Descriptive characteristics of the two groups according to their rate of CD4 cell decline prior to initiation of cART are reported in Table 1. We did not observe any difference in demographic variables between the two groups nor between the class of ART study participants received. Of note, those in the SH group had a higher CD4 cell count and a lower viral load at the start of cART when compared to those in the ST group. Further, whereas the median year of seroconversion among the SH group was 1996, it was 1999 among those in the ST group.
Precombination antiretroviral therapy CD4 cell decline and immunological response in the first year after starting combination antiretroviral therapy
A median of four (range: 2–32) CD4 cell count determinations was available from each individual in the first year after starting cART; the number of determinations per individual was almost the same in the two groups [median (range) of 4 (2–32) and 4 (2–23) in the SH and ST groups, respectively]. The median time between consecutive determinations was similar between the two groups: median (range) of 2.1 (0.1–10.6) and 2.0 (0.1–10.5) months among the SH and ST groups, respectively.
Applying a random coefficients model, we estimated a lower mean increase in CD4 cell level in the first year of cART (by −45.5 cells, P < 0.001) for those in the SH vs. the ST group. The mean CD4 cell slope in the first year was +9.5 cells/μl per month (95% CI 6.7–12.2) in the SH group and +13.9 cells/μl per month (95% CI 12.9–14.8) in the ST group (P value for test of difference in slopes: < 0.001). After adjusting for other variables that were statistically significant in univariable models (with P values ≤0.05), including the precART CD4 cell count and viral load, HIV-transmission group, year of seroconversion, start of cART during primary infection, class of antiretrovirals and a diagnosis of AIDS before cART (Table 2), those in the SH group continued to demonstrate a smaller increase in CD4 cell counts in the first year after starting cART compared with individuals in the ST group (by −4.4 cells/μl per month, P < 0.001; see Table 2). Note that the model reported in Table 2 does not include adjustment for HCV, as information on HCV status was not available for all participants. However, when the analyses were repeated in this subgroup (n = 1 858; 91%), and after adjustment for HCV status, results were similar (data not shown).
A formal test of interaction between the baseline CD4 cell count (as a continuous covariate, per 100 cell/μl increment) and the precART slope group was statistically significant (P < 0.001). For this reason, the multivariable analysis was repeated stratifying the study population by baseline CD4 cell count and the differences in the monthly rate of CD4 cell count over the first year between the ST and SH groups were by −3.5 (P = 0.28), −5.4 (P = 0.02), −3.5 (P = 0.04), −4.2 (P = 0.02), −4.0 (P = 0.11), and −7.4 (P = 0.05) cells/μl among those with baseline CD4 cell counts of 100 or less, 101–200, 201–300, 301–400, 401–500 and more than 500/cells/μl, respectively.
Precombination antiretroviral therapy CD4 cell rate decline as possible determinant of progression to an increase from baseline of at least 50 cells/μl
Separate Kaplan–Meier curves and Cox models were applied for the different levels of baseline CD4 cell count (Fig. 3). Those in the SH group experienced slower attainment of an increase from baseline in CD4 cell count of at least 50 cells/μl; this difference was apparent in every CD4 cell count strata. Crude and adjusted relative hazards of achieving a CD4 cell count increase of at least 50 cells/μl are also shown (Fig. 3). The adjusted relative hazard for this immunological end-point was below 1 in each of the CD4 cell strata, although this was not always statistically significant (Fig. 3). Further, when applying the multivariable Cox model after stratifying by baseline CD4 cell count (same strata of Fig. 3), the relative hazard of achieving an increase of more than 50 cells/μl was 0.70 (95% CI 0.62–0.79) for those in the SH group compared to the ST group.
To our knowledge, this is the first study to consider whether precART CD4 cell decline is associated with immune recovery on cART among ART-naive patients. We found that patients with a steeper precART decline tended to experience faster immune reconstitution once they started cART, independently of baseline CD4 cell count and HIV RNA value.
