It is unknown whether HIV treatment guidelines, based on resource-rich country cohorts, are applicable to African populations.
We estimated CD4 cell loss in ART-naïve, AIDS-free individuals using mixed models allowing for random intercept and slope, and time from seroconversion to clinical AIDS, death and antiretroviral therapy (ART) initiation by survival methods. Using CASCADE data from 20 European and 3 sub-Saharan African (SSA) cohorts of heterosexually-infected individuals, aged ≥15 years, infected ≥2000, we compared estimates between non-African Europeans, Africans in Europe, and Africans in SSA.
Of 1,959 (913 non-Africans, 302 Europeans - African origin, 744 SSA), two-thirds were female; median age at seroconversion was 31 years. Individuals in SSA progressed faster to clinical AIDS but not to death or non-TB AIDS. They also initiated ART later than Europeans and at lower CD4 cell counts. In adjusted models, Africans (especially from Europe) had lower CD4 counts at seroconversion and slower CD4 decline than non-African Europeans. Median (95% CI) CD4 count at seroconversion for a 15–29 year old woman was 607 (588–627) (non-African European), 469 (442–497) (European - African origin) and 570 (551–589) (SSA) cells/µL with respective CD4 decline during the first 4 years of 259 (228–289), 155 (110–200), and 199 (174–224) cells/µL (p<0.01).
Citation: Pantazis N, Morrison C, Amornkul PN, Lewden C, Salata RA, Minga A, et al. (2012) Differences in HIV Natural History among African and Non-African Seroconverters in Europe and Seroconverters in Sub-Saharan Africa. PLoS ONE 7(3): e32369. https://doi.org/10.1371/journal.pone.0032369
Editor: Robert J. Wilkinson, Institute of Infectious Diseases and Molecular Medicine, South Africa
Received: October 30, 2011; Accepted: January 26, 2012; Published: March 6, 2012
Copyright: © 2012 Pantazis 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: The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under EuroCoord grant agreement n° 260694. This work was also supported by funding from the Fogarty AIDS International Training and Research Program (AITRP) FIC 2D43 TW001042. This study is made possible by the generous support of the American people through the United States Agency for International Development (USAID). The contents are the responsibility of the International AIDS Vaccine Initiative and do not necessarily reflect the views of USAID or the United States Government. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
HIV disease progression is characterized by CD4 cell depletion leading to severe immunodeficiency and death in the absence of effective treatment , . CD4 cell count, along with plasma HIV-RNA have been established as the most important prognostic markers of HIV-1 disease progression , ,  and, as such, are used to guide therapeutic decisions .
Current treatment guidelines are largely based on data from high-income countries, although the vast majority of the world's HIV-infected people live in low and middle-income countries, particularly sub-Saharan Africa (SSA) . A limited number of studies have estimated CD4 cell loss in ART-naïve individuals in African countries , , , and a few have directly compared this to estimates derived from high-income countries , , , . Fewer still have used data from individuals with well-estimated dates of HIV seroconversion , . This is important as measures of CD4 cell count from seroprevalent HIV cohorts do not capture duration of HIV infection sufficiently . Furthermore, no study has directly compared time from HIV seroconversion to treatment initiation, clinical AIDS (i.e. not including CD4<200 cells//µL) , or death in SSA and high-income countries. It remains crucial to understand whether any observed differences in the rate of CD4 cell decline between population groups leads to appreciable survival differences. Such differences would need to be considered when developing guidelines on the optimal timing of treatment initiation. In addition, understanding population-specific differences in CD4 cell levels and dynamics after seroconversion could guide study designs in evaluating multi-national HIV prevention and vaccine efficacy trial endpoints.
The objectives of this study are to assess and compare CD4 cell trends, from the time of HIV seroconversion, but prior to antiretroviral treatment initiation, and time to clinical AIDS or death, in persons followed in SSA and European cohorts. We also compare differences in CD4 cell decline and time-to-events between Africans living in Europe with those living in Africa. Individuals in the former group were likely infected in Europe as they had a previous negative HIV test documented in a European clinic.
All collaborating cohorts received approval from their respective or national ethics review boards. Ethics approval for CASCADE collaborating cohorts has been granted by the following committees: Austrian HIV Cohort Study: Ethik-Kommission der Medizinischen Universität Wien, Medizinische Universität Graz – Ethikkommission, Ethikkommission der Medizinischen Universität Innsbruck, Ethikkommission des Landes Oberösterreich, Ethikkommission für das Bundesland Salzburg; PHAEDRA cohort: St Vincent's Hospital, Human Research Ethics Committee; Southern Alberta Clinic Cohort: Conjoint Health Research Ethics Board of the Faculties of Medicine, Nursing and Kinesiology, University of Calgary; Aquitaine Cohort: Commission Nationale de l'Informatique et des Libertés; French Hospital Database: Commission nationale de l'informatique et des libertés CNIL; French ANRS PRIMO Cohort: Comité Consultatif de Protection des Personnes dans la Recherche Biomédicale; French ANRS SEROCO Cohort: Commission Nationale de l'Informatique et des Libertés (CNIL); German HIV-1 Seroconverter Study: Charité, University Medicine Berlin; AMACS: Bioethics & Deontology Committee of Athens University Medical School and the National Organization of Medicines; Greek Haemophilia Cohort: Bioethics & Deontology Committee of Athens University Medical School and the National Organization of Medicines; ICoNA cohort: San Paolo Hospital Ethic Committee; Italian Seroconversion Study: Comitato etico dell'Istituto Superiore di Sanità; Amsterdam Cohort Studies in Homosexual Men and IDUs: Academic Medical Centre, University of Amsterdam; Oslo and Ulleval Hospital Cohorts: Regional komite for medisinsk forskningsetikk - Øst- Norge (REK 1); Badalona IDU Hospital Cohort: Comité Ético de Investigación Clínica del Hospital Universitari Germans Trias i Pujol; CoRIS-scv: Comité Ético de Investigación Clínica de La Rioja; Madrid Cohort: Ethics Committee of Universidad Miguel Hernandez de Elche; Valencia IDU Cohort: Comité Etico de Investigación Clínica del Hospital Dr. Peset-Valencia; Swiss HIV Cohort Study: Kantonale Ethikkommission, spezialisierte Unterkommission Innere Medizin, Ethikkommission beider Basel, Kantonale Ethikkommission Bern, Comité départemental d'éthique de médecine et médecine communautaire, Commission d'éthique de la recherche clinique, Université de Lausanne, Comitato etico cantonale, Ethikkommission des Kantons St.Gallen; UK Register of HIV Seroconverters: South Birmigham REC; Early Infection Cohorts: Kenya Medical Research Institute, Kenyatta National Hospital, Uganda Virus Research Institute Science and Ethics Committee, Uganda National Council for Science and Technology, Uganda Virus Research Institute Science and Ethics Committee, Uganda National Council for Science and Technology, University of Zambia Research Ethics Committee, Emory IRB, National Ethics Committee of Rwanda, University of Cape Town Research Ethics Committee, University of KwaZulu-Natal Nelson R Mandela School of Medicine; Genital Shedding Study Cohort: University Hospitals of Cleveland, IRB for Human Investigation (CWRU), AIDS Research Committee (ARC), STD/AIDS Control Programme, Uganda Ministry of Health, Committee on Human Research (CHR), Office of Research Administration (UCSF), Biomedical Research & Training Institute (BRTI) – Zimbabwe, Institutional Review Office, Fred Hutchinson Cancer Research Center, Medical Research Council of Zimbabwe (MRCZ). Written informed consent was obtained from all participants. Minors are not included.
