a Chelsea and Westminster Hospital, London; b MRC HIV Clinical Trials Centre, London, UK; c University of New South Wales, Sydney, Australia
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Abstract |
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Introduction |
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Two large trials of zidovudine monotherapy in asymptomatic patients with CD4 counts >500 x 106 cells/L (Concorde and the European-Australian Collaborative Group trial (EACG020)) failed to demonstrate any survival benefit with early intervention, 5,12 although both trials found a significant short-term benefit of zidovudine on progression to CDC group IV disease or a CD4 count <350 x 106 cells/L. In the absence of further clinical endpoint studies of antiretroviral therapy in early disease, a current goal is to identify those individuals who, despite asymptomatic disease and a CD4 count >500 x 106 cells/L, are at high risk of disease progression and who might therefore benefit from early intervention. Several observational studies have shown that the rate of CD4 or CD4 per cent decline is strongly predictive of clinical outcome, independent of the baseline or current CD4 cell count, 13,14,15,16and that the additional predictive value of CD4 cell decline is greatest for those with a high CD4 cell count. 15 It has therefore been suggested that individuals with a rapid rate of CD4 lymphocyte decline are a subgroup who may benefit from early initiation of antiretroviral therapy.
Our main objective was to develop a statistical model to determine whether asymptomatic HIV-infected patients with rapid CD4 decline are a subgroup who might benefit from early antiretroviral therapy, relative to those with a slower CD4 decline. Although our analysis was based on data from two randomized placebo-controlled trials of zidovudine monotherapy, 5,12 the same approach is applicable to trials of combination antiretroviral therapy.
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Materials and methods |
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Concorde was a double-blind randomized comparison of two treatment policies, immediate or deferred zidovudine therapy, in asymptomatic HIV infection. 5 Between October 1988 and October 1991, 1749 HIV-infected individuals from 74 centres in the UK, Ireland, and France were randomly allocated to either immediate therapy with zidovudine 250 mg four times daily (n= 877) or matching placebo (n = 872). Participants were offered open zidovudine when they developed AIDS-related complex (ARC) or AIDS, or when their CD4 cell count fell persistently below 500 x 106 cells/L, if the clinician judged that the treatment was indicated. Follow-up was to death or 31 December 1992, and the results of the study were published in April 1994.
The European-Australian Collaborative Group study (EACG020) was a double-blind, placebo-controlled trial of zidovudine treatment in 984 individuals with asymptomatic HIV infection and CD4 cell counts >400 x 106/L. 12 Patients were recruited from 56 centres in Australia and Europe between December 1988 and January 1992, and randomly assigned to receive zidovudine 500 mg twice daily (n = 495) or matching placebo (n = 489). Participants with disease that met the CDC stage IV criteria or whose CD4 cell count dropped to below 350 x 106/L were offered open zidovudine therapy. Follow-up was to death or 31 January 1992, and the results of the study were published in July 1993.
In both trials, T cell subsets were measured by flow cytometry, 4 weeks before entry and at randomization. In Concorde, clinical assessment was carried out every 4 weeks for the first year, and then every 12 weeks. Primary endpoints were survival, progression to AIDS, CDC group IV disease, and severe adverse events. Participants in EACG020 were assessed every 4 weeks until week 24, and every 12 weeks thereafter. The primary endpoint under study was overall disease progression, defined as progression to AIDS, ARC, CDC stage IV disease, or two CD4 cell counts below 350 x 106/L. Clinical events were categorized in both trials according to the CDC 1987 classification. 17 The median duration of follow-up in the published trials was 3.3 years for Concorde and 1.8 years for EACG020. One hundred and twenty-seven individuals (7%) were lost to follow-up in Concorde and 79 (8%) in EACG020. Full details of the trial design, statistical methods, protocol for laboratory measurements, clinical endpoints, and follow-up are available in the reports on the trials. 5,12
Study participants
The analysis reported here is based on a subgroup of 197 patients enrolled into the Concorde trial from three clinical centres (St Stephen's, Charing Cross, and Westminster Hospitals) in London, UK and 105 patients enrolled into EACG020 from two clinical centres (Albion Street and St Vincent's Hospital) in Sydney, Australia. Of these, 193 and 104 participants, respectively, had at least one pre-randomization and post-randomization count recorded, and were therefore eligible for inclusion in our analysis. One hundred and fifty-four patients (100 Concorde, 54 EACG020) were randomized to immediate zidovudine monotherapy (IMM), and 143 (93 Concorde, 50 EACG020) to initial placebo or deferred treatment (DEF). For this analysis, we obtained follow-up data well beyond the period stated in the original trial report, to include clinical events up to 4 November 1996 (69.0 months) for Concorde participants and 31 March 1995 (53.4 months) for EACG020 participants. Additional CD4 cell counts available before randomization and all available counts after randomization were also abstracted from the medical records for our patient subgroup. The baseline CD4 cell count was defined as the mean of all available counts within the 3 months before randomization.
