Messou, Eugène MD, PhD*†‡; Kouakou, Martial MD†; Gabillard, Delphine MSc*§; Gouessé, Patrice MD†; Koné, Mamadou MSc†; Tchehy, Amah MSc†; Losina, Elena PhD‡; Freedberg, Kenneth A MD, MSc‡; dri-Yoman, Thérèse N' MD*†; Anzian, Amani MD*†; Toure, Siaka MD, PhD*†; Anglaret, Xavier MD, PhD*§
Over the past 6 years, 3 million HIV-infected adults have started antiretroviral therapy (ART) in sub-Saharan Africa.1 This unprecedented scaling up has been successful not only in saving lives but also in building capacity and allowing people to acquire experience in how to implement large treatment programs.2
Successful ART programs require providing lifelong treatment. A critical issue is how to help people maintain treatment over the long term. Reports from ART programs across sub-Saharan Africa have consistently shown that a substantial proportion of patients who initiate ART are then lost to follow-up (LTFU).3-5 Some of these patients died,6-10 although others are alive but have withdrawn from care for various reasons.6,11,12 Preventing the latter from stopping treatment or getting them back into care once they have stopped is an important priority for ART programs.1
Even if there is wide variation in reported rates of LTFU,13,14 some factors associated with LTFU have been consistently reported.6,7,11,12,15,16 However, it is not easy to draw lessons, predict and identify which intervention should be implemented to decrease rates of LTFU in a specific setting.17
The objective of this study was to assess whether simple enhanced follow-up procedures decreased LTFU rates in a large HIV care clinic in Côte d'Ivoire. A secondary objective was to examine factors associated with LTFU from month-6 to month-18 in this clinic and determine whether some of them might help identify patients at month-6 for subsequent intervention(s) to prevent further LTFU.
The CePReF clinic is the HIV care reference center of the Aconda program in Abidjan, Côte d'Ivoire.18,19 All patients who started ART at the CePReF clinic between June 6, 2005, and May 1, 2008, and attended their 6-month follow-up visit were eligible for the study.
Standard Care and Treatment
The standard of care for HIV-infected adults on ART in the Aconda program has been described elsewhere.19 During the study period, all patients initiated ART according to World Health Organization (WHO) criteria.20 When patients were HIV-1 infected, first-line ART consisted of 2 nucleoside reverse transcriptase inhibitors and 1 nonnucleoside reverse transcriptase inhibitor. When they were HIV-2 or HIV-1 and HIV-2 dually reactive, first-line ART consisted of 2 NRTIs and 1 protease inhibitor. CD4 counts and complete blood counts were measured every 6 months. Patients paid a fixed rate of US $2 per month for antiretroviral drugs and laboratory tests until August 2008, when the national HIV program made them available free of charge for patients. A team of 6 persons, including 3 social workers and 3 counselors, organized support groups to encourage patients to adhere to therapy21 and made telephone calls or home visits when patients did not show up to pick up their antiretroviral drugs.12,22
Computerized Data Recording System
Standardized forms were used to record the following variables at routine visits: (1) “initial visit”: date, sex, date of birth (or age), height, weight, HIV type (HIV-1, HIV-2, or both); (2) “follow-up visit”: date, weight; (3) “ART initiation visit”: date, WHO clinical stage, weight, patient's home location; (4) “drug prescription (antiretroviral or other)”: date, name, and quantity of drugs delivered; (5) “CD4 count and complete blood count measurement”: date, CD4 count, CD4 percentage, hemoglobin level, and platelet, granulocyte, and leukocyte counts; (6) “telephone call and home visit”: dates at which patients were contacted, and vital status on that date; (7) “patients known to have died”: date of death.
In June 2005, we launched a prospective cohort study (VOLTART cohort) of long-term virologic outcomes on ART in 3 HIV outpatient clinics in Abidjan, including the CePReF clinic.18 HIV-infected adults who started ART between June 6, 2005, and May 1, 2007, and attended their 6-month visit were eligible for the cohort. Participants in VOLTART received the same standard care and treatment as other HIV-infected patients on ART. In addition, they received free plasma HIV-1 RNA every 6 months, a research physician was devoted to specifically attend the patients included in the cohort, and a research coordinator was devoted to monitoring and managing the cohort data and helping track patients by telephone and/or home visit.