We used data from the CASCADE Collaboration (Concerted Action of Seroconversion to AIDS and Death in Europe) in EuroCoord (www.EuroCoord.net) and the ANRS 1220 PRIMO-CI study. CASCADE is a collaboration of 25 cohorts of individuals with well-estimated dates of HIV seroconversion (seroconverters) ; PRIMO-CI is an ongoing prospective cohort of HIV-1 seroconverters initiated in June 1997 in Abidjan, Côte d'Ivoire . At the time of data update in September 2009 CASCADE included 20 European, 2 Australian and one Canadian cohort. Two SSA cohorts have also joined CASCADE: the International AIDS Vaccine Initiative (IAVI)-sponsored African HIV Research Network Early HIV Infection Cohort (Kenya, Uganda, Rwanda, Zambia, South Africa)  and the FHI-sponsored Hormonal Contraception (HC) and HIV Genital Shedding and Disease Progression (GS) Cohort in Uganda and Zimbabwe , . Data from the Canadian and Australian CASCADE cohorts were excluded from this analysis.
The seroconversion date is estimated by various methods: most frequently as the midpoint between the last documented negative and first positive HIV antibody test dates with an interval of less than 3 years between tests, through laboratory evidence of seroconversion (PCR positivity in the absence of HIV antibodies or antigen positivity with fewer than four bands on Western blot), or as the date of a seroconversion illness with both an earlier documented negative and a later positive HIV test not more than 3 years apart.
Given that the vast majority of individuals recruited in the SSA cohorts were infected heterosexually and seroconverted in or after the year 2000, individuals infected through other modes of transmission or before year 2000 were excluded from current analyses. Since patterns of change in CD4 count may differ for children, individuals aged less than 15 years at seroconversion were also excluded. Finally, we excluded all CD4 cell measurements taken after combination antiretroviral therapy (cART) initiation or clinical AIDS development and used data only from individuals with at least two eligible CD4 cell measurements. cART was defined as either a protease inhibitor-based or a non-nucleoside reverse transcriptase inhibitor-based regimen, in combination with at least two nucleoside or nucleotide reverse transcriptase inhibitors (NRTIs), or a triple NRTI regimen. Women receiving single dose nevirapine for prevention of mother-to-child HIV transmission were not censored.
Eligible individuals were categorized according to the location of their cohort (i.e. Europe or SSA). Using information from two variables collected in CASCADE: “ethnicity” and “geographic origin”, we further divided individuals belonging to European cohorts. Because limited ethnicity data were collected in the European cohorts, individuals who were non-white, and whose country of origin was in SSA or North Africa, were classified as “Europeans - African origin”. All other seroconverters in European cohorts were classified as “non-African Europeans”. Three groups were thus created: non-African Europeans, Europeans - African origin, and SSAs.
CD4 counts at cART initiation and at AIDS diagnosis were estimated through a modified Kaplan–Meier technique . We estimated average CD4 cell trends over time, accounting for the correlation among repeated measurements within each individual, through linear mixed models with random intercept and random slope . We used the square root transformation of CD4 count values to normalise their distribution, stabilise their variance and linearise changes over time .
Using Kaplan-Meier methods, we also estimated times from HIV seroconversion to each of the following: clinical AIDS, initiation of cART, death, and loss to follow-up adjusting for late entry into the cohort. In order to assess whether differences in time to clinical AIDS were due to pulmonary or extra-pulmonary tuberculosis (TB), an AIDS-defining event known to occur at higher rates in African compared to European populations, we repeated the analysis excluding TB as an AIDS event. Loss to follow-up was defined as a gap of more than 12 (or 6 in a sensitivity analysis) months between a patient's last CD4 evaluation or clinical assessment and the date their cohort dataset was pooled within CASCADE.
Sensitivity analyses were performed to investigate the robustness of our main findings, taking into account the potentially informative truncation ,  of CD4 cell measurements due to cART initiation or loss to follow-up. More specifically, our final multivariable mixed model was refitted using joint models for both the evolution of CD4 cell counts and the time to the potentially informative event (i.e. cART initiation or loss to follow-up). The proportion of individuals who progressed to AIDS or died while ART-naïve was negligible, thus AIDS and death were not considered as informative censoring events. However, to minimize the potential bias that may result from those censoring mechanisms, the analysis was repeated with follow-up censored at 3 years following seroconversion. Finally, sensitivity analyses included the application of the main multivariable mixed model on a dataset where individuals with only one eligible CD4 cell measurement were included.
All analyses were performed using Stata 10.1 (StataCorp, TX USA). Joint models were fitted through the Joint Multivariate Random Effects (JMRE)  method using the user-written jmre1 command in Stata .
Study population characteristics
The CASCADE database included data from 20,631 individuals: 19,921 from Europe, Australia or Canada, 408 from IAVI-sponsored cohorts and 302 from FHI-sponsored studies. Data from a further 285 individuals from the Primo-CI cohort were also included.
Of the 19,921 individuals from resource-rich countries, we excluded: 12,910 who had seroconverted before 2000, 4,901 who were not infected through sex between men and women, 519 who had one or no CD4 counts while ART-naïve and AIDS-free, 374 who were from non-European cohorts, and 2 who were aged <15 years. From the 995 individuals in the three SSA cohorts, we excluded 251 individuals: 105 had seroconverted pre-2000, 94 were not infected through sex between men and women, and 52 had one or no CD4 counts while ART-naïve and AIDS-free. In summary, the three study groups in these analyses comprising 1,959 individuals were: non-African Europeans (N = 913), Europeans - African origin (N = 302), and SSAs (N = 744).