Statistical analysis
For each trial, the baseline characteristics (age, sex, risk group, and CD4 cell count) of the two treatment armsimmediate (IMM) (equivalent to the standard intervention group) or deferred (DEF) (equivalent to the standard placebo group) zidovudine therapywere compared by Student's t-test for age and the chi-squared test for the categorical variables, sex and risk group. The Wilcoxon rank-sum test was used to compare median values for CD4 cell counts.
The individual slopes of the CD4 cell count trajectory before and after randomization were estimated by fitting a mixed linear model, using the statistical package MLn. 18 This has the advantage over the standard least-squares approach in that there is no minimum number of CD4 cell counts required for each patient, since calculation of individual estimates utilizes data from the whole sample. The CD4 cell count profile in the DEF therapy group was assumed to follow a linear decline both before and after randomization with both the intercept (baseline count) and slope varying randomly between individuals. There was no evidence of non-linearity in the CD4 cell count profile in this group. In contrast, in the IMM therapy group, the model assumed that pretreatment linear decline was followed first by an immediate initial rise at the start of therapy and then a linear decline thereafter. We explored alternative timepoints (3, 4 and 6 months) for the transition between the initial CD4 cell rise and subsequent decline in addition to a quadratic function post-randomization, but these did not improve the fit significantly. Because of randomization, the joint distribution of pretreatment slope and baseline count was assumed to be the same in the two treatment groups. The pretreatment slope and baseline count were calculated for each patient. Patients were stratified into groups based on quartiles of their estimated pre-randomization slopes, i.e. (group 1) <25th percentile; (group 2) 25th to 50th percentile; (group 3) 50th to 75th percentile; and (group 4) >75th percentile. The correlation between pretreatment slope and the level of initial CD4 cell rise and the magnitude of change in the rate of CD4 cell decline after treatment were examined in the IMM therapy group.
Disease progression was defined as the development of AIDS, a 50% drop in CD4 count from the baseline level, or death, whichever came first. A Cox proportional hazards model 19 stratified by trial was used to examine the relationship between the previous rate of CD4 cell decline and the risk of disease progression, after adjustment for the baseline CD4 cell count. In this analysis, the pretreatment slope was based only on CD4 cell counts up to the time of randomization. We first tested for interaction (i.e. whether the effect of zidovudine on disease progression varied according to the previous rate of CD4 cell decline) in the Cox proportional hazards model, using an interaction term between pre-randomization decline and treatment, after adjustment for the baseline CD4 cell count. A Cox model was also used to examine whether the magnitude of treatment effect could be explained by the magnitude of change in a patient's rate of CD4 cell decline, where change in rate of CD4 cell decline was defined as the post-minus pre-randomization slope, and was modelled as a time-dependent variable. Since zidovudine is known to have a short-lived benefit, the analysis was repeated using follow-up data up to 1 year only. All analyses were based on an intention-to-treat approach, and all P values presented are two sided. Data were analysed with the use of SAS version 6. 08 (SAS Institute Inc., Cary, NC, USA) and STATA 4.0 (STATA Corporation, College Station, TX, USA).
