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Risk factors for loss to follow-up from antiretroviral therapy programmes in low-income and middle-income countries

Frijters, Elise M.a,b; Hermans, Lucas E.a,c,d; Wensing, Annemarie M.J.a,c,d; Devillé, Walter L.J.M.e,d; Tempelman, Hugo A.c,d; De Wit, John B.F.f,g

Author Information
doi: 10.1097/QAD.0000000000002523



Over 19 million HIV-infected patients in low-income and middle-income countries (LMIC) are receiving antiretroviral therapy (ART) [1]. As part of the UNAIDS-defined 90–90–90 targets, treatment programmes are aiming to initiate 90% of HIV-infected patients on ART and to achieve treatment success in 90% of those who were initiated on ART by the year 2020 [2]. However, ART programs in LMIC are characterized by high rates of loss to follow-up (LTFU), up to 40% after 5 years of ART [3,4]. These LTFU rates present a serious risk to the concerted efforts to halt the HIV epidemic by attaining near-universal ART coverage.

Even though not all patients who become LTFU are truly lost to care, LTFU is associated with poor outcomes [5–7]. A meta-analysis on outcomes of adult patients after LTFU from ART programmes in LMIC found a combined summary estimate of 38.8% mortality, 28.6% treatment stop and 18.6% self-transfer [8].

Knowledge of risk factors for LTFU can contribute to individualized patient care and inform policy on a programmatic level. In recent years, a significant number of studies have revealed that a wide range of sociodemographic, clinical, behaviour-related and system-related determinants are independently associated with LTFU [9–18].

Despite the significant amount of individual studies on this topic, to date this evidence has not been consolidated and reviewed to assist clinicians and researchers in understanding the key determinants of LTFU. We set out to perform a systematic review and meta-analysis to identify risk factors for LTFU from ART in adults in LMIC.


This review has been conducted and reported according to the PRISMA guidelines. The study protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO) (registration number CRD42016047131).

Search strategy

A systematic search was conducted in PubMed, Embase, Psycinfo and Cochrane on the 1st of August 2019. The search strategy consisted of a combination of ‘HIV’, ‘ART’, ‘LTFU’ and ‘LMIC’ and their synonyms and the names of all LMICs as defined by the World Bank. For the full search strategy, see appendix 1, No date limits were implemented and no filters were used.

Eligibility criteria

All studies on adult HIV-positive patients (≥15 years old) that initiated ART in LMICs were subjected to inclusion and exclusion criteria. Studies were excluded if they only included specific patient populations or risk groups. Qualitative studies and case reports or series with less than 10 patients were excluded. Randomized controlled trials were excluded as these typically include nonstandard measures to improve retention, which may have influenced determinants of LTFU. Intervention studies were excluded. The remaining studies were included based on outcome definition and the potential risk factor(s). The LTFU outcome had to reflect nonretention for at least 28 days after a missed visit, excluding deceased patients and patients with a documented transfer. Potential risk factors had to be quantifiable, and reported in a multivariable analysis corrected for at least age and sex, either using an odds ratio or hazard ratio with 95% confidence interval (95% CI). All potential risk factors of LTFU that were reported in this manner were included.

Study selection

Search results were exported and deduplicated. Two researchers (E.M.F. and L.E.H.) independently performed title and abstract screening using a predefined list of inclusion and exclusion criteria (Fig. 1). Discrepant screening results were discussed between the two researchers. In cases where consensus on inclusion could not be reached, a third researcher (W.L.J.M.D.) made the final decision. Full-text screening was performed using an expanded list of inclusion and exclusion criteria (Fig. 1). During this round of screening, consensus on the reason for exclusion was also required. When different studies reported on the same cohort of patients, the study with the largest sample size or the most recent publication was included. Multiple studies of the same cohort were included if different predictor-outcome relationships were studied.

Fig. 1
Fig. 1:

Data extraction

Data was extracted using a standardized form. The following details were extracted: timeframe of study, study design, number of participants, participant selection, geographical setting, definition of the LTFU outcome, duration of follow-up, prevalence of the LTFU outcome, determinants studied and their effect measures for correlation and corresponding measures of significance from the multivariate analysis.

Quality assessment

For all included studies, a quality assessment was performed using the QUIPS (Quality in Prognostic Studies) tool applied to our research question (Appendix 2, For each element of this tool a high, moderate or low score was assigned to the studies, leading to an overall high, moderate or low risk of bias. For each meta-analysis, a sensitivity analysis was performed in which only studies with a moderate-to-low risk of bias were included.