Of the 1,959 individuals in the final analysis, two-thirds were female; the median age at seroconversion was 31 years (Table 1). The median (IQR) duration of follow-up was 3.5 years (1.8–5.7), representing a total of 7,420 person-years (Table 2). The median number of CD4 measurements was seven and was higher in SSAs (10) than in the non-African Europeans (5) and Europeans - African origin (4).
CD4 cell count evolution
Both the unadjusted and adjusted models estimate lower initial CD4 cell count as well as slower rates of decline for all Africans compared to their non-African European counterparts (Table 3). Differences between the unadjusted and adjusted model were small with the group effects on the rate of CD4 cell decline being slightly attenuated in the adjusted models.
Women had consistently higher CD4 cell counts. Younger individuals and those with a delayed cohort entry of more than 6 months had a slower CD4 cell decline. Calendar year of seroconversion, method of seroconversion determination, and interval between last negative and first positive HIV tests dates were not significantly associated with CD4 cell decline, after adjusting for other factors included in the multivariable model.
The mean (95% C.I.) estimated CD4 cell count at seroconversion for women, aged 15–29 years who enrolled into the cohorts within 6 months of seroconversion were 607 (588, 627), 469 (442, 497) and 570 (551, 589) cells/µL for non-African Europeans, Europeans - African origin, and SSA cohorts, respectively (Figure 1). The corresponding CD4 cell loss in the first 4 years from seroconversion was 259 (228, 289), 155 (110, 200) and 199 (174, 224) cells/µL, respectively.
AIDS diagnoses, survival, cART initiation and loss to follow-up
Despite the slower rate of CD4 cell loss, the probability of being diagnosed with clinical AIDS was higher in all Africans, particularly in SSA cohorts (Figure 2). The most common clinical AIDS events in SSA cohorts were pulmonary TB (29.7%) and HIV wasting syndrome (14.9%). The corresponding events in Europe were Pneumocystis pneumonia (20.0%) and Kaposi Sarcoma (17.1%) among persons of non-African origin; TB was the most common first AIDS-defining event (61.6%) among Europeans of Africa origin (extra-pulmonary (38.5%) and pulmonary (23.1%)). After excluding pulmonary or extra-pulmonary TB as an AIDS event, however, we found only a marginal difference in time to clinical AIDS between the three groups (p = 0.06). Overall survival including persons with TB was similar, however, among the three study groups.
Curves shown by study group: individuals of non-African origin (solid line) or of African origin (dotted line) in European cohorts and individuals in SSA cohorts (dashed line).
Individuals in SSA cohorts tended to initiate treatment later than those in the European cohorts (p<0.001). Estimated median (95% CI) CD4 cell count at cART initiation was 296 (287, 309), 274 (262, 290) and 188 (172, 192) cells/µL for non-African Europeans, Europeans of African origin, and SSAs, respectively (p<0.001). The corresponding estimated median (95% CI) CD4 cell count at AIDS diagnosis was 42 (19, 116), 143 (<52, 164) and 82 (22, 126) cells/µL (p = 0.078).
Rates of loss to follow-up (among AIDS-free persons not on cART) were substantially higher in European cohorts compared to SSA cohorts (Figure 2) (p<0.001).
Sensitivity analyses showed that our results were robust when taking into account the potentially informative truncation of CD4 cell measurements due to loss to follow-up. When we simultaneously fitted the final multivariable model for CD4 cell evolution (Table 3) with a survival model for the time to loss to follow-up, the changes in the estimates of the CD4 cell count model were negligible irrespectively of the loss to follow-up definition (i.e. ≥12 or ≥6 months gap).
We adjusted for potentially informative truncation of CD4 cell count measurements due to cART initiation. This resulted in a much faster decline in CD4 count, but the average CD4 cell count at seroconversion and the corresponding differences between groups remained similar to those in the main analysis. The corresponding difference between individuals in SSA and non-African Europeans became more pronounced and was highly significant; the difference in slopes between non-African Europeans and Europeans - African origin became attenuated and was no longer significant. However, treating cART as an informative censoring event is probably inappropriate in this case since decisions about its initiation are mainly based on already observed outcomes (i.e. prior CD4 cell measurements). Moreover, the application of the mixed models in our main analysis on data where we artificially censored follow-up at 3 years after seroconversion, yielded very similar estimates to those reported in Table 3.
Finally, when we included data from the 469 individuals with only one CD4 cell count while ART-naïve and AIDS-free, our main findings remained practically unchanged. The sole exception was that the difference in initial CD4 cell count between individuals in SSA and non-African Europeans was attenuated and no longer statistically significant. The majority of the additional individuals were in the latter group and started cART immediately after their first CD4 cell measurement.
We found that Africans, particularly those in European cohorts, have lower initial CD4 cell counts and slower rates of CD4 cell decline in the absence of cART. This does not, however, appear to have conferred them with any survival advantage. That said, because we had limited duration of follow-up (median, 3.5 years), there may be inherent differences in long-term survival that we were unable to detect.
Although seroconverters in SSA were initially seemingly disadvantaged by having lower CD4 cell counts at seroconversion, their subsequent slower CD4 cell loss resulted in them reaching the same CD4 levels as the other two groups by approximately 2.5 years after seroconversion. Their average CD4 count was higher thereafter falling below 350 cells/µL almost 6 months later than that of non-African Europeans. In contrast, Europeans - African origin consistently had the lowest average CD4 counts throughout the follow-up period and reached a CD4 count of350 cells/µL approximately 1 to 1.5 years earlier than non-African Europeans and Africans living in SSA, respectively. Of note, the slower CD4 cell count decline in African populations remained evident even after conditioning on CD4 levels at seroconversion.
These findings are in agreement with two smaller seroconverter cohorts with shorter follow-up time ,  and a number of seroprevalent cohorts, of lower CD4 cell counts and similar or milder CD4 cell decline in Africans compared to their counterparts in Europe and North America , , , , .