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Results |
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Table I presents the demographic and laboratory characteristics at randomization in a subset of 297 participants from the two trials. The IMM and DEF group participants within each trial were similar, apart from a lower median baseline CD4 cell count in the IMM compared with the DEF therapy group (525 x 106/L vs. 599 x 106/L, P < 0.01) in the EACG020 trial. We next examined the comparability of the IMM and DEF therapy groups between the trials. Consistent with the differences in eligibility criteria between Concorde and EACG020, EACG020 participants were older and had a higher CD4 cell count at randomization (mean age = 36.4 years; median CD4 cell count at randomization = 552 x 106/L) compared with Concorde participants (mean age = 34.0 years, P= 0.02; median CD4 cell count = 456 x 106/L, P< 0.001). The number of pre-randomization CD4 counts (median 4, interquartile (IQ) range = 36) and median interval of 2.2 months between CD4 cell counts were similar between the two trials. However, Concorde trial participants had approximately twice as many CD4 cell counts post-randomization (median = 20, IQ range = 1427) as EACG020 participants did (median = 11, IQ range = 6.515, P < 0.001), which relects the more frequent monitoring of CD4 cell counts and longer follow-up available in Concorde (median = 69.0 months) compared with EACG020 (median = 53.4 months).
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To assess the generalizability of findings from our analyses, we compared the characteristics of our patient subgroup with the characteristics of the rest of the study population of Concorde and EACG020. Patients in our subgroup were significantly older, with a mean age (S.D.) of 33.5 (8.2) versus 31.1 (8.8) years in Concorde and 36.4 (9.5) versus 33.9 (9.5) years in EACG020, and were more likely to be homosexual men (Concorde, 96% vs. 60; EACG020, 99 vs. 62). Baseline CD4 cell counts in our subgroup were similar to those in the main trials.
CD4 lymphocyte response to therapy
Table II shows the predicted baseline CD4 cell count, initial response to treatment, and the joint distributions of pre-randomization and post-randomization CD4 cell decline. The estimated mean baseline CD4 cell count was 523.1 x 106/L with an average rate of CD4 cell decline before randomization of -22.5 x 106/L per 6 months, which was assumed to be constant following randomization for patients assigned to DEF therapy. For the patients receiving IMM therapy, the model predicted an initial rise of 60.0 x 106 cells/L after starting therapy, and a subsequent rate of CD4 cell decline of -26.0 x 106/L per 6 months. Patients were stratified into quartiles (groups 1-4) according to their estimated pre-randomization slopes, where group 1 had the slowest (median = -4.9 x 106 cells/L per 6 months) and group 4 the fastest (median = -42 x 106 cells/L per 6 months) rate of CD4 cell decline.
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Disease progression
The 297 participants from the two trials combined were followed for a median period of 61 months following randomization. Clinical events (i.e. development of AIDS or a 50% drop in CD4 cell count from the level at randomization) occurred in 90 patients in the IMM therapy group (58%) and 93 in the DEF group (65%). Deaths were reported in 38 (25%) and 39 (27%) patients in the IMM and DEF groups, respectively. The overall relative risk for disease progression or death with IMM versus DEF therapy after adjustment for baseline CD4 cell count was 0.80 (95% CI = 0.601.06).
When pre-randomization slopes were recalculated using only CD4 cell counts before randomization (in accordance with the assumptions of the Cox model), the estimates within each quartile were comparable to those reported inTable II (group 1, median = -2.4 (range = -12.0 to +32.8 x 106 cells/L per 6 months); group 2, median = -16.4 (range = -19.5 to -12.1 x 106 cells/L per 6 months); group 3, median = -22.7 (range = -25.9 to -19.6 x 106 cells/L per 6 months); group 4, median = -31.4 (range = -54.5 to -25.9 x 106 cells/L per 6 months).