Statistical analysis

Both odds ratios (OR) and hazard ratios were extracted. Meta-analysis was performed when at least five studies reported on a given determinant using a comparable definition. Pooled effect estimates and their 95% confidence intervals (CI) were calculated using random effect models with inverse variance weights. Results were presented as Forest Plots. Meta-analysis was performed using RevMan Version 5.3 (Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014). Subgroup analysis was performed for studies from within and outside of sub-Saharan Africa.


After removal of duplicates a total of 3708 articles were identified and screened on title and abstract, which yielded 529 articles that were eligible for full text screening. Data from 90 articles was extracted (Table 1       ); data from 80 articles could be included in one or more meta-analyses [19–107]. The reasons for exclusion are listed in Figure 1.

Table 1
Table 1:
Baseline characteristics of studies.
Table 1 (Continued)
Table 1 (Continued):
Baseline characteristics of studies.
Table 1 (Continued)
Table 1 (Continued):
Baseline characteristics of studies.
Table 1 (Continued)
Table 1 (Continued):
Baseline characteristics of studies.
Table 1 (Continued)
Table 1 (Continued):
Baseline characteristics of studies.
Table 1 (Continued)
Table 1 (Continued):
Baseline characteristics of studies.
Table 1 (Continued)
Table 1 (Continued):
Baseline characteristics of studies.
Table 1 (Continued)
Table 1 (Continued):
Baseline characteristics of studies.

Study characteristics

The eighty studies included described a total of 1 605 320 patients. Median sample size was 4466 patients (IQR: 1876–13 616, range: 346–306 355) per study. The majority of included studies (70/80) were conducted in SSA, with a total of 1 402 858 patients (87.3%). The remaining studies were conducted in China (n = 3), India (n = 2), South-East Asia (n = 3), Haiti (n = 1), and one in several Latin American countries (Table 1       ).

The percentage of patients identified as LTFU varied between 2.8 and 65.6%. Median or mean CD4+ T-lymphocyte count (CD4+ cell count) at ART initiation ranged from 82 to 375 cells/μl and in the vast majority of studies, median age was between 30 and 40 years. In studies from SSA, about two-thirds of the study participants were women. In all other studies, more than 60% were men.

Of the included studies, 78 were prospective or retrospective cohort studies and two were case–control studies. Data was collected between 2000 and 2018 and the year of publication ranged from 2008 to 2019. Follow-up duration varied from 3 to 90 months. Most studies (52/80) had a follow-up duration of between 6 and 24 months. All studies defined LTFU as being disengaged from care without subsequent return for a minimum period of time. In the majority of studies (52/80), this minimum period ranged from 30 to 90 days. The other 28 studies used a minimum period of 90 days or more.

Risk of bias

Of the 80 studies, 31 scored a low risk of bias, 40 a moderate risk of bias and nine a high risk of bias (Appendix 2, and 3, Most studies scored well on participant selection, study attrition and outcome measurement. Suboptimal scores were often present for prognostic factor measurement and study confounding. A sensitivity analysis excluding the studies with high risk of bias showed no significant difference of results (Appendix 4,


The included studies reported on 81 different determinants (Appendix 5, Twenty determinants were reported by five or more studies and for 17 of them, meta-analysis could be performed. As a result of inconsistent categorization between studies for haemoglobin level [28,30,39,41,43,68,84,89,102,108], alcohol use [21,36,40,52,77] and clinic size [20,27,29,39,45,64,91,102] no meta-analysis could be performed. Findings of the meta-analyses are presented below. Outcome data that could not be included in the meta-analyses can be found in Appendix 6,

Sociodemographic determinants

Studies frequently reported on associations between LTFU and sex (n = 66), age (n = 11), employment status (n = 6), relationship status (n = 16), and level of education (n = 11). All forest plots are shown in Fig. 2  . Male sex (hazard ratio 1.22; 95% CI 1.16–1.26), unemployment (hazard ratio 1.23; 95% CI 1.09–1.38) and not being in a stable relationship (hazard ratio 1.22; 95% CI 1.11–1.33 for single vs. married; see Fig. 2  d for other analyses) were all significantly associated with an increased risk of LTFU. Older age was associated with lower risk of LTFU with a hazard ratio of 0.98 (95% CI 0.98–0.99) for each year increase in age. A higher educational level was associated with a decreased risk of LTFU. The risk of LTFU decreased further as the level of education increased with hazard ratios of 0.89 (95% CI 0.80–0.98); 0.82 (95% CI 0.71–0.95) and 0.76 (95% CI 0.62–0.94) for, respectively primary, secondary and tertiary education as compared with no education (Fig. 2  c).