It is well known that, even in healthy individuals, lymphocyte subset values are influenced by various factors including genetics and the environment . Genetic factors such as HLA type can segregate along African tribal lines. In sub-Saharan Africa environmental factors such as parasitic (e.g. malaria, schistosomiasis), respiratory, and gastrointestinal co-morbidities are much more common than in Europe and will likely affect the immune status of residents. Furthermore, it has been proposed that the infecting HIV-1 subtype may also influence CD4 levels . Given that subtype information was unavailable for more than 80% of individuals from Europeans cohorts and, for those with known subtype, the most prevalent subtype among non-African Europeans was B (49%) and, among Africans, non-B (69% CRF_02 and 74% A or C for Europeans- African origin and SSA, respectively) with only 2 SSA seroconverters being infected with subtype B, we were not able to assess the contribution of subtype, in addition to that of ethnicity and geographic origin. A large CD4 difference between Africans and non-Africans followed in the French ANRS PRIMO cohort was found after controlling for subtype . Muller et al's study  concluded that the differences they observed in rate of CD4 cell loss among Africans and Europeans in the Swiss HIV cohort were unlikely to be due to environmental factors, since they were all located in Switzerland, or to the infecting HIV-1 subtype, since differences persisted even after controlling for subtype. Their conclusion that these differences were likely due to host genetic factors is further supported by our findings of a slower rate of CD4 cell loss experienced by Africans, in both the European and SSA cohorts compared to non-African Europeans. Environmental factors may still play a role, however, since adaptation to a new environment after relocation takes place gradually over time. Unfortunately, we do not have data on dates of migration to Europe for the Europeans of African origin to allow further exploration. Of note, however, we found that CD4 levels for Europeans- African origin were much lower than those in the SSA cohorts. One reason for this is that African populations are genetically very diverse, and large differences in CD4 levels (both pre- and post-seroconversion) have been observed even among populations living in geographically-close countries . In our study, the majority of the Europeans of African origin live in France and are more likely to originate from North and West Africa rather than from Eastern or Southern Africa, where the majority of the participants in the SSA cohorts originate.
Africans, particularly those in SSA cohorts, progressed to clinical AIDS significantly faster than non-African Europeans (p = 0.002). After excluding both pulmonary and disseminated TB as AIDS-defining events, however, we found little evidence of a difference in time to AIDS between groups (p = 0.06). We acknowledge that the power of this comparison is reduced due to the low number of non-TB AIDS events. However, this suggests that the difference between the Europeans and Africans in European cohorts is largely due to differences in TB rates. This TB rate differential partially, accounts for the differences in progression to AIDS between the SSA and both European groups as well. Any remaining difference in time to AIDS may be due to differences in co-infection rates and existing co-morbidities. For example, malaria is reported to facilitate HIV replication through increased cytokine production and immune cell activation  leading to CD4 cell loss and the consequent diagnosis of AIDS-defining conditions. Residual differences in progression to AIDS may also be an artefact of the higher number of CD4 cell measurements taken from SSA cohort participants compared to participants in the resource-rich country cohorts (10 vs. 5 and 4 measurements, respectively). The more frequent CD4 testing would allow an AIDS diagnosis to be made earlier. The fact that TB is often diagnosed at higher CD4 cell counts  may also explain why the SSA group (which had higher TB rates) progressed to AIDS more rapidly despite their slower CD4 cell decline.
Not surprisingly, given the differences in HIV treatment guidelines based on CD4 counts and the tendency in Europe to treat primary HIV infection, we found that individuals in European cohorts initiated cART earlier than their SSA counterparts. Individuals in SSA cohorts initiated cART with 86–108 CD4 cells/µL, on average, lower than their counterparts in European cohorts. Despite lower CD4 cell count at cART initiation, after TB is excluded as an AIDS-defining event, estimated time to clinical AIDS for individuals from SSA cohorts is similar to that of Europeans. This suggests that the slower CD4 cell loss may have conferred a clinical benefit counterbalancing lower CD4 counts at seroconversion. It also supports the WHO recommendations for active TB case finding and isoniazid preventive therapy for HIV-infected individuals in Africa  to improve clinical prognosis.
Europeans - African origin in this analysis were more likely to initiate cART soon after seroconversion compared to non-African Europeans. This is, most probably, because the majority of identified Africans (n = 288, 95%) in European cohorts were enrolled in France, a country with particular interest in treating primary HIV infection ; French cohorts of African and non-African ancestry comprised 48% of the data in our analyses.
Interestingly, individuals enrolled into cohorts within 6 months of seroconversion had significantly faster rates of CD4 cell decline compared to those enrolled later. This suggests that, in cohorts with substantial delayed enrolment, there may exist a preferential inclusion of slow progressors because those progressing more rapidly are less likely to be enrolled into cohorts. It may also be because the rate of CD4 loss is higher around the time of seroconversion, and this rapid drop is more likely to be identified in individuals with shorter enrolment times and more frequent CD4 cell measurements. Of note, the time from infection to cohort enrolment was longer in the European, compared to the SSA cohorts, particularly for individuals of African origin. Even after adjusting for this, however, we found significantly slower CD4 cell loss among Europeans - African origin. Moreover, restricting the analysis to those with short (i.e. <6 or <3 months) enrolment delay did not alter significantly our main findings.
These results were based on the analysis of longitudinal data derived from a large collaboration of prospective cohorts in 7 West European and 7 SSA countries. The large size of the CASCADE database allowed us to restrict the analysis to recent seroconverters and to those heterosexually infected. Importantly, the robustness of our findings regarding the effects of the most common truncation mechanisms and the exclusion of individuals with only one CD4 measurement while ART-naïve and AIDS-free has been investigated through a series of sensitivity analyses. Results from these analyses showed that our findings regarding the lower initial CD4 cell count levels of African immigrants in Europe and the slower rate of CD4 cell loss among SSA seroconverters remained consistent with those of the main analysis.
Our study is based on data from observational cohorts. Despite restricting the European data to include only individuals with the characteristics of African cohorts and adjusting for most of the known prognostic and confounding factors, residual confounding and potential selection bias in cohort enrolment cannot be ruled out. Because the healthcare infrastructure in SSA is limited and quality healthcare difficult to access, the frequent study visits, and resulting increased contact with clinicians, experienced by the SSA cohorts could also influence the health status and outcomes for the SSA cohorts. These factors most likely contributed to the low loss to follow-up rate seen in the SSA cohorts as well. The SSA cohorts provided transportation and/or reimbursement for transportation and time, health care services for acute illnesses, regular counselling, active follow-up of individuals who missed study visits and required frequent study visits. All of these are factors effective in promoting low loss to follow-up rates in resource-poor settings. Furthermore, seroconverters may not be representative of the general HIV-infected population, although we recently showed that estimates of HIV progression derived from seroconverter cohorts are similar to that seen in the general HIV-infected population .
In conclusion, although Africans in SSA and Europe demonstrated a slower rate of CD4 cell decline and higher rates of tuberculosis than non-African Europeans, survival rates and AIDS rates, excluding TB, were similar. Given that treatment decisions, particularly in resource-rich countries, are largely based on CD4 levels, understanding initial CD4 counts at seroconversion, subsequent CD4 decline, and the time from seroconversion to key CD4 thresholds (e.g. 350, 200 cells/µL) will impact the timing of ART initiation. Based on these findings, it appears, therefore, that HIV treatment guidelines developed from cohorts in Europe are applicable and appropriate for Africans. Universal access and implementation of such guidelines remains the primary challenge.