The baseline CD4 cell count was strongly predictive of disease progression (P = 0.004): a 100 cell increase in CD4 cell count at randomization was associated with a reduced hazards ratio (HR) of 0.87 (95% CI = 0.78-0.96), but the pre-randomization rate of CD4 cell decline had no significant impact on the risk of progression in either the IMM or DEF therapy groups (P= 0.7 and 0.4, respectively). TheFigure (panel a) shows the HRs for risk of disease progression with IMM versus DEF therapy across the four quartiles of pre-randomization rate of CD4 cell decline for both trials combined, after adjustment for the baseline CD4 cell count. Although, the reduction in the risk of progression with IMM therapy appears to to be greatest in group 4 (HR = 0.61, which is equivalent to a 39% risk reduction), this was not statistically significant (95% CI = 0.351.05). In patients with a previous CD4 cell decline greater than the overall median, i.e. groups 3 and 4 combined, the estimated risk was HR = 0.64 (95% CI = 0.420.97, P= 0.03). In patients with previous CD4 cell decline rates less than the overall median, the HR was 0.92 (95% CI = 0.611.39, P= NS).
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There was no evidence of a significant relationship between magnitude of change in CD4 cell decline and clinical progression, either before (P = 0.6) or after (P = 0.42) adjustment for baseline CD4 cell count. The findings were similar when the trials were analysed separately. These data suggest that the beneficial effect of zidovudine in patients with rapid CD4 cell decline is not explained by a change in the rate of CD4 cell decline.
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Discussion |
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These findings are consistent with previous reports that a high rate of CD4 cell decline is a strong independent predictor for the more rapid development of AIDS. 13,14,15,16 It is well recognized that individuals at highest risk of disease progression derive the greatest benefit from therapeutic interventions. When five published trials 1,2,3,4,5 of monotherapy in patients with symptomatic HIV infection were examined for the relationship between benefit of zidovudine therapy and mortality rate in the control group, an increasing mortality rate was associated with an increase in the numbers of deaths delayed with zidovudine. Similar considerations apply to the appropriate use of cholesterol-lowering drugs 20 and the treatment of hypertension. 21 This has prompted the adoption of risk-based thresholds in treatment guidelines in these areas, whereby therapy is reserved for persons who meet specific high-risk criteria for future clinical events. 22
We examined whether the apparent therapeutic benefit in the patient subgroup with rapid CD4 cell decline was explained by the greater reduction in their rate of CD4 cell decline with zidovudine. Although patients with a faster initial CD4 cell decline experienced the greatest reduction in rate of CD4 cell decline following zidovudine therapy, we found no relationship between this magnitude of change and clinical outcome, consistent with the findings of two other studies. 14,23 Previous observational studies have shown that it is the sustained effect on the CD4 cell count in response to therapy and not the nature of the initial response that is important for clinical outcome. 14,24 However, the CD4 lymphocyte count is known to be a poor marker of the clinical response to antiretroviral therapy, in part because of its inherent large intra-assay variability. 25,26 Changes in CD4 cell count predict only 35-40% of the clinical benefit of zidovudine therapy. 27
The individual slopes of the CD4 cell count trajectory before and after randomization were estimated by fitting a mixed linear model. 18 There are several advantages of using a mixed model for regression over the standard least-squares approach. Firstly, variability between and within patients is taken into account, and, secondly, there is no minimum number of CD4 cell counts per patient required, since individual estimates are calculated using the pooled estimate from the whole sample. In contrast, a least-squares approach cannot effectively model within-patient variation, and also requires a minimum number of counts for each individual to generate more reliable estimates.
Recent data have established that a high viral load despite asymptomatic disease is associated with a poor prognosis. 10 A single determination of plasma RNA viral load can provide important prognostic information and help identify those patients at high risk of early disease progression. Mellors et al. 10 have shown that among patients with a CD4 cell count greater than 500 x 106 cells/L, more than 70% progressed to AIDS and died within 10 years if their baseline viral load was more than 10,900 copies/mL, compared with less than 30% in those who had a viral load below 10,000 copies/mL. However, there are no data as yet to indicate whether these individuals benefit from early intervention. In a further study, 11 it was also suggested that viral load was superior to the CD4 lymphocyte count as a surrogate marker for clinical drug efficacy. Further analyses of randomized trials of combination antiretroviral therapy among patients with a CD4 cell count >500 x 106 cells/L are needed to define the precise virological thresholds associated with clinical benefit from early intervention.
