JAIDS Journal of Acquired Immune Deficiency Syndromes:
Epidemiology and Prevention
CD4-Specific Mortality Rates Among HIV-Infected Adults With High CD4 Counts and No Antiretroviral Treatment in West Africa
Lewden, Charlotte MD, PhD*,†; Gabillard, Delphine MSc*,†; Minga, Albert MD†,‡; Ekouévi, Didier K. MD, PhD*,†,‡; Avit, Divine MD§; Konate, Issouf MD‖; Amani-Bossé, Clarisse MD§; Messou, Eugène MD, PhD‡; Coffie, Patrick MD†,‡; Ouedraogo, Abdoulaye MD‖; Laurent, Christian PhD¶; Anglaret, Xavier MD, PhD*,†,‡; the ANRS 12222 MorbidityMortality Study Group
*INSERM, U897, Bordeaux, France
†Université Bordeaux Segalen, ISPED, Bordeaux, France
‡Programme PACCI, Abidjan, Côte d'Ivoire
§Programme MTCT-Plus, ACONDA, Abidjan, Côte d'Ivoire
‖Centre Muraz, Bobo-Dioulasso, Burkina Faso
¶Institut de Recherche pour le Développement (IRD), Université Montpellier 1, UMI 233, Montpellier, France
Correspondence to: Charlotte Lewden, MD, PhD, Inserm U897, ISPED, Université Bordeaux Segalen, 146 rue Léo-Saignat 33076 Bordeaux cedex, France (e-mail: email@example.com).
The ANRS 12222 Morbidity/Mortality Study Group is funded by the French National Agency for Research on Aids and Viral Hepatitis (ANRS). Grants ANRS 12222.
This data was presented at the 5th AFRAVIH, March 28–31, 2010, Maroc; at the 14th Workshop on HIV Observational Databases, March 25–27, 2010, Sitges, Spain; and at the 6th IAS Conference on HIV Pathogenesis, Treatment, and Prevention, July 17–20, 2011, Rome, Italy (abstract # 2509).
The authors X.A., D.G., C.Le., and C.La. developed the analysis plan, to which all authors then contributed. D.G. performed statistical analyses. All authors contributed to interpretation of the data. C.Le. and X.A. wrote the report, to which all authors then contributed. D.G., C.Le. and X.A. had full access to all the data in the study and had final responsibility for the decision to submit for publication.
The members of the ANRS 12222 Morbidity/Mortality Study Group are listed in Appendix I.
The authors have no conflicts of interest to disclose.
Received July 18, 2011
Accepted September 30, 2011
Background: CD4-specific rates of mortality in sub-Saharan African adults with high CD4 counts have rarely been estimated. This estimation is useful to the when to start antiretroviral treatment (ART) debate.
Methods: We pooled data from National Agency for Research on AIDS and Viral Hepatitis (ANRS)–funded research cohorts or associated partners in West Africa. All HIV-infected adults (≥18 years) with available follow-up time off ART were eligible. We used a joint model to estimate CD4 count evolution. We estimated CD4-specific rates of mortality, loss-to-follow-up (LTFU) and ART initiation by dividing the number of first event by the follow-up time off ART within each CD4 category.
Results: Between 1996 and 2009, 2588 adults (80% women) from 5 cohorts in Cote d'Ivoire and Burkina Faso were followed off ART during 6862 person-years. In the 201–350, 351–500, 501–650, and >650 cells per cubic millimeter CD4 categories, mortality rates were: 3.0, 1.5, 0.4, 0.2 per 100 person-years; LTFU rates: 6.0, 4.6, 6.1, 6.0 per 100 person-years; and ART initiation rates: 18.1, 2.7, 0.5, 0.5 per 100 person-years, respectively. All estimates varied across cohorts; mortality rates were higher when rates of LFTU and ART initiation were lower; LTFU rates were 2–40 times higher than mortality rates.
Conclusions: Among untreated West African adults with high CD4 counts, mortality and LTFU rates were substantial. Even when data are collected under research conditions, informative censoring due to ART initiation and LTFU could lead to significantly underestimate mortality figures.
