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Predictors of Long-Term Increase in CD4+ Cell Counts in Human Immunodeficiency Virus-Infected Patients Receiving a Protease Inhibitor-Containing Antiretroviral Regimen

  1. Vincent LeMoing1,3,
  2. Rodolphe Thiébaut3,
  3. Geneviéve Chêne3,
  4. Catherine Leport1,
  5. Valérie Cailleton5,
  6. Christian Michelet6,
  7. Hervé Fleury4,
  8. Serge Herson2,
  9. François Raffi7 and
  10. for the APROCO Study Group
  1. 1Service des Maladies Infectieuses et Tropicales, Hôpital Bichat-Claude Bernard
  2. 2Service de Médecine Interne, Hôpital de la Salpêpitaltrièpitalre, Paris
  3. 3Institut National pour la Santèet la Recherche Médicale Unité 330
  4. 4Laboratoire de Virologie, Hôpital Pellegrin, Bordeaux
  5. 5Institut National pour la Santé et la Recherche Médicale Unité 379, Marseille
  6. 6Service de Médecine Interne, Hôpital Pontchaillou, Rennes
  7. 7Service des Maladies Infectieuses, Hôtel-Dieu, Nantes, France
  1. bReprints or correspondence: Dr. François Raffi, Hôtel Dieu, Service de Médecine Interne B, 44093 Nantes, France.

  1. Presented in part: 8th Conference on Retroviruses and Opportunistic Infections, Chicago, February 2001 (abstract 432).

 
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Abstract

The temporal relationships between plasma human immunodeficiency virus (HIV) RNA levels and evolution of CD4+ cell counts was studied, using a 2 slope longitudinal mixed model, in 988 patients prospectively enrolled at the initiation of a protease inhibitor-containing regimen of antiretroviral therapy. The short-term slope (baseline through month 4) for mean change in CD4+ cell count was +21.2 cells/mm3/month, and the long-term slope (month 4 through month 24) was +5.5 cells/mm3/month. Compared with results from patients without viral response, the long-term slope was 2.5 cells/mm3/month higher in patients who had plasma HIV RNA levels of <500 copies/mL at month 4 (P < .001). It was significantly lower after a rebound in plasma HIV RNA level to ⩾500 copies/mL (P < .0001), varied according to plasma HIV RNA level at the time of rebound, and was negative only when the plasma HIV RNA level at rebound was ⩾10,000 copies/mL. If CD4+ cell counts can remain elevated despite virologic treatment failure, such a discrepant response may be transient in patients who have a high plasma HIV RNA level at the time of treatment failure.

Although definitive eradication of human immunodeficiency virus (HIV) from an individual is not currently achievable, the main goal of highly active antiretroviral therapy (HAART) in HIV-infected patients is to maintain a durable protection against the development of HIV-related complications. Achievement of this goal probably is determined principally by a long-term increase in CD4+ cell counts [1–4], which, in turn, is strongly associated with long-term maintenance of a significant decrease in plasma HIV RNA levels [5–10]. Moreover, the highest increase in CD4+ cell counts is observed in patients in whom plasma HIV RNA levels of <500 copies/mL are maintained for the longest periods of time [9, 11]. However, such a sustained and complete virologic response is not possible for many patients [12, 13], and therapeutic alternatives are still sparse for patients who experience virologic treatment failure [14]. The evidence that a continuous increase in CD4+ cell countsmay be observed inmany [4, 15–17], and perhaps most [9], patients in whom virologic treatment failure is documented is, therefore, of great interest, because most of these patients would probably continue to benefit clinically from HAART despite virologic treatment failure.

The frequency of such a discrepancy between virologic and immunologic responses is highly variable across studies, partly because of differences in the definitions of immunologic and virologic treatment failure [9]. For example, the choice to use a threshold of increase in CD4+ cell counts to discriminate immunologic response and failure is somewhat arbitrary. Moreover, a threshold plasma HIV RNA level above which CD4+ cell counts would further decrease in patients experiencing virologic failure of HAART could not be determined in other studies, possibly because these studies involved an insufficient number of subjects or lacked statistical modeling of data.

