning to the clinic. Direct and indirect costs related to the
provision of care have been identified as major obstacles to access
to ART, acceptance of ART  and adherence to treatment
[34,35]. Mortality in programmes that charge user fees has been
shown to be higher than in those offering free treatment .
Decentralisation of services, task shifting to lay care providers,
longer drug refill periods for stable patients, as well as provision of
transport vouchers for those in need are some of the strategies that
could address this issue.
Other important reasons for LTFU were improvements in
health, adverse effects and feeling too sick to come to the clinic or
being hospitalised. Reports of stopping care as a result of perceived
improved health reflect a poor understanding of the chronic
nature of the disease and the need for continued, life-long ART.
The experience or fear of toxicities has been found to be associated
with poor adherence in previous studies [36,37]. These issues need
to be addressed through training of care givers and preparing
patients for ART. Interventions that are aimed at the individual
(rather than groups) and provided over longer time periods (.12
weeks) have been shown to be effective in improving adherence to
Stigma and social problems were also repeatedly mentioned.
Fear of disclosure, social isolation or the exposure to a
discouraging social network have being identified as barriers to
treatment adherence in studies conducted in high and low-income
settings [35,39]. In a study conducted in Botswana, Tanzania and
Uganda, patients reported difficulties in taking their drugs when
they were among employers, co-workers or friends to whom they
had not disclosed their HIV status . The development of
practical medication management skills in open discussions with
patients could be beneficial in this context .
In conclusion, a substantial minority of patients LTFU cannot
be traced and among those traced on average 46% of patients
have died. Transfer to another programme, financial constraints
and improving or deteriorating health were common reasons for
not returning to the clinic. These findings have important
implications both for patient care and the monitoring and
evaluation of ART programmes in resource-limited settings.
Found at: doi:10.1371/journal.pone.0005790.s001 (0.05 MB
Figure 3. Mortality of patients LTFU that were successfully traced. Study-specific mortality estimates with binomial exact confidence
intervals, combined estimates and confidence intervals from random effects meta-analysis. Studies including patients not on ART (#; squares);
workplace programme, programme from outside Africa ($; triangles).
Figure 4. Estimated change in mortality among patients LTFU
with proportion of patients LTFU in programme. Analysis based
on 15 studies from sub-Saharan Africa. The area of each circle is
inversely proportional to the variance of the estimate for that study.
Table 3. Reasons for not returning to ART programme among patients found alive.
% of patients
Too sick to come
Stigma & social
Yu 2007100% (58)35% 22% n.r.n.r.7% n.r. 36%
Maskew 2007100% (51) 12% 47%n.r.n.r. 8% 2% 31%
Dalal 2008100% (90) 49% 2%10% 20%n.r. 6% 13%
63% (271) n.r. n.r. 4% 23%7% n.r.67%
Deribe 200879% (170) n.r. n.r.n.r.n.r. 64%8% 28%
Ive 2005 100% (22)43%14%n.r. n.r.n.r. 19% 24%
Billy 200797% (60) 35% n.r. 62%n.r.n.r.n.r. 3%
Lurton 2008 100% (26) 54%n.r.n.r. n.r. n.r.n.r.n.r.
Joshi 200892% (86) 14% 45% 3%n.r.n.r.5% 33%
Muwanga 2008100% (213) 17%n.r.26% n.r.n.r. n.r.57%
McGuire 200924% (49) n.r.n.r.20% n.r. 20% 10% 50%
n.r.; not reported.
Loss to Follow-Up & Mortality
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Acknowledgments Download full-text
We are grateful to Doris Kopp for expert help with literature searches. We
would also like to thank S. Charalambous, P. Tattevin, G. Lurton and M.
Maskew for providing additional information on their studies.
Analyzed the data: MWGB. Wrote the paper: MWGB MPR ME.
Conceived and designed the systematic review: MWGB MPR ME.
Performed data extraction: MWGB MPR.
1. Egger M, Hirschel B, Francioli P, Sudre P, Wirz M, et al. (1997) Impact of new
antiretroviral combination therapies in HIV infected patients in Switzerland:
prospective multicentre study. Swiss HIV Cohort Study. BMJ 315: 1194–1199.
2. Mocroft A, Vella S, Benfield TL, Chiesi A, Miller V, et al. (1998) Changing
patterns of mortality across Europe in patients infected with HIV-1. EuroSIDA
Study Group. Lancet 352: 1725–1730.
3. Palella FJ Jr, Delaney KM, Moorman AC, Loveless MO, Fuhrer J, et al. (1998)
Declining morbidity and mortality among patients with advanced human
immunodeficiency virus infection. HIV Outpatient Study Investigators.