The absolute number of CD4+ cells per cubic millimeter (CD4 count) is the most common marker of disease progression in HIV-infected adults1 with a lower CD4 count predicting a higher frequency of severe morbidity and mortality.2 It is recommended to start patients on antiretroviral treatment (ART) before they reach a CD4 threshold under which their risk of mortality is significantly increased. It is now admitted that a CD4 count of 350 cells per cubic millimeter is the minimal threshold to recommend ART initiation worldwide.3,4 However, recent data from Africa and Thailand strengthen the case in favor of earlier initiation of ART,5 some national guidelines recommend starting ART at 500 CD4 cells per cubic millimeter,6 and randomized trials are currently assessing the benefits and risks of initiating ART in patients with more than 500 CD4 cells per cubic millimeter.7,8 It is still unclear whether there is a universal CD4 threshold to be applied in all settings and all patients or whether “when to start ART?” is a context-driven question.9–11
The rationale for raising the question of “should we start ART at higher CD4 counts than currently recommended?” is based on 3 hypotheses. First, that the short-term risk of mortality or severe morbidity is higher in HIV-infected patients with high CD4 counts than in HIV-negative patients; second, that the short-term risk of mortality or severe morbidity increases with decreasing CD4 counts, even at high CD4 counts; and third, that controlling viral load earlier could prevent some HIV-related diseases in the long term. The 2 former hypotheses can be explored by estimating CD4-specific rates of mortality in cohort studies of patients with high CD4 counts. The latter hypothesis can only be addressed through randomized trials with long-term follow-up.
In Europe and in North America, mortality rates in patients with high CD4 counts have been repeatedly estimated in large cohort collaborations.10,12–15 In sub-Saharan Africa, cohort studies providing estimates in individuals without ART and with high CD4 counts are scarce.16,17
In this study, we pooled data from longitudinal studies funded by the National Agency for Research on AIDS and Viral Hepatitis (ANRS, France) or associated partners in West Africa. Our aim was to estimate CD4-specific rates of mortality in untreated adults with high CD4 counts.
Research studies sponsored by the ANRS or associated partners in resource-limited countries were eligible if the study procedures included (1) repeated CD4 counts; (2) a follow-up period without ART; and (3) an active strategy to retain patients.
Within eligible studies, patients were included in this analysis if: (1) they were aged ≥18 years at enrollment; (2) they had at least 1 CD4 measurement available; and (3) they were followed at least 1 day off ART.
Procedures and Definitions
In all participating studies, transport to the clinic, visits, drugs, hospitalizations, and biological or radiological tests were free of charge for patients. All studies included the following procedures: scheduled visits, ranging from every 3 months to every 6 months; CD4 counts at inclusion and every 6 months thereafter; active strategies to contact patients who did not show up for a scheduled visit (including phone calls, home visits and hospital records); standardized definitions and procedures to document follow-up events; and ART initiation, and standardized data collection. All study protocols had been approved by national ethics committees or institutional review boards.
Patients were defined as loss-to-follow-up (LTFU) if their last contact was more than 6 months before the database cut-off for this study, if they had not started ART before their last contact and if they were not known to be dead.
For the present analysis, the date of inclusion of patients was the date of first contact reported in the database. Data were censored at the date of the first event among the following: last contact with the study team, death, ART initiation, or database cut-off date for this study.
We considered the following CD4 strata: 201–350, 351–500, 501–650, and >650 cells per cubic millimeter. The rationale for breaking down the >650 cells per cubic millimeter stratum into 2 strata, 501–650 and >650 cells per cubic millimeter was based on the assumption that the short-term risk of mortality could decrease with increasing CD4 counts, even at very high CD4 counts, and that this could be especially true in low-resource settings were major causes of HIV-related severe morbidity are common community infections (eg, tuberculosis).17
To determine the time spent in a given CD4 stratum, we estimated the CD4 evolution at individual level by jointly modelling the correlation between repeated measures in each subject through a linear mixed model and the time to drop out through a survival model. We were thus able to adjust inferences on longitudinal measurements in the presence of nonignorable missing values.18,19 The linear mixed model had 2 random effects (intercept and slope), adjusted on participating study, gender and baseline CD4 count (<200, 200–350, 351–500, >500/mm3). The underlying assumptions were verified by graphically studying model residuals. The time-to-drop-out analyses were based on an exponential model, adjusted on participating study and baseline CD4 count (<200, 200–350, 351–500, >500/mm3). CD4 counts evolution and time-to-drop-out were linked by 2 random effects parameters (random intercept and random slope). The joint model was performed using the NLMIXED procedure of the SAS software, version 9.1 (SAS institute Inc, Cary, NC).