To answer some of these pending questions by studying the temporal relationships between plasma HIV RNA levels and immunologic response while subjects were receiving HAART, we analyzed the predictors of long-term increase in CD4+ cell counts in a large cohort of HIV-infected patients at the initiation of a protease inhibitor (PI)-containing antiretroviral regimen.

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Patients and Methods

Patients. The APROCO (Antiprotéase Cohort; Agence Nationale de Recherches sur le SIDA-EP11) Study is a prospective observational study that is ongoing in 47 clinical centers in France and is aimed at describing the virologic, immunologic, and clinical effects of PI therapy in the context of routine care of patients with HIV infection. In total, 1281 HIV-1-infected patients were enrolled in the study from May 1997 through June 1999 at the initiation of their first PI-containing antiretroviral regimen. Standardized clinical and biological data, including measurement of CD4+ cell counts and plasma HIV RNA levels, were collected at baseline (month 0 [M0]), after 1 and 4 months of PI therapy, and every 4 months thereafter. CD4+ cell counts were measured prospectively by standardized flow cytometry. All plasma HIV RNA levels were measured prospectively by the assay routinely available in each center. Three assays are approved in France: reversetranscription polymerase chain reaction (Amplicor; Roche), branched DNA (Quantiplex; Chiron), and nucleic acid sequence-based amplification (Nasba; Organon Technika), with lower limits of HIV-1 RNA detection of 20–500 copies/mL.

Definitions. “Early virologic response” was defined as a plasma HIV RNA level of <500 copies/mL atM4, regardless of which assay was used for quantification of plasma HIV RNA [18]. “Virologic rebound” was defined as the first occurrence of an increase in the plasma HIV RNA level to ⩾500 copies/mL after early virologic response had been seen. A self-administered questionnaire with questions about adherence to therapy was completed by each patient on the same day that blood samples were obtained for plasma HIV RNA measurement at M1 and M4 and then every 8 months thereafter. Assessment of adherence was based on comparison of the number of pills of the antiretroviral drugs that the patient reported having taken during the 4 days before the visit and the number of pills that the patient was scheduled to have taken. This quantitative assessment was corrected by 4 qualitative questions concerning adherence during the previous 4 days and the previous weekend. In brief, adherence was considered to be “high” at a given visit if the patient reported taking 100% of the scheduled pills, claimed to have followed therapy completely, did not skip any dose during the weekend, and never modified the prescribed schedule; “low” if the patient's reported intake was <80% of scheduled pills or if the patient claimed to have followed therapy partially or not at all; and “moderate” in other instances [19]. Patients who did not complete the questionnaire were classified as having “indeterminate” adherence to therapy.

Statistical analysis. To ensure that estimated slopes would be based on a sufficient number of CD4+ cell count measurements and that early virologic response was assessed for each patient, only patients for whom both plasma HIV RNA level and CD4+ cell count measurements at M0, M1, and M4 and ⩾1 measurement of CD4+ cell count thereafter had been made were included in the statistical analysis. In an initial descriptive approach, the median variations in CD4+ cell counts at short term (between M0 and M4) and at long term (between M4 and M24) were calculated according to variables of interest: baseline characteristics, virologic response at M4, selfreported adherence at M4, occurrence of a virologic rebound in patients who displayed early virologic response, and plasma HIV RNA level at the time of virologic rebound. We chose theM4 visit as the cutoff point between short-term and long-term evolution of CD4+ cell counts, because the reconstitution of the pool of naive CD4+ cells begins at approximately this time [20] and because it has been shown elsewhere that a minimum duration of increase in CD4+ cell counts of 4 months is necessary to ensure that protective immune restoration occurs [1].

For the purpose of multivariate analysis and to investigate possible changes in the slopes of CD4+ cell counts over time, we used a mixed longitudinal linear model. This model allows description of the variability of the slopes of CD4+ cell counts over time, as follows: CD4ij = α0 + α1 min(tij, τ) + α2(tij−τ)Itij⩾τ + b0i + b1i min (tij, τ) + b2i (tij−τ)Itij⩾τ+eij , where min(tij,τ) is the minimum between tij and τ, Itij⩾τ = 1 when tij is ⩾ τ, and Itij⩾ τ = 0 otherwise [21].