A further reason why viral load might be considered a preferable surrogate measure to the CD4 lymphocyte count in identifying subgroups of patients at high risk of progression is that a high viral load is likely to precede the onset of rapid CD4 cell decline. Recent reports have highlighted the dynamic interaction between HIV replication and CD4 lymphocyte destruction. 28 Decreases in CD4 cell counts occur as a result of viral replication, and so represent a later time point in the disease course than a plasma viral load level. Likewise, when effective antiretroviral therapy is started, levels of HIV replication decline steeply over a period of a few weeks, which is then followed by a rise in the CD4 cell count. 28 Since the rationale of therapy is to prevent HIV-mediated immune lymphocyte destruction, the HIV-1 RNA level is likely to be the most important parameter on which to base decisions about initiating therapy in patients with a CD4 lymphocyte count above 500 x 106 cells/L. However, since viral load is not yet widely available, particularly in resource-poor settings, a high rate of CD4 cell decline offers an alternative approach to identifying patients at high risk of progression.
The interpretation of the results from this analysis, as with the overall trial data, is complicated by the fact that many of the subjects originally assigned to the placebo group received zidovudine, and those assigned to the immediate treatment arm discontinued therapy. Although data were analysed by assigned treatment, if the majority of patients on zidovudine subsequently discontinued therapy and those on placebo took zidovudine, and this differed according to the rate of CD4 cell decline, then our findings could be substantially altered. In the published trial reports, it is stated that 418 (48%) of the deferred therapy arm in Concorde took zidovudine at some stage during follow-up, 5 and 135 (27%) in EACG020 withdrew from blinded treatment (an unknown percentage of whom started on open-label zidovudine). 12 However, when the analysis was repeated restricting follow-up to the first year only, when few patients have discontinued their assigned therapy, the results were similar.
It is noteworthy that we analysed data from only a subgroup (11.3% and 10.5%, respectively) of the total Concorde and EACG020 trial participants. However, we had follow-up data for 5 years after randomization, compared with 3.3 years and 1.8 years, respectively, with the published Concorde and EACG020 trials, and, as a result, had approximately twice the event rate. Although there was a greater proportion of older homosexual men in our subgroup, the baseline CD4 cell counts were similar, and our results are likely to be generalizable to the overall study population.
There are several impediments to the adoption of routine monitoring of trends in CD4 cell counts in patients with early disease to assist in therapeutic decision making. First, there is the problem of the occasional dramatic fluctuation in a patient's CD4 cell count, often because of factors unrelated to HIV infection, such as laboratory and biological variability. 26 Although individuals with a rapid CD4 cell decline can be identified readily in retrospect, the near-term variability in the CD4 cell count can make it difficult to assign any prognostic significance to precipitous changes, which may be temporary. A further problem is in the application of predictive models from groups of patients to the individual, in terms of how many CD4 cell counts are needed and over what period in order to generate a reliable slope for the individual patient. A reasonable recommendation is a minimum of three CD4 measurements over an 8 week period to be confident of the presence of a trend.
Our findings have several implications for clinical practice and future trials of antiretroviral therapy. Firstly, among patients with early asymptomatic HIV infection and a CD4 cell count >500 x 106 cells/L, only those with a 6-monthly rate of CD4 cell decline >26 x 106 cells/L are likely to derive benefit from early antiretroviral therapy. The benefit of treating this subgroup may be even greater with combination therapy, and our analytic approach should be replicated in trials of combination therapy including protease inhibitors. However, since antiretroviral therapy is usually lifelong, adverse effects need to be considered in weighing up the benefits, risks, and costs of intervention in early disease. One study has shown that the transient benefits of early antiretroviral therapy are at least partially offset by drug toxicity resulting in a decreased quality of life. 29 To assist in therapeutic decision making, future studies should focus on defining risk thresholds (based on a combination of demographic, CD4 cell, and viral load parameters) below which there is no evidence of benefit from early intervention.
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Acknowledgments |
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Notes |
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References |
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Received 28 January 1998; returned 16 June 1998; revised 27 August 1998; accepted 9 October 1998