CASCADE Steering Committee: Julia Del Amo (Chair), Laurence Meyer (Vice Chair), Heiner C. Bucher, Geneviève Chêne, Osamah Hamouda, Deenan Pillay, Maria Prins, Magda Rosinska, Caroline Sabin, Giota Touloumi. Co-ordinating Centre: Kholoud Porter (Project Leader), Sara Lodi, Kate Coughlin, Sarah Walker, Abdel Babiker.
CASCADE Clinical Advisory Board: Heiner C. Bucher, Andrea De Luca, Martin Fisher, Roberto Muga
CASCADE Collaborators: Austria: Austrian HIV Cohort Study (Robert Zangerle); Australia PHAEDRA cohort (AD Kelleher, DA Cooper, Pat Grey, Robert Finlayson, Mark Bloch) Sydney AIDS Prospective Study and Sydney Primary HIV Infection cohort (Tony Kelleher, Tim Ramacciotti, Linda Gelgor, David Cooper, Don Smith); Canada South Alberta clinic (John Gill); Denmark Statens Serum Institute (Louise Bruun Jørgensen); Estonia Tartu Ülikool (Irja Lutsar); France Aquitaine cohort (Geneviève Chêne, Francois Dabis, Rodolphe Thiebaut, Bernard Masquelier), French Hospital Database (Dominique Costagliola, Marguerite Guiguet), Lyon Primary Infection cohort (Philippe Vanhems), French PRIMO cohort (Marie-Laure Chaix, Jade Ghosn), SEROCO cohort (Laurence Meyer, Faroudy Boufassa); Germany German cohort (Osamah Hamouda, Claudia Kücherer, Barbara Bartmeyer); Greece Greek Haemophilia cohort (Giota Touloumi, Nikos Pantazis, Olga Katsarou), AMACS (Paparizos V, Gargalianos-Kakolyris P, Lazanas M); Italy Italian Seroconversion Study (Giovanni Rezza, Maria Dorrucci), ICONA cohort (Antonella d'Arminio Monforte, Andrea De Luca.) Netherlands Amsterdam Cohort Studies among homosexual men and drug users (Maria Prins, Ronald Geskus, Jannie van der Helm, Hanneke Schuitemaker); Norway Oslo and Ulleval Hospital cohorts (Mette Sannes, Oddbjorn Brubakk, Anne-Marte Bakken Kran); Poland National Institute of Hygiene (Magdalena Rosinska); Spain Badalona IDU hospital cohort (Roberto Muga, Jordi Tor), Barcelona IDU Cohort (Patricia Garcia de Olalla, Joan Cayla), CoRIS-scv (Julia del Amo, Santiago Moreno, Susana Monge; Madrid cohort (Julia Del Amo, Jorge del Romero), Valencia IDU cohort (Santiago Pérez-Hoyos); Switzerland Swiss HIV Cohort Study (Heiner C. Bucher, Martin Rickenbach, Patrick Francioli); Ukraine Perinatal Prevention of AIDS Initiative (Ruslan Malyuta); United Kingdom Edinburgh Hospital cohort (Ray Brettle), Health Protection Agency (Gary Murphy), Royal Free haemophilia cohort (Caroline Sabin), UK Register of HIV Seroconverters (Kholoud Porter, Anne Johnson, Andrew Phillips, Abdel Babiker, Valerie Delpech), University College London (Deenan Pillay). African cohorts: Genital Shedding Study (US: Charles Morrison; FHI 360, Robert Salata, Case Western Reserve University, Uganda: Roy Mugerwa, Makerere University, Zimbabwe: Tsungai Chipato, University of Zimbabwe); Early Infection Cohorts (Kenya, Uganda, Rwanda, Zambia, South Africa: Pauli Amornkul, International AIDS Vaccine Initiative).
EuroCoord Executive Board: Geneviève Chêne, University of Bordeaux II, France; Dominique Costagliola, Institut National de la Santé et de la Recherche Médicale, France Julia Del Amo, Instituto de Salud Carlos III, Spain; Carlo Giaquinto, Fondazione PENTA, Italy; Di Gibb, Medical Research Council, UK; Jesper Grarup, Københavns Universitet, Denmark; Ole Kirk, Københavns Universitet, Denmark; Bruno Ledergerber, University of Zurich, Switzerland; Laurence Meyer, Institut National de la Santé et de la Recherche Médicale, France; Alex Panteleev, St. Petersburg City AIDS Centre, Russian Federation; Andrew Phillips, University College London, UK, Kholoud Porter (Chair), Medical Research Council, UK; Caroline Sabin (Scientific Coordinator), University College London, UK, Claire Thorne, University College London, UK; Stephen Welch, Fondazione PENTA, UK.
EuroCoord Council of Partners: Jean-Pierre Aboulker, Institut National de la Santé et de la Recherche Médicale, France; Jan Albert, Karolinska Institute, Sweden; Silvia Asandi , Romanian Angel Appeal Foundation, Romania; Geneviève Chêne, University of Bordeaux II, France; Dominique Costagliola, INSERM, France; Antonella d'Arminio Monforte, ICoNA Foundation, Italy; Stéphane De Wit, St. Pierre University Hospital, Belgium; Frank De Wolf, Stichting HIV Monitoring, Netherlands; Julia Del Amo, Instituto de Salud Carlos III, Spain; José Gatell, Fundació Privada Clínic per a la Recerca Bíomèdica, Spain; Carlo Giaquinto, Fondazione PENTA, Italy; Osamah Hamouda, Robert Koch Institut, Germany; Igor Karpov, University of Minsk, Belarus; Bruno Ledergerber, University of Zurich, Switzerland; Jens Lundgren, Københavns Universitet, Denmark; Ruslan Malyuta, Perinatal Prevention of AIDS Initiative, Ukraine; Claus Møller, Cadpeople A/S, Denmark; Andrew Phillips , University College London, UK; Kholoud Porter, Medical Research Council, United Kingdom; Maria Prins, Academic Medical Centre, Netherlands; Aza Rakhmanova, St. Petersburg City AIDS Centre, Russian Federation; Jürgen Rockstroh (Chair), University of Bonn, Germany; Magda Rosinska, National Institute of Public Health, National Institute of Hygiene, Poland; Claire Thorne, University College London, UK; Giota Touloumi, National and Kapodistrian University of Athens, Greece; Alain Volny Anne, European AIDS Treatment Group, France.