In this study, we compare outcomes at month-18 in patients who participated in the VOLTART cohort (enhanced follow-up) and in those who attended their 6-month follow-up visit and received treatment at the CePReF clinic outside the framework of the cohort (routine follow-up). Outcomes were death, transfer of care, and LTFU.
Patients were defined as LTFU between month-6 and month-18 if (1) their last contact with study team was before month 18; (2) they were not known to be dead or transferred out between month-6 and month-18; (3) no further information on their vital status could be obtained between month-18 and month-24, or they were found to be dead or transferred out between month-18 and month-24 and their date of death or date of transfer was more than 6 months after the date of their last contact with the study team.
The medication possession ratio (MPR) was defined as the number of daily doses of antiretroviral drugs dispensed by the pharmacy to each patient, divided by the patient's total follow-up time in days since ART initiation.
Time to follow-up during the period of observation between routine and enhanced follow-up was compared by using time-to-first-event analyses, including Kaplan-Meier estimates and log-rank testing.
We used Cox proportional hazard regression analysis to estimate the association between the probability of being LTFU between month-6 and month-18 and sex, age, ART regimen, pre-ART CD4 count, pre-ART body mass index, distance living from the clinic, type of follow-up, and the MPR between ART start and month-6 (M0-M6 MPR). Analyses were performed with SAS software, version 9.1 (SAS institute Inc. Cary, NC).
Overall, 2074 adults started ART at the CePReF clinic during the study period. After 6 months on ART, 1636 patients (78.9%) were still alive and in care. Of these, 637 were included in the VOLTART cohort (enhanced group) and 999 were followed under standard conditions (routine group) (Fig. 1).
Withdrawal From Care Before Month-6
Patients who withdrew from care before month-6 had lower pre-ART CD4 count (P < 0.001), lower body mass index (P < 0.001), and were more likely to be male (P < 0.001) than patients still in care at month-6 (Table 1). Among patients who started ART during the study period, 7.8% died, 11.6% were LTFU, and 1.8% transferred care to another center before month-6. These outcomes did not change significantly over calendar time. The rate of death at month-6 was 8.5% in the February 2006 to April 2007 period and 6.1% in the May 2007 to May 2008 period (P = 0.06). The rate of LTFU at month-6 was 11.1% in the February 2006 to April 2007 period and 12.6% in the May 2007 to May 2008 period (P = 0.34).
Outcomes From Month-6 to Month-18
Pre-ART characteristics and M0-M6 MPR were similar in patients from the enhanced and routine groups (Table 1).
Between month-6 and month-18, patients in the enhanced and routine groups had similar rates of death (3.9% vs. 3.6%, P = 0.74) and transfer out (1.7% vs. 3.0%, P = 0.11), although patients from the enhanced group were less likely to be LTFU than those in the routine group (5.8% vs. 11.3%, P < 0.001) (Fig. 1).
In multivariate analysis, the probability of LTFU was lower in the enhanced group, in patients living within the boundaries of the district centered on the clinic, and in those with higher M0-M6 MPR (Table 2). Patients in the enhanced group had a 46% decrease in the risk of being LTFU from month-6 to month-18 (hazard ratio: 0.54; confidence interval: 0.37 to 0.78), those living outside the study center area had a 53% increase in the risk of being LTFU from month-6 to month-18 (hazard ratio: 1.53; CI: 1.10 to 2.13), and those having a M0-M6 MPR at 80%-94%, 50%-79%, and <50% had a 1.5-fold, 4.0-fold, and 5.7-fold increase in the risk of being LTFU from month-6 to month-18 compared with those having a M0-M6 MPR ≥95%. The probability of being LTFU between month-6 and month-18 was 12% in the routine and 6% in the enhanced groups (Fig. 2). The probability of being LTFU between month-6 and month-18 was 5%, 7%, 19%, and 30% in patients with M0-M6 MPR ≥95%, 80%-94%, 50%-79%, and <50% (Fig. 3).
We did not find a significant association between LTFU and sex, age, or pre-ART CD4 counts.