In this model, CD4ij is the jth measurement of CD4+ cell counts for the subject i; tij represents the time elapsed between M0 and the date of the CD4+ cell count measurement; α0, α1, and α2 are the fixed effects; b0i, b1i, and b2i are the random effects; and eij is the normally distributed residual error. The population short-termslope (before τ = M4) was estimated by â1 and the population long-term slope (after τ = M4) by â2. The effect of fixed explanatory variables (baseline characteristics, virologic response at M4, and adherence at M4) on short-term and long-term slopes of CD4+ cell counts were calculated by estimating and testing interactions between these covariates and each of the 2 fixed slopes. Variables associated with short-term or long-term slope in univariate analysis with P< .25 were eligible for multivariate analysis. A backward procedure was used to eliminate nonsignificant variables (P>.05) from the initial multivariate model.

To assess whether occurrence of virologic rebound in patients with early virologic response was followed by an inflection of the long-term slope, we added to the multivariate model an interaction between the long-termslope and a time-dependent indicator of virologic rebound with 3 levels: 1 level for patients who did not have early virologic response; 1 level for patients who had early virologic response, before occurrence of a virologic rebound, as well as for patients who never experienced rebound; and 1 level for data obtained at the time of potential rebound and thereafter. We also allowed a change in the long-term slope that was dependent on the level of plasma HIV RNA at the time of rebound.

For the selection of randomand fixed effects, as well as the choice of the better cutoff point or transformation of variables, models were compared by use of the likelihood ratio statistical method in case of embedded models and the Akaike information criterion otherwise. The Akaike criterion is calculated as −2L + 2k, where L is the loglikelihood and k is the number of parameters in the model. The better the fit of the model, the higher the likelihood and the lower the Akaike information criterion [22]. Normality of distribution of residuals of the final multivariate model was graphically checked. All statistical analyses were done with SAS software (version 8.0; SAS Institute). For computation of linear mixed models, we used the PROC MIXED procedure.

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Results

Table 1 summarizes the main characteristics at M0, M1, and M4 of the 988 patients retained for further analyses among the 1281 enrolled in the cohort. Reasons for exclusion were as follows: missing CD4+ cell count data at M0, M1, or M4 (n = 190); missing plasma HIV RNA level data at M0, M1, or M4 (n = 62); and no CD4+ cell count measurement after M4 (n = 31). Most patients were men between 30 and 40 years of age. More than 40% of them were naive of antiretroviral therapy at enrollment into the cohort, and most had early- or midstage HIV infection (relatively high CD4+ cell counts and few diagnoses of AIDS).

Figure 1
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Figure 1

Median increase in CD4+ cell count (observed values) since baseline at each follow-up visit, according to presence or absence of early virologic response (plasma human immunodeficiency virus [HIV] RNA level of <500 copies/mL at month 4 [M4]) and occurrence of further virologic rebound (increase in plasma HIV RNA level of ⩾500 copies/mL in patients with early response).

Table 1
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Table 1

Baseline characteristics, immunologic and virologic response, and adherence to therapy for 988 human immunodeficiency virus (HIV)-positive patients receiving protease inhibitor-containing therapy.

Median follow-up was 23 months (interquartile range [IQR], 17–25 months). CD4+ cell counts were measured at the M12 visit for 901 patients (91%) and at theM24 visit for 534 patients (54%). Overall, the median increase in CD4+ cell counts since M0 was 81 cells/mm3 at M4 (IQR, 21–159 cells/mm3), 143 cells/ mm3 at M12 (IQR, 58–241 cells/mm3), and 186 cells/mm3 at M24 (IQR, 73–322 cells/mm3). Early virologic response (plasma HIV RNA level of <500 copies/mL atM4) was observed in 786 patients (80%), among whom 248 (32%) had a further virologic rebound. The median plasma HIV RNA level was 3.32 log10 copies/mL at the time of virologic rebound (n = 248), <1000 copies/mL in 55 patients (22%), 1000–4999 copies/mL in 110 (44%), 5000–9999 copies/mL in 22 (9%), and ⩾10,000 copies/ mL in 61 (25%). The level of plasma HIV RNA at the time of rebound was ⩾1 log10 copies/mL less than the M0 value for 113 patients (46%) and <1 log10 copies/mL less than the M0 value for 135 patients (54%).