We estimated CD4-specific rates of mortality, LTFU, and ART initiation per 100 person-years by dividing the number of first events that occurred in each CD4 stratum by the time spent in the corresponding stratum (for patients who did not have the event) or the time between entry in the stratum and first event (for patients who experienced the event). Confidence intervals were calculated assuming a Poisson distribution if the number of events was lower than 50 and normal approximation otherwise.
Studies Sites Characteristics and Populations
Among 17 longitudinal studies of HIV-infected adults sponsored by the ANRS or associated partners in low-resource settings from 1996 to 2009, 5 included the follow-up of HIV-infected adults without ART. These 5 studies were conducted in Cote d'Ivoire and in Burkina Faso (Table 1). Their main objective was to study the following: HIV disease natural history (n = 2),2,20 sexually transmitted infections in vulnerable women (n = 1),21 tolerance and efficacy of interventions to prevent of mother-to-child transmission of HIV (n = 1),22 and feasibility of HIV care and treatment in a pilot program including pregnant and postpartum women with a family-focused approach (n = 1).23 In these 5 studies, between April 1996 and March 2009, 2699 adults were followed at least 1 day without ART, of whom 2588 (96%) had at least 1 measurement of CD4 count. Their main characteristics are shown in Table 1.
Mortality, LTFU, and ART Initiation
The 2588 patients were followed during 6862 person-years (Table 1). In pooled analysis, CD4-specific mortality rates decreased with increasing CD4 counts, from 3.0 per 100 person-years in the 201–350 cells per cubic millimeter CD4 strata to 0.2 per 100 person-years above 650 CD4 cells per cubic millimeter (Fig. 1). ART initiation rates also decreased with increasing CD4 counts, ranging from 18.1 per 100 person-years in the 201–350 cells per cubic millimeter CD4 strata to 0.5 per 100 person-years above 650 CD4 cells per cubic millimeter. LTFU rates ranged from 4.6 to 6.0 per 100 person-years, with no significant difference between CD4 strata.
Estimates varied across cohorts (Fig. 2, Table 2). Within the 201–350 cells per cubic millimeter CD4 stratum, the highest mortality rate was 5.0 per 100 person-years in a cohort with a low rate of ART initiation (3.4 per 100 person-years). In this cohort, the LTFU rate was 4.7 per 100 person-years. Conversely, the lowest mortality rate was 0.9 per 100 person-years in this CD4 stratum in a cohort with high rates of both LTFU and ART initiation. Within all CD4 strata above 350 cells per cubic millimeter, rates of ART initiation were low and mortality rates tended to be lower when the rate of LFTU was higher. The range of variability across cohorts of mortality rates decreased when CD4 count increased.
To our knowledge, this is the first report of CD4-specific mortality rates in HIV-infected adults with high CD4 count and no ART in West Africa.
Estimating CD4-specific rates requires longitudinal observational databases with repeated CD4 counts and standardized procedures. In sub-Saharan Africa, most of the large databases with longitudinal follow-up enroll HIV-infected patients at ART initiation.24 In untreated individuals, CD4 counts are often low at first contact25 and data on follow-up with high CD4 counts are scarce. Finally, most databases are rather program-based than research-oriented, meaning that data is recorded in real-life conditions, with rare CD4 count measurements and high rates of LTFU.26
We pooled data from ANRS-funded cohort studies in West Africa. In these studies, procedures, definitions, and data collection were standardized. Patients were followed free of charge, had systematic CD4 measurements every 6 months, and were systematically traced when they missed scheduled appointments.
CD4-specific mortality rates largely varied across cohorts. We censored follow-up at last contact in patients LTFU and at ART initiation in those who started ART. By doing so, we found the highest estimates of mortality within cohorts with the lowest rates of LTFU and in cohorts who were implemented during the pre-ART era and had the lowest rates of ART initiation. This strongly suggests that data censoring due to LTFU and ART initiation was informative and that mortality estimates are more accurate when rates of LTFU and ART initiation are low. As a consequence, in our study, true mortality figures are probably more accurately estimated in cohorts with the highest mortality rates and the lowest rates of LTFU and ART initiation; furthermore, in these cohorts with even low rates of LTFU and ART, mortality rates might be still underestimated because of informative censoring.