EuroCoord External Advisory Board: David Cooper, University of New South Wales, Australia; Nikos Dedes, Positive Voice, Greece; Kevin Fenton, Centers for Disease Control and Prevention, USA; David Pizzuti, Gilead Sciences, USA; Marco Vitoria, World Health Organisation, Switzerland.
EuroCoord Secretariat: Kate Coughlin, MRC Clinical Trials Unit, UK; Silvia Faggion, Fondazione PENTA, Italy; Richard Frost, MRC Regional Centre London, UK; Lorraine Fradette, MRC Clinical Trials Unit, UK; Christine Schwimmer, University of Bordeaux II, France; Martin Scott, UCL European Research & Development Office, UK.
ANRS 1220 Primo-CI Study Group
Principal Investigators: Albert Minga, Charlotte Lewden
Clinical Investigators and Event Documentation Committee: Yao Abo, Lambert Dohoun, Albert Minga
Cohort Management: Emma Anini Yah Drowa, Isidore Bohouo Bades, Tatiana Kouamé, Marie Julie N'Dri, Minata Ouattara, Abdelh Sidibé
Biology: Roseline Afi, Arlette Emieme, André Inwoley, Thomas d'Aquin Toni
Data-management and statistics: Ali Coulibaly, Germain Bomisso, Mamadou Konaté
Xavier Anglaret, Brigitte Bazin, Francois Dabis, Christine Danel, Christiane Deveau, Cécile Goujard, Laurence Quinty, Laurence Meyer, Roger Salamon, Rodolphe Thiébaut, Marie-Laure Chaix, Christine Rouzioux, Martine Sinet
Support: Agence Nationale de Recherche sur le SIDA et les Hépatites Virales (ANRS) - French Agency on AIDS and Viral Hepatitis
International AIDS Vaccine Initiative (IAVI) African HIV Research Network, Early HIV Infection Cohort
Principal Investigators (PIs): Etienne Karita* (Protocol Chair), Susan Allen, Omu Anzala*, Linda-Gail Bekker, Mubiana Inambao, Anatoli Kamali*, William Kilembe, Shabir Lakhi*, Mary H. Latka*, Eduard Sanders*
Clinical Investigators: Gaudensia Mutua, Mary Mwangome, Eugene Ruzagira, Rogers Twesigye
IAVI team: Pauli N. Amornkul*, Emmanuel Cormier, Pat Fast*, Jill Gilmour*, Marietta Krebs, Matt Price, Gwynneth Stevens, Helen Thomson, Sarah Yates
Steering Committee: Anatoli Kamali (Current Chair), Pontiano Kaleebu (Former Chair), Eric Hunter, and denoted (*) PIs/IAVI members.
FHI Hormonal Contraception and HIV Genital Shedding and Disease Progression Cohort
US: Charles Morrison; Family Health International, Robert Salata, Case Western Reserve University, Uganda: Roy Mugerwa, Josaphat Byamugisha, Makerere University, Zimbabwe: Tsungai Chipato, Thulani Magwali, University of Zimbabwe)
Conceived and designed the experiments: NP GT CM PNA KP. Analyzed the data: NP GT. Wrote the paper: NP GT KP. Drafted manuscript with critical revision for important intellectual content undertaken: CM PNA CL RAS AM TC HJ SL EK LM.
- 1. Katzenstein DA, Hammer SM, Hughes MD, Gundacker H, Jackson JB, et al. (1996) The relation of virologic and immunologic markers to clinical outcomes after nucleoside therapy in HIV-infected adults with 200 to 500 CD4 cells per cubic millimeter. New England Journal of Medicine 335: 1091–1098.DA KatzensteinSM HammerMD HughesH. GundackerJB Jackson1996The relation of virologic and immunologic markers to clinical outcomes after nucleoside therapy in HIV-infected adults with 200 to 500 CD4 cells per cubic millimeter.New England Journal of Medicine33510911098
- 2. Pantaleo G, Graziosi C, Fauci AS (1993) The Immunopathogenesis of Human-Immunodeficiency-Virus Infection. New England Journal of Medicine 328: 327–335.G. PantaleoC. GraziosiAS Fauci1993The Immunopathogenesis of Human-Immunodeficiency-Virus Infection.New England Journal of Medicine328327335
- 3. OBrien WA, Hartigan PM, Martin D, Esinhart J, Hill A, et al. (1996) Changes in plasma HIV-1 RNA and CD4+ lymphocyte counts and the risk of progression to AIDS. New England Journal of Medicine 334: 426–431.WA OBrienPM HartiganD. MartinJ. EsinhartA. Hill1996Changes in plasma HIV-1 RNA and CD4+ lymphocyte counts and the risk of progression to AIDS.New England Journal of Medicine334426431
- 4. Sterling TR, Vlahov D, Astemborski J, Hoover DR, Margolick JB, et al. (2001) Initial plasma HIV-1 RNA levels and progression to AIDS in women and men. New England Journal of Medicine 344: 720–725.TR SterlingD. VlahovJ. AstemborskiDR HooverJB Margolick2001Initial plasma HIV-1 RNA levels and progression to AIDS in women and men.New England Journal of Medicine344720725
- 5. Mellors JW, Munoz A, Giorgi JV, Margolick JB, Tassoni CJ, et al. (1997) Plasma viral load and CD4(+) lymphocytes as prognostic markers of HIV-1 infection. Annals of Internal Medicine 126: 946–954.JW MellorsA. MunozJV GiorgiJB MargolickCJ Tassoni1997Plasma viral load and CD4(+) lymphocytes as prognostic markers of HIV-1 infection.Annals of Internal Medicine126946954
- 6. Adolescents. PoAGfAa (2009) Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. Department of Health and Human Services. Adolescents. PoAGfAa2009Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. Department of Health and Human Services.Available: http://www.aidsinfo.nih.gov/ContentFiles/AdultandAdolescentGL.pdf. Accessed 2010 Dec 6. Available: http://www.aidsinfo.nih.gov/ContentFiles/AdultandAdolescentGL.pdf. Accessed 2010 Dec 6.
- 7. UNAIDS (2010) Report on the Global AIDS Epidemic. UNAIDS2010Report on the Global AIDS Epidemic.Available: http://www.unaids.org/globalreport/Global_report.htm. Accessed 2012 Feb 3. Available: http://www.unaids.org/globalreport/Global_report.htm. Accessed 2012 Feb 3.