Median increases in CD4+ cell counts between M0 and M4, between M4 and M12, and between M4 and M24, according to various factors are shown in table 2. Long-term increase in CD4+ cell counts was higher in patients who achieved early virologic response and, among them, in those who did not have virologic rebound during follow-up. At M24, the increases in CD4+ cell counts appeared to be similar among those without early virologic response and those with early virologic response but a further virologic rebound (figure 1). Moreover, at M24, among patients who had a virologic rebound, the increase in CD4+ cell counts since M4 was negative or null in those patients with plasma HIV RNA levels of ⩾5000 copies/mL at the time of rebound (table 2). A longitudinal mixed model without explanatory covariates estimated the following CD4+ cell count slopes for the 988 patients: short-term slope (before M4), +21.2 cells/mm3/ month (95% confidence interval [CI], +18.7 to +23.8 cells/mm3/ month); long-term slope (after M4), +5.5 cells/mm3/month (95% CI, +5.0 to +6.1 cells/mm3/month). In univariate analysis (data not shown), the short-term slope of CD4+ cell counts (before M4) was significantly (P < .05) higher inwomen, in patientswith baseline CD4+ cell counts of <500 cells/mm3, in patients with higher baseline plasma HIV RNA levels, in antiretroviral-naive patients, and in patientswho were seronegative for hepatitis C virus (HCV) coinfection. The long-term slope of CD4+ cell counts was not associated with baseline characteristics, including antiretroviral drugs prescribed at M0, except that it was significantly lower in patients with baseline CD4+ cell counts of 200–500 cells/ mm3. It tended to be higher in antiretroviral-naive patients (P = .05) and in patients who self-reported as highly adherent at M4 (P = .09). Moreover, the long-term slope was associated significantly with the decrease in plasma HIV RNA levels between M0 and M4 (P < .001): it was 0.8 cells/mm3/month higher (95% CI, 0.3–1.3 cells/mm3/month) for each decrease of 1 log10 copies/mL in plasma HIV RNA between M0 and M4.

Table 2
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Table 2

Observed increase in CD4+ cell counts since baseline (month 0 [M0]) at M4, M12, and M24 in 988 human immunodeficiency virus (HIV)-positive patients, according to M0 characteristics, adherence to therapy at M4, early virologic response, and occurrence of virologic rebound.

The final multivariate model of the evolution of CD4+ cell counts over time, taking into account factors measured until M4, is shown in table 3. Age, Centers for Disease Control and Prevention HIV infection stage [23], previous antiretroviral therapy, PI prescribed at baseline, and adherence to therapy were included in the initial model but were not significantly associated with an increase in CD4+ cell counts and thus were eliminated to yield this final model. Short-term increase in CD4+ cell counts was associated positively with baseline plasma HIV RNA level; it was higher in patients with CD4+ cell counts of 200–500 cells/mm3, in women, and in antiretroviralnaive patients and was lower in patients who were seropositive for HCV. The adjusted long-term slope of CD4+ cell counts was higher in patients with baseline CD4+ cell counts of ⩾500 cells/ mm3, as well as in patients with plasma HIV RNA levels of <500 copies/mL at M4. None of the other factors measured until M4 was associated with long-term increase in CD4+ cell counts. When virologic response at M4 was entered in the model as a continuous variable (decrease in plasma HIV RNA level between M0 and M4) instead of a dichotomous variable (plasma HIV RNA level of <500 copies/mL), it was no longer significantly associated with the long-term slope, which was 0.6 cells/mm3/month higher (95% CI, −0.2 to +1.5 cells/mm3/ month; P = .16) for each decrease of 1 log10 copies/mL in plasma HIV RNA level between M0 and M4. Moreover, this latter model fitted the data less well than did the model including dichotomous early virologic response. This suggests that, early during therapy and taking into account the initial plasma HIV RNA level, long-term increase in CD4+ cell counts may be predicted better by variation in plasma HIV RNA level around a threshold level than by the relative decrease in plasma HIV RNA level compared with pretherapy values.

Table 3
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Table 3

Multivariate longitudinal modeling of short-term (before month 4 [M4]) and long-term (after M4) slopes of CD4+ cell counts.