In our study, in the cohort with the lowest LTFU and ART initiation rates, mortality estimates were 5.0 per 100 person-years, 2.9 and 0.8 per 100 person-years in the 200–350, 350–500, and 500–650 CD4 cells per cubic millimeter strata, respectively. These rates are consistent with previous reports from Zimbabwe and South Africa.16,17 They are much higher than those reported by cohort collaborations from high-income countries.12,13 No formal comparison between settings is allowed, especially because our sample size is small and our confidence interval wide compared with those of large cohort collaborations from high-income countries. However, our findings strengthen the rationale for the 2010 WHO guidelines to increase the CD4 threshold for ART initiation from 200 cells per cubic millimeter to 350 cells per cubic millimeter in low-resource settings3 and suggest that the rationale for starting ART earlier than currently recommended might be even stronger in sub-Saharan Africa than in Europe or in North America. This also suggests that randomized trials assessing the benefits and risks of starting ART at high CD4 counts should carefully take into account the fact that mortality rates at high CD4 count might be different in high-resource as compared with low-resource settings.
Finally, our study confirms previous reports that many people are LTFU although waiting for ART, and suggestions by some authors that earlier initiation of ART may contribute to a better retention of patient in care.27
Our study has several limitations. The first limitation is its sample size. Yet our estimates are probably the best possible in the current context of obviously scarce data. Thus, there is clearly a need for large cohorts studies to be implemented in Africa, which would include patients with high CD4 counts and provide standardized follow-up before they initiate ART. These cohorts should ideally be multicountry and their funding should provide for a high level of data collection standardization, LTFU prevention, and morbidity documentation, conditions which are not always fulfilled in routine program databases.28,29
The second limitation is the extent of mortality underestimation. Our data suggest that LTFU and ART initiation probably led to underestimate true mortality rates in patients off ART through informative censoring, but the extent of this underestimation cannot be measured. LTFU may be a source of mortality misclassification, whereas ART initiation may be a source of both mortality and LTFU misclassification, as patients who start ART may be better retained into care than those who do not. The proportion of deaths among LTFU patients is unknown and may vary across CD4 strata. Available data on the outcomes of patients LTFU although on ART is increasing.30 Unfortunately, such data are scarce for individuals LTFU without ART with high CD4 counts.31,32 Even if recorded in the context of cohort studies, LTFU rates were similar or even higher than mortality rates, suggesting that even a low proportion of deaths among LTFU patients may have led to significantly underestimating mortality. We took into account informative censoring in the model estimating the CD4 count evolution,33 and by doing so we were able to accurately estimate the time spent within each CD4 strata. However, this did not allow us to adjust mortality rates with nonobserved events due to LTFU or initiation of ART.34
The third limitation is that we describe here crude mortality rates and not standardized mortality ratios. Therefore, we do not know how the mortality rates in patients with CD4 in the 2 strata >500 cells per cubic millimeter relate to the background population mortality.
The fourth limitation is that we did not address morbidity rates and causes of death in the present study. In fact, standardized morbidity data were recorded in only 2 of the 5 participating studies. Morbidity data from these 2 specific studies will be analyzed further.
Finally, our study included 80% of women. This percentage is higher than in the HIV-infected adult population in West Africa, thus limiting generalizability. Furthermore, 9% of the overall follow-up time was during pregnancy, which might influence data through both maternal mortality and the natural lowering of CD4 during pregnancy.35 The former might lead to overestimating mortality rates across the entire CD4 spectrum, whereas the latter might lead to misallocate some deaths to wrong CD4 strata.
In conclusion, mortality rates were substantial in our collaborative study conducted in West Africa in HIV-infected adults with more than 200 CD4 cells per cubic millimeter; all the more so as these mortality rates were probably underestimated because of informative censoring due to LTFU and ART initiation. We suggest that large multicountry cohorts including patients without ART with high CD4 counts should be implemented to better estimate the risk of early mortality in HIV-infected adults in sub-Saharan Africa. In such cohorts, underestimation of mortality due to informative censoring should be systematically discussed and the incidence of LTFU and ART initiation should be systematically provided when reporting CD4-specific rates of mortality.