- 8. Deuffic-Burban S, Losina E, Wang B, Gabillard D, Messou E, et al. (2007) Estimates of opportunistic infection incidence or death within specific CD4 strata in HIV-infected patients in Abidjan, Cote d'Ivoire: impact of alternative methods of CD4 count modelling. European Journal of Epidemiology 22: 737–744.S. Deuffic-BurbanE. LosinaB. WangD. GabillardE. Messou2007Estimates of opportunistic infection incidence or death within specific CD4 strata in HIV-infected patients in Abidjan, Cote d'Ivoire: impact of alternative methods of CD4 count modelling.European Journal of Epidemiology22737744
- 9. Jaffar S, Grant AD, Whitworth J, Smith PG, Whittle H (2004) The natural history of HIV-1 and HIV-2 infections in adults in Africa: a literature review. Bulletin of the World Health Organization 82: 462–469.S. JaffarAD GrantJ. WhitworthPG SmithH. Whittle2004The natural history of HIV-1 and HIV-2 infections in adults in Africa: a literature review.Bulletin of the World Health Organization82462469
- 10. Morgan D, Malamba SS, Maude GH, Okongo MJ, Wagner HU, et al. (1997) An HIV-1 natural history cohort and survival times in rural Uganda. AIDS 11: 633–640.D. MorganSS MalambaGH MaudeMJ OkongoHU Wagner1997An HIV-1 natural history cohort and survival times in rural Uganda.AIDS11633640
- 11. Mekonnen Y, Geskus RB, Hendriks JC, Messele T, Borghans J, et al. (2005) Low CD4 T cell counts before HIV-1 seroconversion do not affect disease progression in Ethiopian factory workers. J Infect Dis 192: 739–748.Y. MekonnenRB GeskusJC HendriksT. MesseleJ. Borghans2005Low CD4 T cell counts before HIV-1 seroconversion do not affect disease progression in Ethiopian factory workers.J Infect Dis192739748
- 12. Meyer LCM-L, Nagy Z, Venet A, Deveau C, Pacanovski J, et al. (2007) Low CD4 T cell counts in sub-Saharan African subjects enrolled at the time of HIV-1 primary infection in the French ANRS PRIMO cohort. LCM-L MeyerZ. NagyA. VenetC. DeveauJ. Pacanovski2007Low CD4 T cell counts in sub-Saharan African subjects enrolled at the time of HIV-1 primary infection in the French ANRS PRIMO cohort.Proceedings of the 4th IAS conference on HIV pathogenis, treatment and prevention. July 22–25, 2007 ed. Proceedings of the 4th IAS conference on HIV pathogenis, treatment and prevention. July 22–25, 2007 ed.
- 13. Keller M, Lu Y, Lalonde RG, Klein MB (2009) Impact of HIV-1 viral subtype on CD4+ T-cell decline and clinical outcomes in antiretroviral naive patients receiving universal healthcare. AIDS 23: 731–737.M. KellerY. LuRG LalondeMB Klein2009Impact of HIV-1 viral subtype on CD4+ T-cell decline and clinical outcomes in antiretroviral naive patients receiving universal healthcare.AIDS23731737
- 14. Lewden C, Thiebaut R, Boufassa F, Coulibaly A, Malateste K, et al. (2010) Comparison of Early CD4 T-Cell Count in HIV-1 Seroconverters in Cote d'Ivoire and France: The ANRS PRIMO-CI and SEROCO Cohorts. JAIDS-Journal of Acquired Immune Deficiency Syndromes 53: 260–265.C. LewdenR. ThiebautF. BoufassaA. CoulibalyK. Malateste2010Comparison of Early CD4 T-Cell Count in HIV-1 Seroconverters in Cote d'Ivoire and France: The ANRS PRIMO-CI and SEROCO Cohorts.JAIDS-Journal of Acquired Immune Deficiency Syndromes53260265
- 15. Porter K, Babiker A, Walker S, Darbyshire J, Gill N, et al. (2000) Effect of ignoring the time of HIV seroconversion in estimating changes in survival over calendar time in observational studies: results from CASCADE. AIDS 14: 1899–1906.K. PorterA. BabikerS. WalkerJ. DarbyshireN. Gill2000Effect of ignoring the time of HIV seroconversion in estimating changes in survival over calendar time in observational studies: results from CASCADE.AIDS1418991906
- 16. Anon (1992) 1993 revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR Recomm Rep 41: 1–19.Anon19921993 revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults.MMWR Recomm Rep41119
- 17. Bhaskaran K, Hamouda O, Sannes M, Boufassa F, Johnson AM, et al. (2008) Changes in the risk of death after HIV seroconversion compared with mortality in the general population. JAMA 300: 51–59.K. BhaskaranO. HamoudaM. SannesF. BoufassaAM Johnson2008Changes in the risk of death after HIV seroconversion compared with mortality in the general population.JAMA3005159
- 18. Minga A, Danel C, Abo Y, Dohoun L, Bonard D, et al. (2007) 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 85: 116–123.A. MingaC. DanelY. AboL. DohounD. Bonard2007Progression to WHO criteria for antiretroviral therapy in a 7-year cohort of adult HIV-1 seroconverters in Abidjan, Cote d'Ivoire.Bull World Health Organ85116123
- 19. Price MA, Wallis CL, Lakhi S, Karita E, Kamali A, et al. (2011) Transmitted HIV Type 1 Drug Resistance Among Individuals with Recent HIV Infection in East and Southern Africa. AIDS Res Hum Retroviruses 27: 5–12.MA PriceCL WallisS. LakhiE. KaritaA. Kamali2011Transmitted HIV Type 1 Drug Resistance Among Individuals with Recent HIV Infection in East and Southern Africa.AIDS Res Hum Retroviruses27512
- 20. Morrison CS, Richardson BA, Mmiro F, Chipato T, Celentano DD, et al. (2007) Hormonal contraception and the risk of HIV acquisition. AIDS 21: 85–95.CS MorrisonBA RichardsonF. MmiroT. ChipatoDD Celentano2007Hormonal contraception and the risk of HIV acquisition.AIDS218595
- 21. Morrison CS, Demers K, Kwok C, Bulime S, Rinaldi A, et al. (2010) Plasma and cervical viral loads among Ugandan and Zimbabwean women during acute and early HIV-1 infection. AIDS 24: 573–582.CS MorrisonK. DemersC. KwokS. BulimeA. Rinaldi2010Plasma and cervical viral loads among Ugandan and Zimbabwean women during acute and early HIV-1 infection.AIDS24573582