Data were best fitted by the adjunction in the model of an inflection of the long-term slope after occurrence of virologic rebound. In this model (model 1), the estimated slope in patients with early virologic response was significantly lower after rebound than before rebound (P < .0001). Two additional models were tested to take into account the level of plasma HIV RNA at the time of virologic rebound (table 4). Likelihood was further increased in these 2 models, compared with model 1. Moreover, all slopes after rebound were significantly lower than slopes before rebound. The likelihood of the model taking into account the absolute plasma HIV RNA level at the time of rebound (model 2) was higher than the likelihood of the model taking into account the difference in plasma HIV RNA level between the time of rebound and the pretherapy value (model 3). This suggests that the evolution of CD4+ cell counts after virologic rebound may be predicted better by the absolute plasma HIV RNA level at the time of rebound than by the variation in plasma HIV RNA levels since baseline. In model 2, which best fitted the data, the estimated adjusted long-term slope remained positive after rebound at plasma HIV RNA levels of 500–5000 copies/ mL, was not significantly different from 0 (P = .12) after rebound at plasma HIV RNA levels of 5000–10,000 copies/mL, and was negative after rebound at plasma HIV RNA levels of ⩾10,000 copies/mL (P = .01 for the comparison with 0). In model 3, the adjusted long-term slope was not significantly different from 0 (P = .06) after occurrence of a rebound at <1 log10 copies/mL from baseline level.

Table 4
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Table 4

Estimated adjusted long-term slopes of CD4+ cell count before and after occurrence of rebound in plasma human immunodeficiency virus (HIV) RNA to ⩾500 copies/mL in patients with plasma HIV RNA levels <500 copies/ mL at month 4 (M4): effect of plasma HIV RNA level at time of rebound and further slope of plasma HIV RNA.

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Discussion

Our analyses, based on a large cohort of patients receiving HAART as part of routine care, confirm that long-termimmunologic response is strongly related to the early achievement and long-term maintenance of a plasma HIV RNA level of <500 copies/mL. They also confirm that discrepancy between immunologic and virologic response is very frequent, because, in the APROCO cohort, most of the patients who did not have early virologic response or had a rebound in plasma HIV RNA level after initial response had a continuous increase in CD4+ cell count during a median follow-up of 23 months. Nevertheless, this increase in CD4+ cell count was significantly attenuated after occurrence of a rebound in plasma HIV RNA of ⩾500 copies/mL. The increase in CD4+ cell count continued only when the plasma HIV RNA level at the time of rebound was <5000 copies/mL; rebound in plasma HIV RNA level of ⩾10,000 copies/mL was followed by a significant decrease in CD4+ cell counts.

Because a short-term increase in CD4+ cell counts is thought to be due mainly to redistribution of trapped cells [20] and because we analyzed the predictors of early immunologic response in a previous study [24], we centered the present study on determinants of long-termincrease in CD4+ cell counts, which mostly is the consequence of generation of new T cells. Our new analyses otherwise yielded some determinants of short-term immunologic response. As in the Swiss HIV cohort study [24], HCV coinfection was associated with a weaker short-term immunologic response in our study. The weaker immunologic response in HCV-coinfected patients may be associated with a worse clinical prognosis [25]. Because HCV replicates in lymphoid tissue in coinfected patients [26], it has been suggested that HCV is directly pathogenic to the immune system [25], but this remains to be demonstrated clearly.

The only baseline characteristic associated with long-term increase in CD4+ cell counts in multivariate analysis was a baseline CD4+ cell count of ⩾500 cells/mm3. This could be explained by a lower frequency of virologic rebound [19] and also by a partial recovery of anti-HIV immunity [27] in such patients.

The association between adherence to therapy and long-term immunologic response observed in univariate modeling and suggested by others [28] was lowered after adjustment for virologic response. This suggests that the association, if any, between adherence and immunologic response is, at least in part, mediated by virologic response. Long-term immunologic response was indeed strongly associated with early virologic response. Moreover, both early (after 4 months of therapy) and later (at the time of virologic rebound) further evolution in CD4+ cell counts was better predicted by variation of plasmaHIVRNAaround a threshold level than by the relative decrease in plasma HIV RNA level compared with pretherapy values. This is somewhat contradictory to the results of 2 previous studies that emphasized the role of the relative decrease in plasma HIV RNA [5, 9]. These studies assessed the relationships between long-term immunologic response and the mean of all plasma HIV RNA levels measured during the whole course of therapy and thus were not designed to study the temporal relationships between a given plasma HIV RNA level and the subsequent evolution of CD4+ cell counts.