1. Mellors JW, Munoz A, Giorgi JV, et al.. Plasma viral load and CD4+ lymphocytes as prognostic markers of HIV-1 infection. Ann Intern Med. 1997;126:946–954.
2. Anglaret X, Messou E, Oaussa T, et al.. Pattern of bacterial disease in a cohort of HIV-1 infected adults receiving cotrimoxazole prophylaxis, Abidjan, Côte d'Ivoire. AIDS. 2003;17:575–584.
5. Grinsztejn B, Ribaudo H, Cohen MS, et al.. Effects of early versus delayed initiation of antiretroviral therapy (ART) on HIV clinical outcomes: results from the HPTN 052 randomized clinical trial. Presented at: Proceedings of the 6th International AIDS Society (IAS) Conference on HIV Pathogenesis, Treatment and Prevention; July 17–20, 2011; Roma, Italy. [MOAX0105].
6. Thompson MA, Aberg JA, Cahn P, et al.. Antiretroviral treatment of adult HIV infection: 2010 recommendations of the International AIDS Society-USA panel. JAMA. 2010;304:321–333.
9. When to Start Consortium. Timing of initiation of antiretroviral therapy in AIDS-free HIV-1-infected patients: a collaborative analysis of 18 HIV cohort studies. Lancet. 2009;373:1352–1363.
10. Kitahata MM, Gange SJ, Abraham AG, et al.. Effect of early versus deferred antiretroviral therapy for HIV on survival. N Engl J Med. 2009;360:1815–1826.
11. Shepherd BE, Jenkins CA, Rebeiro PF, et al.. Estimating the optimal CD4 count for HIV-infected persons to start antiretroviral therapy. Epidemiology. 2010;21:698–705.
12. The UK Collaborative HIV Cohort (CHIC) Study Steering Committee. Rate of AIDS diseases or death in HIV-infected antiretroviral therapy-naive individuals with high CD4 cell count. AIDS. 2007;21:1717–1721.
13. Dunn D, Woodburn P, Duong T, et al.. Current CD4 cell count and the short-term risk of AIDS and death before the availability of effective antiretroviral therapy in HIV-infected children and adults. J Infect Dis. 2008;197:398–404.
14. Study Group on Death Rates at High CD4 Count in Antiretroviral Naive Patients. Death rates in HIV-positive antiretroviral-naive patients with CD4 count greater than 350 cells per μL in Europe and North America: a pooled cohort observational study. Lancet. 2010;376:340–345.
15. CASCADE Collaboration. Short-term risk of AIDS according to current CD4 cell count and viral load in antiretroviral drug-naive individuals and those treated in the monotherapy era. AIDS. 2004;18:51–58.
16. Badri M, Lawn SD, Wood R. Short-term risk of AIDS or death in people infected with HIV-1 before antiretroviral therapy in South Africa: a longitudinal study. Lancet. 2006;368:1254–1259.
17. Hargrove JW, Humphrey JH. Mortality among HIV-positive postpartum women with high CD4 cell counts in Zimbabwe. AIDS. 2010;24:F11–F14.
18. Thiebaut R, Jacqmin-Gadda H, Babiker A, et al.. Joint modelling of bivariate longitudinal data with informative dropout and left-censoring, with application to the evolution of CD4+ cell count and HIV RNA viral load in response to treatment of HIV infection. Stat Med. 2005;24:65–82.
19. Guo X, Carlin B. Separate and joint modeling for longitudinal and event time data using standard computer packages. Am Stat. 2004;58:1–9.
20. Minga A, Danel C, Abo Y, et al.. Progression to WHO criteria for antiretroviral therapy in a 7-year cohort of adult HIV-1 seroconverters in Abidjan, Cote d'Ivoire. Bull World Health Organ. 2007;85:116–123.
21. Nagot N, Ouangre A, Ouedraogo A, et al.. Spectrum of commercial sex activity in Burkina Faso: classification model and risk of exposure to HIV. J Acquir Immune Defic Syndr. 2002;29:517–521.
22. Dabis F, Bequet L, Ekouevi DK, et al.. Field efficacy of zidovudine, lamivudine and single-dose nevirapine to prevent peripartum HIV transmission. AIDS. 2005;19:309–318.