We conducted a prospective cohort study nested in a large HIV care programs in Abidjan, Côte d'Ivoire. In this program, during the first year of the study period, adult patients who had received ART for 6 months and remained in care were offered participation in the cohort study on the day of their 6-month visit. Cohort participants received the same care and treatment as nonparticipants and had the same follow-up routine monitoring procedures, which included monthly visits, CD4 counts every 6 months, and home visits or phone calls when they did not show up to pick up their drugs. However, from 6 months onward, follow-up of participants was enhanced in 2 ways as follows: first, participants had plasma HIV-1 RNA measured at 6 months, and then every 6 months thereafter; second, a dedicated team of 2 persons enhanced their follow-up. A physician was devoted to attend to patients included in the cohort whenever they showed up for their monthly visits; and a research assistant was devoted to following the cohort participants' data and ensuring that those who missed a pharmacy refill were tracked by telephone and/or home visit. Of note, participants in the cohort, and nonparticipants, had to pay for their transportation, for all care and treatment other than ARV drugs, and for all tests other than those included in routine monitoring.
We compared 18-month outcomes of participants and nonparticipants in the cohort and had 2 main findings.
First, reinforcing follow-up beginning at month-6 was independently associated with a 47% decrease in the risk of LTFU between month-6 and month-18. It has been shown previously that patients participating in research studies have better outcomes compared with those treated in routine programs, including lower mortality and lower rate of LTFU. However, this cohort was not a typical research study, in the sense that participants had the same standard of care as nonparticipants. In what is usually known as the “cohort effect”, free transportation, free care, including drugs and tests, more frequent scheduled visits, and specific cohort-associated procedures to track LTFU, are often thought to explain why cohort participants have better outcomes than patients followed in routine programs.9 In this study, cohort participants had none of these advantages compared with nonparticipants. There are 3 potential reasons why they were less likely to be LTFU. First, measuring viral load every 6 months could decrease the rate of LTFU in the year after the first measurement. If this is true, one would expect viral load measurement to also decrease mortality, which we did not observe. Second, being consistently attended to by the same physician could encourage patients to remain in care. Third, a dedicated research assistant for each 600 patients could optimize tracking procedures, even in a care center where a team of 6 persons is already routinely in charge of making sure these procedures are applied.
The second key finding of the study is that the MPR during the first 6 months of ART was strongly associated with the risk of LTFU from month-6 to month-18 in patients who were in care at month-6, in both the routine and enhanced groups also show elsewhere.23 In our center, procedures to reinforce adherence at 6 months in patients who are believed to be nonadherent are already in place. Some of the study patients who had low MPR probably benefited from these procedures. However, at the time of the study, the MPR was not explicitly identified as a tool to predict the short-term risk of being LTFU. This strongly suggests that the MPR at month-6 can be used to identify those at highest risk of LTFU and develop specific interventions to improve their retention.24,25
This study has several limitations. First, patients were not randomly assigned to routine or enhanced follow-up; these were offered to them on a calendar time basis. Therefore, we cannot rule out changes over time in the way patients were followed in this HIV care center.2 However, the outcomes during the first 6 months of ART did not change over calendar time during the study period and neither did the 6-18 months rates of death and of patient transfer. It is unlikely, therefore, that a change in study center characteristics over that time explains the 47% decrease in the rate of LTFU. Second, the number of variables included in the analysis was limited. Some variables not recorded might have acted as confounders in the analysis, even if patients in the routine and enhanced groups were similar in terms of measured characteristics. Because we adjusted the analysis for age, sex, ART regimen, pre-ART CD4 count, home location, and MPR during the first 6 months, we believe that major confounding was controlled for.
In HIV-infected adults alive and in care after 6 months of ART, the MPR can be used routinely at month-6 to identify patients who may benefit most from follow-up reinforcement. Furthermore, additional simple follow-up enhancement procedures halved the risk of LTFU from month-6 to month-18.
2. Boulle A, Van Cutsem G, Hilderbrand K, et al. Seven-year experience of a primary care antiretroviral treatment programme in Khayelitsha, South Africa. AIDS. 2010;24:563-572.
3. Brinkhof MW, Dabis F, Myer L, et al. Early loss of HIV-infected patients on potent antiretroviral therapy programmes in lower-income countries. Bull World Health Organ. 2008;86:559-567.
4. Mutevedzi PC, Lessells RJ, Heller T, et al. Scale-up of a decentralized HIV treatment programme in rural KwaZulu-Natal, South Africa: does rapid expansion affect patient outcomes? Bull World Health Organ. 2010;88:593-600.