Rebounds in plasma HIV RNA seem to be deleterious for further increase in CD4+ cell counts. This appears to be true even when virologic rebound is strictly defined, as in the present study, in which transient increases in plasma HIV RNA were included in the definition of rebound, and regardless of the level of plasma HIV RNA at time of rebound. This is in keeping with the results of previous studies [9, 11] and confirms that the ideal objective of HAART is to maintain plasma HIV RNA levels at the lowest possible level for the longest duration possible [29]. Our study provides additional information applicable to those many patients in whom very low plasma HIV RNA levels cannot be maintained in the long term. In these patients, until plasma HIV RNA increases to 5000–10,000 copies/mL, an increase in CD4+ cell counts may be expected to continue, although at a weaker rate. Our results thus confirm and explain those from another cohort of patients treated with various antiretroviral regimens [30]. In this cohort, clinical outcome was not different in patients with undetectable plasma HIV RNA and in those with intermediate virologic response to therapy with plasma HIV RNA levels of <5000 copies/mL. It thus seems to be possible to delay changing the therapy for such patients, specifically, while awaiting the availability of new therapeutic options or to spare drug classes. This conservative approach is associated with the risk of selecting and accumulating resistance mutations in the still-replicating viruses [31]. Moreover, “salvage” regimens are more likely to be effective if they are initiated at a low level of viral replication [14]. Nevertheless, a change in therapy may be more urgently needed for patients who have a rebound in plasma HIV RNA level of ⩾10,000 copies/mL, because these patients seem to have a subsequent decrease in CD4+ cell counts that is not far from the decay observed before the advent of HAART [32]. Longer follow-up will help to determine whether this decay in CD4+ cell counts, which was important enough to rapidly erase the beneficial effect of transient viral response after M4, as shown by our descriptive approach, will also subsequently erase the benefits of early virologic response. It is, however, necessary to emphasize that adherence to therapy should be assessed at the time of rebound in patients having such high-intensity virologic rebounds, because most of them may be poorly adherent [33].

We believe that modeling slopes of CD4+ cell counts had 2 major advantages in this study. First, it was not necessary to choose an arbitrary threshold of CD4+ cell count increase to define response. Second, it allowed for the study of the temporal relationships between occurrence and intensity of virologic treatment failure and subsequent evolution of CD4+ cell counts, which, to our knowledge, has not been done previously. Longitudinal modeling also allowed the assessment of evolution of CD4+ cell counts without choosing arbitrary time points [15]. Patients who missed visits after M4, who may be at a higher risk of being poorly adherent and having therapy failure [13], thus were included in the analyses. This may have improved the generalizability of our results. The modeling performed in the present study, however, has some limitations. We had to select patients without missing values during the first 4 months of follow-up, which could have led to selection biases. However, we believe that these potential biases were not important enough to invalidate our results. Actually, when we performed analyses for all 1240 patients with ⩾1 follow-up visit (data not shown), assuming that all patients who did not have a measure of plasma HIV RNA atM4 had not responded to therapy, very similar results were found. Because we had to assume that the plasma HIV RNA level did not vary after virologic rebound, we could not take into account the evolution of plasma HIV RNA levels after rebound. For example, we were not able to detect whether return of plasma HIV RNA level to <500 copies/mL, for example, after changes in antiretroviral therapy or intervention to reinforce adherence, was associated with a further modification of the longterm slope of CD4+ cell counts. Longer follow-up would be necessary to study the relationships between CD4+ cell counts and plasma HIV RNA levels after occurrence of virologic rebound, as well as in patients who did not have early virologic response.