It is well known that, upon initiation of cART, the reconstitution of the CD4+ T-cell pool characteristically exhibits a biphasic pattern. The initial increase is very rapid, usually observed in the first 4–6 months following treatment [5,14] and likely reflects redistribution of memory cells from lymphoid tissue, as suppression of viral replication causes a reduction in immune activation [15–17]. Previous observations, not including the pretreatment CD4 cell slope, showed that the first phase of CD4 cell increase was predicted only by higher pretreatment viral load, whereas a slower but longer second phase increase was associated with younger age, lower pretreatment CD4 cell count and higher pretreatment viral load . Although immune activation and its reduction are key factors, a high baseline viral load, which determines a high immune activation, is also related to a faster decline of CD4+ T cells probably migrating into the lymphoid tissue. This migration is not only related to a steeper pretreatment CD4 cell slope but also strongly influences the initial phase of the CD4 cell response to cART, consistent with the suggestion that relatively more lymphocytes, including recent thymic emigrants, are sequestered in lymphoid tissue in persons with higher viral loads, leading to greater and faster CD4 cell redistribution after viral suppression [16–18]. Thus, patients with high immune activation (i.e. high viral load and a steep pretreatment CD4 cell slope) may be expected to have more rapid CD4 cell responses on cART.
Progressive CD4 cell depletion, with a disproportionate decline in naive CD4 and CD8 cells, characterizes untreated HIV-1 disease [18,19]. The mechanisms that underlie these changes, and the processes responsible for T-cell reconstitution after cART, remain incompletely understood. Until now, precART CD4 cell declines and cART-induced immune reconstitution have been studied separately [20,21]. Here we show that the dynamics of these two phenomena are correlated. During infection, the immune system and the virus coexist in a precarious balance. The continuous loss of CD4+ T lymphocytes has to be compensated by the production of new cells, in a scenario that is not only extremely dynamic within a given patient, but also influenced by several host and viral factors [22–24]. We considered the slope of CD4 cell in the 2 years before treatment initiation, as this period is likely to be of most relevance to clinicians caring for patients, the majority of whom will not have been diagnosed with HIV at the time of seroconversion. In patients with a steeper precART CD4 decline, immune redistribution could be the leading factor for immune reconstitution. In patients with a lower CD4 cell decline, the dynamic could be completely different, and rather than redistribution, there could be a slow but continuous killing of CD4 cells that, in the first period of treatment, could negatively impact immune reconstitution.
The present study poses several questions about the pathogenesis of HIV infection that cannot be answered with current knowledge. We were not able to evaluate different patterns of qualitative immune reconstitution among the two groups of patients, which may be seen as a limitation. Robbins et al.  have shown that only patients who started cART with a CD4 cell count more than 350 cells/μl are likely to regain normal naive-memory cell ratios. Thus, it is important to study in greater depth, among patients starting treatment, the different populations of CD4+ T cells that are involved in immune recovery. Furthermore, it is crucial to analyse not only the changes in the CD4+ T-cell pool present in peripheral blood, but also those in lymphoid tissues and in key sites such as the gastrointestinal tract.
Although some current and previous treatment guidelines for initiation of cART [7,8] incorporate a rapidly declining CD4 cell count (e.g. >100 cells/μl per year) as one of the conditions that may indicate the need for therapy among ART-naive patients, to our knowledge, no recent clinical trials or cohort studies are available that support this guideline .
It should be noted that the strict inclusion criteria for our analysis (at least two CD4 cell count determinations in the 2 years prior to cART and at least two determinations in the year after starting cART) resulted in the exclusion of a large proportion of patients in CASCADE. Thus, our analyses will be most generalizable to patients who are under very close clinical care.
In conclusion, we unexpectedly found that individuals with a faster rate of CD4 cell loss precART tended to experience better immunological responses when they started cART than those with slower precART CD4 cell declines. The clinical relevance of this finding deserves further investigation.