- 22. Phillips AN, Lee CA, Elford J, Janossy G, Kernoff PBA (1992) The Cumulative Risk of Aids as the Cd4 Lymphocyte Count Declines. Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology 5: 148–152.AN PhillipsCA LeeJ. ElfordG. JanossyPBA Kernoff1992The Cumulative Risk of Aids as the Cd4 Lymphocyte Count Declines.Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology5148152
- 23. Laird NM, Ware JH (1982) Random-Effects Models for Longitudinal Data. Biometrics 38: 963–974.NM LairdJH Ware1982Random-Effects Models for Longitudinal Data.Biometrics38963974
- 24. Taylor JMG, Law N (1998) Does the covariance structure matter in longitudinal modelling for the prediction of future CD4 counts? Statistics in Medicine 17: 2381–2394.JMG TaylorN. Law1998Does the covariance structure matter in longitudinal modelling for the prediction of future CD4 counts?Statistics in Medicine1723812394
- 25. Laird NM (1988) Missing data in longitudinal studies. Stat Med 7: 305–315.NM Laird1988Missing data in longitudinal studies.Stat Med7305315
- 26. Touloumi G, Pocock SJ, Babiker AG, Darbyshire JH (1999) Estimation and comparison of rates of change in longitudinal studies with informative drop-outs. Statistics in Medicine 18: 1215–1233.G. TouloumiSJ PocockAG BabikerJH Darbyshire1999Estimation and comparison of rates of change in longitudinal studies with informative drop-outs.Statistics in Medicine1812151233
- 27. Pantazis N, Touloumi G (2010) Analyzing longitudinal data in the presence of informative drop-out: The jmre1 command. Stata Journal 10: 226–251.N. PantazisG. Touloumi2010Analyzing longitudinal data in the presence of informative drop-out: The jmre1 command.Stata Journal10226251
- 28. Urassa W, Bakari M, Sandstrom E, Swai A, Pallangyo K, et al. (2004) Rate of decline of absolute number and percentage of CD4 T lymphocytes among HIV-1-infected adults in Dar es Salaam, Tanzania. AIDS 18: 433–438.W. UrassaM. BakariE. SandstromA. SwaiK. Pallangyo2004Rate of decline of absolute number and percentage of CD4 T lymphocytes among HIV-1-infected adults in Dar es Salaam, Tanzania.AIDS18433438
- 29. Muller V, von Wyl V, Yerly S, Boni J, Klimkait T, et al. (2009) African descent is associated with slower CD4 cell count decline in treatment-naive patients of the Swiss HIV Cohort Study. AIDS 23: 1269–1276.V. MullerV. von WylS. YerlyJ. BoniT. Klimkait2009African descent is associated with slower CD4 cell count decline in treatment-naive patients of the Swiss HIV Cohort Study.AIDS2312691276
- 30. Katubulushi M, Zulu I, Yavwa F, Kelly P (2005) Slow decline in CD4 cell count in a cohort of HIV-infected adults living in Lusaka, Zambia. AIDS 19: 102–103.M. KatubulushiI. ZuluF. YavwaP. Kelly2005Slow decline in CD4 cell count in a cohort of HIV-infected adults living in Lusaka, Zambia.AIDS19102103
- 31. Tollerud DJ, Clark JW, Brown LM, Neuland CY, Pankiw-Trost LK, et al. (1989) The influence of age, race, and gender on peripheral blood mononuclear-cell subsets in healthy nonsmokers. J Clin Immunol 9: 214–222.DJ TollerudJW ClarkLM BrownCY NeulandLK Pankiw-Trost1989The influence of age, race, and gender on peripheral blood mononuclear-cell subsets in healthy nonsmokers.J Clin Immunol9214222
- 32. Troude P, Chaix ML, Tran L, Deveau C, Seng R, et al. (2009) No evidence of a change in HIV-1 virulence since 1996 in France. AIDS 23: 1261–1267.P. TroudeML ChaixL. TranC. DeveauR. Seng2009No evidence of a change in HIV-1 virulence since 1996 in France.AIDS2312611267
- 33. Lovvorn AE, Patnaik P, Walker CJ, Kwok C, Van Der Pol B, et al. (2010) Variations in CD4 cell counts among HIV-uninfected and infected women in Uganda and Zimbabwe. Int J STD AIDS 21: 342–345.AE LovvornP. PatnaikCJ WalkerC. KwokB. Van Der Pol2010Variations in CD4 cell counts among HIV-uninfected and infected women in Uganda and Zimbabwe.Int J STD AIDS21342345
- 34. Pisell TL, Hoffman IF, Jere CS, Ballard SB, Molyneux ME, et al. (2002) Immune activation and induction of HIV-1 replication within CD14 macrophages during acute Plasmodium falciparum malaria coinfection. AIDS 16: 1503–1509.TL PisellIF HoffmanCS JereSB BallardME Molyneux2002Immune activation and induction of HIV-1 replication within CD14 macrophages during acute Plasmodium falciparum malaria coinfection.AIDS1615031509
- 35. Crowe SM, Carlin JB, Stewart KI, Lucas CR, Hoy JF (1991) Predictive Value of Lymphocyte-Cd4 Numbers for the Development of Opportunistic Infections and Malignancies in Hiv-Infected Persons. Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology 4: 770–776.SM CroweJB CarlinKI StewartCR LucasJF Hoy1991Predictive Value of Lymphocyte-Cd4 Numbers for the Development of Opportunistic Infections and Malignancies in Hiv-Infected Persons.Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology4770776
- 36. WHO (2011) Guidelines for intensified TB case-finding and INH preventive therapy for people living with HIV in resource-constrained settings. WHO2011Guidelines for intensified TB case-finding and INH preventive therapy for people living with HIV in resource-constrained settings.Available: http://www.who.int/hiv/pub/tb/9789241500708/en/index.html. Accessed 2012 Feb 3. Available: http://www.who.int/hiv/pub/tb/9789241500708/en/index.html. Accessed 2012 Feb 3.
- 37. Schiffer V, Deveau C, Meyer L, Iraqui I, Nguyen-Wartel A, et al. (2004) Recent changes in the management of primary HIV-1 infection: results from the French PRIMO cohort. HIV Med 5: 326–333.V. SchifferC. DeveauL. MeyerI. IraquiA. Nguyen-Wartel2004Recent changes in the management of primary HIV-1 infection: results from the French PRIMO cohort.HIV Med5326333
- 38. Lodi S, Phillips A, Touloumi G, Pantazis N, Bucher HC, et al. (2010) CD4 decline in seroconverter and seroprevalent individuals in the precombination of antiretroviral therapy era. AIDS 24: 2697–2704.S. LodiA. PhillipsG. TouloumiN. PantazisHC Bucher2010CD4 decline in seroconverter and seroprevalent individuals in the precombination of antiretroviral therapy era.AIDS2426972704