N Engl J Med 338: 853–860.
4. World Health Organization (2008) Towards universal access. Scaling up priority
HIV/AIDS interventions in the health sector. Progress report 2008. Available:
5. Braitstein P, Brinkhof MWG, Dabis F, Schechter M, Boulle A, et al. (2006)
Mortality of HIV-1-infected patients in the first year of antiretroviral therapy:
comparison between low-income and high-income countries. The Lancet 367:
6. Yiannoutsos CT, An M-W, Frangakis CE, Musick BS, Braitstein P, et al. (2008)
Sampling-based approaches to improve estimation of mortality among patient
dropouts: experience from a large PEPFAR-funded program in Western Kenya.
PLoS ONE 3: e3843.
7. Brinkhof MW, Dabis F, Myer L, Bangsberg DR, Boulle A, et al. (2008) Early loss
of HIV-infected patients on potent antiretroviral therapy programmes in lower-
income countries. Bulletin of the World Health Organization 86: 497–576.
8. Rosen S, Fox MP, Gill CJ (2007) Patient retention in antiretroviral therapy
programs in sub-Saharan Africa: A systematic review. PLoS Medicine 4: e298.
9. Conference on Retroviruses and Opportunistic Infections. Abstract Search.
10. International AIDS Society Abstract Search. Available: http://www.iasociety.
11. Google Scholar. Available: http://scholar.google.com/.
12. Dahab M, Charalambous S, Karstaedt A, Hamilton R, Makoa Z, et al. (2008)
Off the radar screen: comparing reasons for treatment default in a workplace
ART programme and a public sector clinic in South Africa (Abstract
no. THPE0123). AIDS 2008 - XVII International AIDS Conference. Mexico
13. Krebs DW, Chi BH, Mulenga Y, Morris M, Cantrell RA, et al. (2008)
Community-based follow-up for late patients enrolled in a district-wide
programme for antiretroviral therapy in Lusaka, Zambia. AIDS Care 20:
14. An M-W, Frangakis CE, Musick BS, Yiannoutsos CT (2009) The need for
double-sampling designs in survival studies: an application to monitor PEPFAR.
Biometrics 65: 301–306.
15. Ive P, Conradie F, Xaba S, Sanne I (2005) Causes of loss to follow up in patients
taking antiretroviral therapy in the national rollout program of South Africa
(Abstract no. MoPp0304). The 3rd IAS Conference on HIV Pathogenesis and
Treatment. Rio de Janeiro, Brasil.
16. Dalal RP, Macphail C, Mqhayi M, Wing J, Feldman C, et al. (2008)
Characteristics and outcomes of adult patients lost to follow-up at an
antiretroviral treatment clinic in Johannesburg, South Africa. J Acquir Immune
Defic Syndr 47: 101–107.
17. Yu JK-L, Chen SC-C, Wang K-Y, Chang C-S, Makombe SD, et al. (2007) True
outcomes for patients on antiretroviral therapy who are ‘‘lost to follow-up’’ in
Malawi. Bulletin of the World Health Organization 85: 550–554.
18. Geng EH, Emenyonu N, Bwana MB, Glidden DV, Martin JN (2008) Sampling-
based approach to determining outcomes of patients lost to follow-up in
antiretroviral therapy scale-up programs in Africa. JAMA 300: 506–507.
19. Bisson GP, Gaolathe T, Gross R, Rollins C, Bellamy S, et al. (2008)
Overestimates of survival after HAART: implications for global scale-up efforts.
PLoS ONE 3: e1725.
20. Maskew M, MacPhail P, Menezes C, Rubel D (2007) Lost to follow up:
contributing factors and challenges in South African patients on antiretroviral
therapy. S Afr Med J 97: 853–857.
21. Hochgesang M, Kuyenda A, Hosseinipour M, Phiri S, Weigel R, et al. (2006)
Active tracing of ART patients lost to follow-up at lighthouse shows that few
‘stopped’ treatment for their own reasons, but many have died (Abstract
no. TUPE0119). AIDS 2006 - XVI International AIDS Conference. Toronto.
22. McGuire M, Munyenyembe T, Althomsons S, Bouithy N, Le Paih M, et al.
(2009) Double sampling of ART and pre-ART patients defaulting from care to
determine vital outcomes in an HIV/AIDS program in rural Malawi. 16th
Conference on Retroviruses and Opportunistic Infections. Montreal, Canada.