The authors thank the reviewers for careful comments about statistical methods and interpretations of the results. They thank also Fenicia Vescio and Flavia Chiarotti for helpful discussion.
C.M. ideated the study and contributed to the manuscript. A.C. contributed to the manuscript. C.S. discussed statistical approach and contributed to the manuscript. A.B. discussed statistical approach and contributed to the manuscript. A.DeL. contributed to the manuscript. H.B. contributed to the manuscript. M.F. contributed to the manuscript. K.P. coordinated CASCADE, discussed statistical approach and contributed to the manuscript. G.R. contributed to the manuscript. M.D. discussed statistical approach, performed all statistical analyses and contributed to the manuscript. The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2011) under EuroCoord grant agreement no. 260694. H.C.B. received funding from santésuisse and the Gottfried and Julia Bangerter-Rhyner-Foundation. H.C.B. has received travel grants, honoraria or unrestricted research grants from GlaxoSmithKline, Bristol-Myers-Squibb, Gilead, Janssen, Roche, Abbott, Tibotec, Boehringer-Ingelheim and viiv Healthcare. These companies had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The other authors declare no conflict of interest.
Steering Committee: Julia Del Amo (Chair), Laurence Meyer (Vice Chair), Heiner C. Bucher, Geneviève Chêne, 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, Janet Darbyshire. Clinical Advisory Board: Heiner Bucher, Andrea De Luca, Martin Fisher, Roberto Muga.
Collaborators: Australia: Sydney AIDS Prospective Study and Sydney Primary HIV Infection cohort (John Kaldor, Tony Kelleher, Tim Ramacciotti, Linda Gelgor, David Cooper, Don Smith); Canada: South Alberta clinic (John Gill); Denmark: Copenhagen HIV Seroconverter Cohort (Louise Bruun Jørgensen, Claus Nielsen, Court Pedersen); 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 Kucherer); Greece Greek Haemophilia cohort (Giota Touloumi, Nikos Pantazis, Angelos Hatzakis, Dimitrios Paraskevis, Anastasia Karafoulidou); Italy: Italian Seroconversion Study (Giovanni Rezza, Maria Dorrucci, Claudia Balotta), ICONA cohort (Antonella d'Arminio Monforte, Alessandro Cozzi-Lepri, Andrea De Luca.) The Netherlands: Amsterdam Cohort Studies among homosexual men and drug users (Maria Prins, Jannie van der Helm, Anneke Krol, Hanneke Schuitemaker); Norway: Oslo and Ulleval Hospital cohorts (Mette Sannes, Oddbjorn Brubakk, Anne Eskild, Johan N Bruun); Poland: National Institute of Hygiene (Magdalena Rosinska, Joanna Gniewosz); Portugal: Universidade Nova de Lisboa (Ricardo Camacho); Russia: Pasteur Institute (Tatyana Smolskaya); Spain: Badalona IDU hospital cohort (Roberto Muga, Jordi Tor), Barcelona IDU Cohort (Patricia Garcia de Olalla, Joan Cayla), Madrid cohort (Julia Del Amo, Jorge del Romero), Valencia IDU cohort (Santiago Pérez-Hoyos, Ildefonso Hernandez Aguado); 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 (Valerie Delpech, Sam Lattimore, Gary Murphy, John Parry, Noel Gill), Royal Free Haemophilia cohort (Caroline Sabin, Christine Lee), UK Register of HIV Seroconverters (Kholoud Porter, Anne Johnson, Andrew Phillips, Abdel Babiker, Janet Darbyshire, Valerie Delpech), University College London (Deenan Pillay), University of Oxford (Harold Jaffe).
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Keywords:© 2011 Lippincott Williams & Wilkins, Inc.
combination antiretroviral therapy response; CD4 cell decline; immune reconstitution; seroconverters