In summary, if CD4+ cell counts can remain elevated despite virologic treatment failure, such a discrepant response may be transient in patients who have a high plasma HIV RNA level at the time of failure, because most of them subsequently have a significant decrease in CD4+ cell counts. Thus, because the so-called discrepant response is probably transient in most patients with high plasma HIV RNA levels and because “salvage” therapy is effective mostly for patients with low plasma HIV RNA levels [14], it seems to be worth considering changing therapy for an adherent patient as soon as the plasma HIV RNA level increases above the detection threshold. When the plasma HIV RNA level remains low and therapeutic alternatives are sparse or absent, HAART may induce a strong and persistent immunologic response. Longer follow-up will probably help to confirm whether this important practical issue is still relevant in the long term, notably in terms of clinical progression.

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APROCO Study Group

Scientific Committee. Steering Committee: C. Leport and F. Raffi, principal investigators; G. Chêne and R. Salamon,methodology; J.-P. Moatti and J. Pierret, virology; F. Brun-Vézinet and H. Fleury, social sciences; and G. Peytavin, pharmacology. Other members: D. Costagliola, P. Dellamonica, C. Katlama, L.Meyer,M.Morin, D. Sicard, A. Sobel, and F.Vincent-Ballereau.

Events Validation Committee. M. Dupon, X. Duval, V. Le Moing, B. Marchou, T. May, P. Morlat, C. Rabaud, and A. Waldner-Combernoux.

Observers. F. Agid, F. Bourdillon, J. F. Delfraissy, J. Dormont, J. Y. Lacut, Y. Souteyrand, and J. L. Vildé.

Clinical centers. Amiens (J.-L. Schmit), Angers (J.-M. Chennebault), Belfort (J.-P. Faller), Besançon (J.-M. Estavoyer, P. Laurent, and P. Vuitton), Bordeaux (J. Beylot, M. Dupon, M. Le Bras, and J.-M. Ragnaud), Bourg-En-Bresse (P. Granier), Brest (M. Garré), Caen (C. Bazin), Compiegne (P. Veyssier), Corbeil Essonnes (A. Devidas), Creteil (A. Sobel), Dijon (H. Portier), Garches (C. Perronne), Lagny (P. Lagarde), Libourne (J. Ceccaldi), Lyon (D. Peyramond), Meaux (C. Allard), Montpellier (J. Reynes), Nancy (P. Canton), Nantes (F. Raffi), Nice (J.-P. Cassuto and P. Dellamonica), Orleans (P. Arsac), Paris (E. Bouvet, F. Bricaire, C. Caulin, J. Frottier, S. Herson, J.-C. Imbert, J.-E. Malkin, W. Rozenbaum, D. Sicard, and J.-L. Vildé), Poitiers (B. Becq-Giraudon), Reims (G. Rémy), Rennes (P. Thomas), Saint-Etienne (F. Lucht), Saint Mande (R. Roué), Strasbourg (J.-M. Lang), Toulon (J.-P. de Jaureguiberry), Toulouse (P. Massip), and Tours (P. Choutet).

Data monitoring and analysis. C. Alfaro, C. Barennes, S. Boucherit, V. Cailleton, M. P. Carrieri, C. Deveaud, S. Duran, S. Dutoit, J.-L. Ecobichon, C. Egouy, C. Jadand, V. Journot, R. Lassalle, L. Latour, V. Le Moing, C. Lewden, B. Masquelier, W. Nouioua, G. Palmer, S. Roloff, A. Sangue, M. Savès, B. Spire, M. Souville, J. Surzyn, and R. Winum.

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Footnotes

  • Written informed consent was obtained from patients enrolled in the APROCO Study, and the study was approved by the institutional review board of Cochin-Tarnier Hospital, Paris.

  • Financial support: Agence Nationale de Recherches sur le SIDA (Action Coordonnée no. 7); Association des Professeurs de Pathologie Infectieuse et Tropicale; Abbot; Boerhinger-Ingelheim; Roche; Bristol-Myers Squibb; Merck Dohm Chibret; Glaxo-Smithkline. V.L.M. received a special grant from Bristol-Myers Squibb.

  • ↵a APROCO Study Group members are listed after the text.

  • Received April 2, 2001.
  • Revision received October 12, 2001.
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  1. J Infect Dis. (2002) 185 (4): 471-480. doi: 10.1086/338929
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