Analyzed the data: MWGB. Wrote the paper: MWGB MPR ME. Conceived and designed the systematic review: MWGB MPR ME. Performed data extraction: MWGB MPR.
The authors have declared that no competing interests exist.
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 programmes.
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.
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.
In industrialized countries the prognosis of HIV infection has improved considerably since highly active antiretroviral therapy (ART) was introduced from 1995 onwards
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
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 availability 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 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
Using similar keywords we searched the abstract databases of the Conference on Retroviruses and Opportunistic Infections (CROI, 1997–2008)
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 reviewer (M.E.).
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 characteristics 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).
The numbers refer to
No. | Study | Location | Setting | LTFU definition | Contact method | Study period | No patients on ART | % LTFU |
1 | Yu 2007 |
Four facilities in Malawi | Rural | No visit for >3 months | Home visit | 2004–2005 | 5009 | 5.0 |
2 | Maskew 2007 |
Johannesburg, South Africa | Urban | Missed appointments | Telephone | n.r. | 5849 | n.r. |
3 | Dalal 2008 |
Johannesburg, South Africa | Urban | Missed appointments >6 weeks | Telephone & home visit | 2004–2005 | 1631 | 16.4 |
4 | Krebs 2008 |
Lusaka, Zambia | Urban & semi-urban | Missed appointments >1 week or month | Home visit | 2005 | n.r. | 21.0 |
5 | Bisson 2008 |
Gaborone, Botswana | Urban | Missed appointments >30 days | Telephone & home visit | 2003 | 410 | 16.6 |
6 | Geng 2008 |
Mbarara, Uganda | Rural | Missed appointments ≥6 months | Home visit | 2004–2007 | 3628 | 22.9 |
7 | Deribe 2008 |
Jimma, Ethiopia | Urban | Missed ≥2 appointments | Telephone & home visit | 2007 | 1270 | 28.0 |
8 | An 2008 |
Eldoret, Kenya | Urban & rural | Missed appointments | Telephone & home visit | 2005–2007 | 8977 | 39.3 |
9 | Ive 2005 |
Johannesburg, South Africa | Urban | Stopped attending the ARV clinic | Telephone | 2004–2005 | 2400 | 3.1 |
10 | Hochgesang 2006 |
Lilongwe, Malawi | Urban | Missed appointments >2 weeks | Home visit | 2005 | 3840 | 48.0 |
11 | Billy 2007 |
Bukoba, Tanzania | Rural | No visit for >3 months | Home visit | 2005–2007 | 1562 | 17.5 |
12 | Dahab 2008 |
Public programme, Gauteng, South Africa | Urban | Missed appointments >1 month | Telephone & home visit† | 2007 | 267 | 16.5 |
13 | Dahab 2008 |
Mine programme, Rustenburg, South Africa | Workplace | Missed appointments >1 month | Telephone & home visit | 2007 | 146 | 36.3 |
14 | Lurton 2008 |
Segu region, Mali | Rural | No visit for >3 months | Telephone, social network & home visit | 2008 | 1568 | 15.1 |
15 | Joshi 2008 |
Jodhpur, India | Urban & Rural | No visit for >3 months | Telephone, social network | n.r. | 1191 | 12.8 |
16 | Muwanga 2008 |
Kampala, Uganda | Urban | Missed appointments >3 month | Telephone | 2007–2008 | 6421 | 12.9 |
17 | McGuire 2009 |
Chiradzulu, Malawi | Rural | Missed appointments >1 month | Home visit | 2008 | 11057 | 11.4 |
n.r.: not reported.
studies including patients not on ART.
estimate from Stringer et al. 2006
The number of patients traced and their vital status are summarized in
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).
Study | Number of patients | Vital status of patients lost to follow-up (%) | ||||
LTFU | Included (%) | Unknown (n) | Alive (n) | Dead (n) | Mortality among traced | |
Yu 2007 | 253 | 253 (100%) | 27% (68) | 23% (58) | 50% (127) | 69% |
Maskew 2007 | 154 | 154 (100%) | 55% (84) | 33% (51) | 12% (19) | 27% |
Dalal 2008 | 267 | 267 (100%) | 35% (94) | 34% (90) | 31% (83) | 48% |
Krebs 2008# | n.r. | 1343 (-) | 41% (554) | 32% (430) | 27% (359) | 46% |
Bisson 2008 | 68 | 68 (100%) | 32% (22) | 9% (6) | 59% (40) | 87% |
Geng 2008 | 829 | 128 (15%) | 13% (17) | 62% (79) | 25% (32) | 29% |
Deribe 2008 | 355 | 355 (100%) | 18% (65) | 61% (215) | 21% (75) | 27% |
An 2008# | 3528 | 1143 (32%) | 46% (522) | 43% (497) | 11% (124) | 20% |
Ive 2005 | n.r. | 74 (-) | 35% (26) | 30% (22) | 35% (26) | 54% |
Hochgesang 2006 | 1843 | 727 (39%) | 26% (189) | 44% (320) | 30% (218) | 41% |
Billy 2007 | 273 | 113 (41%) | 14% (16) | 55% (62) | 31% (35) | 36% |
Dahab 2008 | 44 | 44 (100%) | 20% (9) | 39% (17) | 41% (18) | 51% |
Dahab 2008$ | 53 | 53 (100%) | 23% (12) | 68% (36) | 9% (5) | 12% |
Lurton 2008 | 236 | 61 (26%) | 16% (10) | 43% (26) | 41% (25) | 49% |
Joshi 2008$ | 152 | 152 (100%) | 30% (46) | 61% (93) | 9% (13) | 12% |
Muwanga 2008 | 831 | 831 (100%) | 55% (459) | 26% (213) | 19% (159) | 43% |
McGuire 2009 | 1233 | 654 (53%) | 32% (206) | 31% (204) | 37% (244) | 54% |
Overall | 6420 (100%) | 37% | 38% | 25% | 40% | |
Patients on ART (excluding#) | 3934 | 34% | 38% | 28% | 42% | |
On ART, Africa, public programme, (excluding#, $) | 3729 | 34% | 37% | 29% | 46% |
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 increased from 5% to 50% (
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.
Seven studies
Reasons for not returning to the clinic among patients found alive were assessed in 11 studies, for 1096 (75%) of the 1464 surviving patients (
Study | % of patients interviewed (n) | Transfer out | Financial reasons | Improved health | Too sick to come to clinic | Stigma & social problems | Adverse effects of drugs | Other reasons |
Yu 2007 | 100% (58) | 35% | 22% | n.r. | n.r. | 7% | n.r. | 36% |
Maskew 2007 | 100% (51) | 12% | 47% | n.r. | n.r. | 8% | 2% | 31% |
Dalal 2008 | 100% (90) | 49% | 2% | 10% | 20% | n.r. | 6% | 13% |
Krebs 2008# | 63% (271) | n.r. | n.r. | 4% | 23% | 7% | n.r. | 67% |
Deribe 2008 | 79% (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 2007 | 97% (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 2008 | 92% (86) | 14% | 45% | 3% | n.r. | n.r. | 5% | 33% |
Muwanga 2008 | 100% (213) | 17% | n.r. | 26% | n.r. | n.r. | n.r. | 57% |
McGuire 2009 | 24% (49) | n.r. | n.r. | 20% | n.r. | 20% | 10% | 50% |
n.r.; not reported.
The cause of death was investigated for 128 deaths in three studies from Johannesburg, South Africa
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
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
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
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
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
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
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.
Search strategies
(0.05 MB DOC)
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.