Fig. 2
Fig. 2:
Sociodemographic determinants.
Fig. 2 (Continued)
Fig. 2 (Continued):
Sociodemographic determinants.
Fig. 2 (Continued)
Fig. 2 (Continued):
Sociodemographic determinants.

Clinical determinants

Markers of health at start of treatment that have been studied in relation to LTFU include WHO stage (n = 38), weight (n = 15), functional status (n = 9), active infection with tuberculosis (n = 19), and CD4+ cell count (n = 23). Values indicative of poorer health, such as lower weight and worse functional status were generally associated with increased risk of LTFU. The hazard ratio for lower body mass index (BMI) (≤18.5 vs. >18.5) was 1.35 (95% CI 1.26–1.45) and for worse functional status 1.46 (95% CI 1.17–1.83) comparing bedridden and working patients and 1.28 (95% CI 1.13–1.45) for ambulatory vs. working (Fig. 3    b and c). Advanced WHO stage was significantly associated with higher risk of LTFU as shown by a hazard ratio of 1.27 (95% CI 1.08–1.49) for stage IV vs. I, hazard ratio 1.34 (95% CI 1.02–1.76) for stage IV vs. I/II and hazard ratio 1.25 (95% CI 1.16–1.34) for stage III/IV vs. I/II. No significant association was seen among less advanced WHO stages (Fig. 3    a). Infection with Mycobacterium tuberculosis was not significantly associated with LTFU (Fig. 3    d). There was considerable variation in the stratification of CD4+ cell count between studies. As a result, five separate meta-analyses were performed (CD4+ cell count ≤50 vs. 200–350/≤200 vs. >200/≤100 vs. >350/100–200 vs. >350/200–350 vs. >350) but none of them revealed significant associations with LTFU (Fig. 3    e).

Fig. 3
Fig. 3:
Clinical determinants.
Fig. 3 (Continued)
Fig. 3 (Continued):
Clinical determinants.
Fig. 3 (Continued)
Fig. 3 (Continued):
Clinical determinants.
Fig. 3 (Continued)
Fig. 3 (Continued):
Clinical determinants.
Fig. 3 (Continued)
Fig. 3 (Continued):
Clinical determinants.

Behaviour-related determinants

Several studies reported on factors related to patient behaviour, namely adherence to ART (n = 6) and disclosure of HIV-positive status to others (n = 8). Both nonadherence and nondisclosure were significantly associated with strongly increased risk of LTFU with a hazard ratio of 3.13 (95% CI 1.81–5.39) and a hazard ratio of 1.64 (95% CI 1.24–2.16) respectively (Fig. 4).

Fig. 4
Fig. 4:
Behaviour-related determinants.

Treatment-related determinants

The relationship between the composition of the initial ART regimen and LTFU has been examined in several studies. The nucleos(t)ide reverse transcriptase inhibitors (NRTIs) stavudine, zidovudine and tenofovir (n = 11) and the non-NRTIs nevirapine and efavirenz were compared (n = 9). No significant association was found between LTFU and prescription of any of these drugs (Fig. 5a). Six studies examined the impact of prophylactic treatment with trimethroprim/sulfamethoxazole on LTFU. In meta-analysis not being prescribed prophylaxis, while being eligible for it, was associated with a higher risk of LTFU (hazard ratio 1.24; 95% CI 1.09–1.40) (Fig. 5b).

Fig. 5
Fig. 5:
Treatment-related determinants.

System level determinants

Various aspects of health infrastructure have been studied in relation to LTFU. Even though 33 studies reported on the association between calendar year of initiation and LTFU, only six studies reported on this variable on a continuous scale. Meta-analysis of these six studies revealed that patients starting treatment in more recent years were at increased risk of LTFU (hazard ratio 1.21; 95% CI 1.10–1.32) (Fig. 6a). Studies did not correct for longer follow-up time for patients who were initiated in earlier years. Results from the other studies can be found in Appendix 6, Seven studies compared receiving ART at a primary health centre as opposed to a hospital, and showed a lower associated risk of LTFU (hazard ratio 0.69; 95% CI 0.52–0.92) for the primary health centre (Fig. 6b). Studies did usually not correct for baseline clinical condition. Geographical setting (urban vs. rural) was not significantly associated with LTFU (Fig. 6c).

Fig. 6
Fig. 6:
System level determinants.