23. Billy A, Mujaki J, Johnathan S, Rwamahe S, Barongo J, et al. (2007) What does
‘‘lost to follow-up’’ mean for patients enrolled in an highly active antiretroviral
treatment (HAART) programme in Africa? (Abstract no. CDB514). 4th IAS
Conference on HIV Pathogenesis, Treatment and Prevention. Sidney, Australia.
24. Lurton G, Akonde ´ A, Madec Y, Teisseire P, Traore T, et al. (2008) Looking for
lost to follow-up patients: experience of Se ´gou, Mali (Abstract no. MOPE0749).
AIDS 2008 - XVII International AIDS Conference. Mexico City, Mexico.
25. Deribe K, Hailekiros F, Biadgilign S, Amberbir A, Beyene BK (2008) Defaulters
from antiretroviral treatment in Jimma University Specialized Hospital,
Southwest Ethiopia. Tropical Medicine & International Health 13: 328–333.
26. Joshi K, Jhanwar S, Mathur A, Agarwal H, Mathur SL (2008) Barriers in
adherence of ART (anti retroviral treatment): a experience of ART Centre of
Western Rajasthan, India (Abstract no. CDB0504). AIDS 2008 - XVII
International AIDS Conference. Mexico City, Mexico.
27. Muwanga A, Easterbrook P, Schaefer P, Wandera M, Okello D, et al. (2008)
Losses to follow-up in a large ART program in Uganda (Abstact No. 840). 15th
Conference on Retroviruses and Opportunistic Infections. Boston, Massachu-
28. Ferradini L, Jeannin A, Pinoges L, Izopet J, Odhiambo D, et al. (2006) Scaling
up of highly active antiretroviral therapy in a rural district of Malawi: an
effectiveness assessment. Lancet 367: 1335–1342.
29. Boulle A, Bock P, Osler M, Cohen K, Channing L, et al. (2008) Antiretroviral
therapy and early mortality in South Africa. Bull World Health Organ 86:
30. Stringer JS, Zulu I, Levy J, Stringer EM, Mwango A, et al. (2006) Rapid scale-up
of antiretroviral therapy at primary care sites in Zambia: feasibility and early
outcomes. JAMA 296: 782–793.
31. Etard JF, Ndiaye I, Thierry-Mieg M, Gueye NF, Gueye PM, et al. (2006)
Mortality and causes of death in adults receiving highly active antiretroviral
therapy in Senegal: a 7-year cohort study. AIDS 20: 1181–1189.
32. Forster M, Bailey C, Brinkhof MW, Graber C, Boulle A, et al. (2008) Electronic
medical record systems, data quality and loss to follow-up: survey of
antiretroviral therapy programmes in resource-limited settings. Bull World
Health Organ 86: 939–947.
33. Zachariah R, Harries AD, Manzi M, Gomani P, Teck R, et al. (2006)
Acceptance of anti-retroviral therapy among patients infected with HIV and
tuberculosis in rural Malawi is low and associated with cost of transport. PLoS
ONE 1: e121.
34. Hardon AP, Akurut D, Comoro C, Ekezie C, Irunde HF, et al. (2007) Hunger,
waiting time and transport costs: time to confront challenges to ART adherence
in Africa. AIDS Care 19: 658–665.
35. Weiser S, Wolfe W, Bangsberg D, Thior I, Gilbert P, et al. (2003) Barriers to
antiretroviral adherence for patients living with HIV infection and AIDS in
Botswana. J Acquir Immune Defic Syndr 34: 281–288.
36. Ammassari A, Antinori A, Cozzi-Lepri A, Trotta MP, Nasti G, et al. (2002)
Relationship between HAART adherence and adipose tissue alterations.
J Acquir Immune Defic Syndr 31 Suppl 3: S140–144.
37. Ammassari A, Murri R, Pezzotti P, Trotta MP, Ravasio L, et al. (2001) Self-
reported symptoms and medication side effects influence adherence to highly
active antiretroviral therapy in persons with HIV infection. J Acquir Immune
Defic Syndr 28: 445–449.
38. Rueda S, Park-Wyllie LY, Bayoumi AM, Tynan AM, Antoniou TA, et al. (2006)
Patient support and education for promoting adherence to highly active
antiretroviral therapy for HIV/AIDS. Cochrane Database Syst Rev 3:
39. Mills EJ, Nachega JB, Bangsberg DR, Singh S, Rachlis B, et al. (2006)
Adherence to HAART: a systematic review of developed and developing nation
patient-reported barriers and facilitators. PLoS Med 3: e438.
Loss to Follow-Up & Mortality
PLoS ONE | www.plosone.org9 June 2009 | Volume 4 | Issue 6 | e5790