23. Tonwe-Gold B, Ekouevi DK, Bosse CA, et al.. Implementing family-focused HIV care and treatment: the first 2 years' experience of the mother-to-child transmission-plus program in Abidjan, Cote d'Ivoire. Trop Med Int Health. 2009;14:204–212.
24. Bartlett JA, Shao JF. Successes, challenges, and limitations of current antiretroviral therapy in low-income and middle-income countries. Lancet Infect Dis. 2009;9:637–649.
25. Wools-Kaloustian K, Kimaiyo S, Musick B, et al.. The impact of the President's Emergency Plan for AIDS Relief on expansion of HIV care services for adult patients in western Kenya. AIDS. 2009;23:195–201.
26. Geng EH, Nash D, Kambugu A, et al.. Retention in care among HIV-infected patients in resource-limited settings: emerging insights and new directions. Curr HIV/AIDS Rep. 2010;7:234–244.
27. Rosen S, Fox MP. Retention in HIV Care between testing and treatment in sub-Saharan Africa: a systematic review. PLoS Med. 2011;8:e1001056.
28. Tayler-Smith K, Zachariah R, Massaquoi M, et al.. Unacceptable attrition among WHO stages 1 and 2 patients in a hospital-based setting in rural Malawi: can we retain such patients within the general health system? Trans R Soc Trop Med Hyg. 2010;104:313–319.
29. 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.
30. Fox MP, Brennan A, Maskew M, et al.. Using vital registration data to update mortality among patients lost to follow-up from ART programmes: evidence from the Themba Lethu Clinic, South Africa. Trop Med Int Health. 2010;15:405–413.
31. Lessells RJ, Mutevedzi PC, Cooke GS, et al.. Retention in HIV care for individuals not yet eligible for antiretroviral therapy: rural KwaZulu-Natal, South Africa. J Acquir Immune Defic Syndr. 2011;56:E79–E86.
32. 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.
33. Duvignac J, Anglaret X, Kpozehouen A, et al.. CD4+ T-lymphocytes natural decrease in HAART-naive HIV-infected adults in Abidjan. HIV Clin Trials. 2008;9:26–35.
34. Brinkhof MW, Spycher BD, Yiannoutsos C, et al.. Adjusting mortality for loss to follow-up: analysis of five ART programmes in sub-Saharan Africa. PLoS One. 2010;5:e14149.
35. Ekouevi DK, Inwoley A, Tonwe-Gold B, et al.. Variation of CD4 count and percentage during pregnancy and after delivery: implications for HAART initiation in resource-limited settings. AIDS Res Hum Retroviruses. 2007;23:1469–1474.
THE ANRS 12222 MORBIDITY/MORTALITY STUDY GROUP
Steering Comittee: X.A., Robert Colebunders, François Dabis, Joseph Drabo, Serge Eholié, D.G., Pierre-Marie Girard, Karine Lacombe, C.La., Vincent Le Moing, and C.Le.
Other representants of participating studies: Gérard Allou, C.A-B., D.A., Aida Benalycherif, Pierre de Beaudrap, Charlotte Boullé, P.C., Ali Coulibaly, Eric Delaporte, Lise Denoeud, Serge Diagbouga, D.K.E., Jean-François Etard, Sabrina Eymard-Duvernay, Patricia Fassinou, Isabelle Fournier-Nicolle, Hervé Hien, Charlotte Huet, I.K., Sinata Koulla-Shiro, Valériane Leroy, Olivier Marcy, Pierre Régis Martin, Nicolas Meda, E.M., A.M., Eitel Mpoudi-Ngolé, Philippe Msellati, Boubacar Nacro, Nicolas Nagot, Ibra Ndoye, Thérèse N'Dri-Yoman, A.O., Men Pagnaroat, Roger Salamon, Vonthanak Saphonn, Olivier Segeral, Catherine Seyler, Besigin Tonwe-Gold, Moussa Traore, Philippe Van de Perre, Ida Viho, Marcel Zannou. Cited Here...
adults; CD4 lymphocyte count; HIV infection; informative censoring; lost to follow-up; mortality; sub-Saharan Africa
© 2012 Lippincott Williams & Wilkins, Inc.
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