Subgroup analysis

Subgroup analyses were performed for studies from SSA and studies from non-SSA countries. Per determinant, subgroup analysis was performed if at least three studies per subgroup reported data on the determinant (Appendix 4, In both subgroups, male sex was a risk factor for LTFU, but a stronger relationship was seen in SSA than in the non-SSA countries (hazard ratio 1.22; 95% CI 1.18–1.27 and hazard ratio 1.08; 95% CI 1.03–1.12, respectively). Being divorced as opposed to married was a significant risk factor for LTFU in non-SSA countries (hazard ratio 1.29; 95% CI 1.19–1.39) but nonsignificant in SSA (hazard ratio 1.06; 95% CI 0.96–1.18). For tuberculosis and treatment regimen, no outcome difference was observed between the subgroups.


This systematic review and meta-analysis combines the available evidence from a large amount of studies to identify risk factors for LTFU in adult HIV-infected patients initiating ART in LMIC. To our knowledge, this is the first aggregated presentation of risk factors for LTFU in adults. Meta-analyses of 80 studies revealed that vulnerable patient groups in terms of socioeconomic status, clinical condition and social support are at increased risk of LTFU from ART programs. Individual patient-related risk factors associated with a significantly increased risk of LTFU were male sex, younger age, lower educational level, being single, unemployment, advanced WHO stage, low weight, worse functional status, poor adherence, and nondisclosure of HIV-positive status. This large array of risk factors highlights that the underlying cause of becoming LTFU is multifactorial.

The sociodemographic and economic risk factors identified may represent barriers to effective participation in treatment programmes. This has been highlighted by other work that shows that many of these same determinants are associated with adverse treatment outcomes, such as lower likelihood of viral load suppression, higher risk of disengaging from care prior to ART initiation and lower adherence to treatment [109–113]. Also in qualitative studies, sociodemographic and economic factors, along with stigma and difficulty accessing health care, are among the most frequently patient-mentioned reasons to discontinue care [101,105]. Our limited subgroup analyses suggest that these risk factors might be locally determined. Male sex showed a stronger relationship with LTFU in SSA than non-SSA countries. The proportion of male individuals included in the studies is also lower in SSA. This might reflect certain sex-related patterns of health-seeking behaviour but could also indicate that services are not well enough suited for men leading to lower inclusion and higher LTFU.

Clinical risk factors for LTFU were universally indicative of poor health status. Poor health is associated with increased risk of mortality in different settings [114–116]. Although all included studies differentiated between LTFU and death, LTFU may still partly be attributable to undocumented mortality. It is likely that the increased risk of LTFU observed in patients with poor health is because of a higher likelihood of death, and that in some cases, this leads to incorrect classification as LTFU. However, there are several other explanations. Access to public health treatment programmes may be compromised for severely ill patients because of financial concerns or inability to travel. Poor health status could also be a reflection of an overall disadvantaged socioeconomic status, or of preexisting barriers to access to healthcare, which are not resolved after initiation of ART and may lead to higher incidence of LTFU over time. Lastly severe illness may be the result of previous disengagement from care, and may therefore be associated with a higher risk of becoming LTFU again. Investing in early diagnosis and linkage to care could mitigate the observed increased risk of LTFU. More research is needed to identify the drivers of late presentation as well as the causes of LTFU in patients with advanced illness.

The association between LTFU and nonadherence to ART and nondisclosure of HIV-positive status is intuitively clear, and is likely to reflect behavioural patterns that are not conducive to successful participation in chronic treatment programmes. These behavioural factors may be the result of societal pressures exerted on patients, such as stigma or related (sex-based) violence [117,118]. In meta-analysis, behavioural factors induced far stronger increases in the risk of LTFU than most other risk factors. This finding is of significant importance, as behavioural risk factors are typically modifiable.

Knowledge of patient-level risk factors for LTFU enables healthcare workers to identify at-risk patients and forms the basis for the development of successful interventions. On the basis of these data, we recommend that patients initiating ART be screened for risk factors for LTFU. If one or more risk factors are present, they should be prioritized for retention interventions. Ideally, an easily applicable risk score is developed [119,120]. Also, an effort should be made to identify underlying patterns or reasons for LTFU in the risk groups identified by this article to tailor interventions to their specific needs. The transition in LMICs towards a more individualistic society, the growing mobility and resulting instability in people's lives may lead to more LTFU as illustrated by our findings of associations between LTFU and young age, single status and unemployment. Services targeting men, adolescents, and mobile populations need to be developed. Furthermore, efforts to improve education on treatment benefits and to take away economical and other structural barriers to accessing ART care need to be strengthened. In settings with severe shortage of resources, if decisions need to be made on who to prioritize for start of ART treatment, the risk factors of LTFU identified here could be taken into account [121].