5. Ekouevi DK, Balestre E, Ba-Gomis FO, et al. Low retention of HIV-infected patients on antiretroviral therapy in 11 clinical centres in West Africa. Trop Med Int Health. 2010;15(suppl 1):34-42.
6. Yu JK, Chen SC, Wang KY, et al. True outcomes for patients on antiretroviral therapy who are “lost to follow-up” in Malawi. Bull World Health Organ. 2007;85:550-554.
7. 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;47:101-107.
8. Bisson GP, Gaolathe T, Gross R, et al. Overestimates of survival after HAART: implications for global scale-up efforts. PLoS One. 2008;3:e1725.
9. Anglaret X, Toure S, Gourvellec G, et al. Impact of vital status investigation procedures on estimates of survival in cohorts of HIV-infected patients from Sub-Saharan Africa. J Acquir Immune Defic Syndr. 2004;35:320-323.
10. Geng EH, Glidden DV, Emenyonu N, et al. Tracking a sample of patients lost to follow-up has a major impact on understanding determinants of survival in HIV-infected patients on antiretroviral therapy in Africa. Trop Med Int Health. 2010;15(suppl 1):63-69.
11. Maskew M, MacPhail P, Menezes C, et al. Lost to follow up: contributing factors and challenges in South African patients on antiretroviral therapy. S Afr Med J. 2007;97:853-857.
12. Weigel R, Hochgesang M, Brinkhof M, et al. Outcomes and associated risk factors of patients traced after being lost to follow-up from antiretroviral treatment in Lilongwe, Malawi. BMC Infect Dis. 2011;11:31. E-pub ahead of print.
13. Rosen S, Fox MP, Gill CJ. Patient retention in antiretroviral therapy programs in Sub-Saharan Africa: a systematic review. PLoS Med. 2007;4:1691-1701.
14. Fox MP, Rosen S. Patient retention in antiretroviral therapy programs up to three years on treatment in sub-Saharan Africa, 2007-2009: systematic review. Trop Med Int Health. 2010;15(suppl 1):1-15.
15. Karcher H, Omondi A, Odera J, et al. Risk factors for treatment denial and loss to follow-up in an antiretroviral treatment cohort in Kenya. Trop Med Int Health. 2007;12:687-694.
16. Ochieng-Ooko V, Ochieng D, Sidle JE, et al. Influence of gender on loss to follow-up in a large HIV treatment programme in western Kenya. Bull World Health Organ. 2010;88:681-688.
17. Losina E, Toure H, Uhler LM, et al. Cost-effectiveness of preventing loss to follow-up in HIV treatment programs: a Cote d'Ivoire appraisal. PLoS Med. 2009;6:e1000173.
18. Messou E, Chaix M, Gabillard D, et al. Association between medication possession ratio, virologic failure and drug resistance in HIV-1 infected adults on antiretroviral therapy in Côte d'Ivoire. J Acquir Immune Defic Syndr. 2011;56:356-364.
19. Messou E, Anglaret X, Duvignac J, et al. Antiretroviral treatment changes in adults from Cote d'Ivoire: the roles of tuberculosis and pregnancy. AIDS. 2010;24:93-99.
21. Decroo T, Telfer B, Biot M, et al. Distribution of antiretroviral treatment through self-forming groups of patients in Tete province, Mozambique. J Acquir Immune Defic Syndr. 2011;56:e39-e44.
22. Toure S, Kouadio B, Seyler C, et al. Rapid scaling-up of antiretroviral therapy in 10,000 adults in Cote d'Ivoire: 2-year outcomes and determinants. AIDS. 2008;22:873-882.
23. Palombi L, Marazzi MC, Guidotti G, et al. 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. Clin Infect Dis. 2009;48:115-122.
24. Bisson GP, Gross R, Bellamy S, et al. Pharmacy refill adherence compared with CD4 count changes for monitoring HIV-infected adults on antiretroviral therapy. PLoS Med. 2008;5:e109.
25. McMahon J, Jordan M, Kelley K, et al. Pharmacy adherence measures to assess adherence to antiretroviral therapy: review of the literature and implications for treatment monitoring. Clin Infect Dis. 2011;52:493-506.
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