The results of our meta-analysis of treatment-related determinants should be interpreted carefully. We identified a relationship between LTFU and not receiving co-trimoxazole prophylaxis while being eligible for it. The underlying mechanism for this association is unclear and could merely be a marker for poor clinic management or lack of resources. No effect of treatment regimen on LTFU was seen. As standard treatment regimens have changed over the course of time, we believe this finding is potentially confounded by various system-level developments in treatment programs over time.

On the system-level, two risk factors for LTFU were detected. The higher rates of LTFU in patients who initiated ART in more recent years is an alarming finding, especially in light of the current test and treat guidelines and expansion of ART. Other analyses of LTFU rates over time have revealed similar trends in LMIC [4] and more specifically in SSA [122]. This trend of increasing LTFU figures could be a result of several underlying mechanisms. First of all, it might result from a possible underlying association between prolonged duration of treatment and decreasing risk of LTFU. Secondly, the initiation on ART of relatively healthy patients at higher CD4+ cell counts in recent years may have led to increased LTFU as the perceived benefits of treatment may not outweigh possible side effects and structural barriers for these patients. In this review, no association between high CD4+ cell counts and LTFU was found, although the amount of data on LTFU in patients with high CD4+ cell counts at initiation of treatment was limited because of the relatively recent introduction of universal treatment in most LMICs. Another possible explanation is that the rapid expansion of treatment programmes in recent years may have constrained efforts to trace back individual patients who have become LTFU. Lastly increased numbers of treatment sites and introduction of out-of-clinic medication collection may have led to higher rates of silent transfers between clinics resulting in higher LTFU figures at individual sites.

Receiving care at a higher level was also associated with increased risk of LTFU. This may be a reflection of centralized initiation of ART and treatment of accompanying conditions, after which patients are referred to decentralized care settings. In this process, patients may become lost. In addition, patients at higher levels of care are likely to require more complex management and be at a higher risk of mortality. As shown before, poor clinical condition in itself is associated with increased risk of LTFU. Lastly, the mostly urban location of secondary care facilities and the associated higher patient mobility could play a role in this process.

Strengths of this review include the systematic approach and comprehensive search terms and inclusion criteria. Included data originates from a wide variety of LMICs in various settings, both urban and rural and from primary to tertiary care level. Various sensitivity analyses were performed to confirm the robustness of the primary findings.

This study also has limitations. The varying definitions of LTFU and follow-up duration of the included studies limits comparability of data and puts emphasis on determinants responsible for relatively ‘early’ LTFU (even though the majority of studies had follow-up times beyond 12 months). The limited number of studies from areas outside of SSA limits the generalizability to other geographic areas. We have sought to address this by performing subgroup analyses in non-SSA countries. Outcomes after LTFU are diverse and this may have influenced the findings of this study. The likely presence of unreported death and silent transfers among LTFU patients might have introduced heterogeneity in the results.

We, therefore, suggest that further research is done differentiating between the several outcomes after LTFU. We expect that patients defaulting treatment might have different risk profiles from those re-engaging in care. Although in many programmes a commendable effort is being made to ascertain final patient outcomes after LTFU, this tracing of LTFU patients is a costly intervention with limited rate of success [123]. Implementation of countrywide reporting systems and unique patient identifiers is of key importance to discriminate between undocumented mortality, silent transfer and actual treatment default. Data from recent studies demonstrate a downward trend in mortality after LTFU between 2003 and 2013 [123–125]. This decreased mortality signifies an improvement of individual patient health after LTFU, but is accompanied by corresponding higher figures of transfer and default. Self-transfer to another facility is often preceded by treatment interruption that may have treatment consequences [126]. An increase in patients defaulting treatment poses a major public health challenge as these patients will become viremic and may contribute to onward spread of HIV. Therefore, addressing LTFU, in all its forms, remains a relevant challenge in halting the HIV epidemic.


This study is the first systematic review and meta-analysis identifying risk factors for LTFU in the general adult population in LMIC. Its findings can be used to develop tools to identify high-risk patients to better target retention interventions.


All authors were responsible for study design and contributed to the interpretation of findings and final manuscript. E.M.F., L.E.H. and W.L.J.M.D. were responsible for search and article screening. E.M.F. was responsible for data extraction and preliminary analysis. E.M.F. and L.E.H. were responsible for creation of tables and figures. J.E.F.DeW. was responsible for the oversight of the process.

Conflicts of interest

There are no conflicts of interest.


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