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Original Investigation |

A Critical Assessment of the Prognostic Value of HIV-1 RNA Levels and CD4+ Cell Counts in HIV-Infected Patients FREE

Sabine Yerly, MS; Thomas V. Perneger, MD, PhD; Bernard Hirschel, MD; Olivier Dubuis, MD; Lukas Matter, MD; Raffaele Malinverni, MD; Hansjakob Furrer, MD; Luc Perrin, MD; Swiss HIV Cohort Study
[+] Author Affiliations

From the Laboratory of Virology (Ms Yerly and Dr Perrin) and AIDS Center (Dr Hirschel), Division of Infectious Diseases, Geneva University Hospital, Geneva, Switzerland; Institute of Social and Preventive Medicine, University of Geneva (Dr Perneger); Institute of Medical Microbiology, University of Bern, Bern, Switzerland (Drs Dubuis and Matter); and AIDS Center, Medical Policlinic, Inselspital Bern (Drs Malinverni and Furrer).


Arch Intern Med. 1998;158(3):247-252. doi:10.1001/archinte.158.3.247.
Text Size: A A A
Published online

Objective  To determine to what extent human immunodeficiency type 1 (HIV-1) RNA levels and CD4+ cell counts predict clinical outcomes in a general HIV-1–infected population.

Methods  Community-based prospective study (Swiss HIV Cohort Study) including 394 HIV-1–infected patients, randomly selected from 4 strata of CD4+ cell counts (0 to <0.05, 0.05 to <0.20, 0.20 to <0.50, and ≥0.50 ×109/L). Levels of HIV-1 RNA, CD4+ cell counts, and other variables were evaluated from samples collected between 1991 and 1993 for their ability to predict death and clinical progression.

Results  Patients were followed up on average for 29 months. Baseline HIV-1 RNA levels, CD4+ cell counts, clinical stage, and β2-microglobulin levels independently predicted survival, whereas only HIV-1 RNA levels and CD4+ cell counts independently predicted clinical progression. Multivariate relative hazards (RHs) for death ranged from 1.0 to 5.4 across quartiles of CD4+ counts, but only from 1.0 to 1.8 across quartiles of HIV-1 RNA. For clinical progression, gradients of risk were similar for CD4+ counts (1.0-4.2) and for HIV-1 RNA (1.0-3.1). In patients with CD4+ cell counts less than 0.05×109/L, HIV-1 RNA levels predicted neither death nor clinical progression. Finally, the number of HIV-1 RNA copies per CD4+ cell was the best predictor of death (multivariate RH, 1.0-9.7 across quartiles) and clinical progression (multivariate RH, 1.0-4.1).

Conclusions  Levels of HIV-1 RNA and CD4+ cell counts provided independent and complementary information on clinical outcomes. The RNA/CD4+ ratio was the best single predictor. In patients who had fewer than 0.05×109/L CD4+ cells, HIV-1 RNA levels had little prognostic value.

Figures in this Article

VARIOUS BIOLOGICAL parameters predict clinical outcomes in patients infected with the human immunodeficiency virus type 1 (HIV-1). Until 1995, CD4+ cell counts were considered to be the best predictor, but several recent studies suggest that a direct measurement of viremia (plasma HIV-1 RNA) may provide superior prognostic information.112 However, currently available evidence presents some limitations, which we sought to address in this study. First, previous studies have involved selected patient populations: patients enrolled in clinical trials of antiviral treatments,712 asymptomatic patients recently infected with HIV-1,1,2 or patients with hemophilia.4 Whether these results apply to HIV-infected patients encountered in general medical practice, in particular to those with advanced immunosuppression, is therefore uncertain. Second, most previous studies have focused on viremia, and treated other predictors, including CD4+ cell counts, as confounders. Little information is available on the respective contribution of each variable, and on the interaction between viremia and CD4+ cell counts in predicting clinical outcomes. Last, few studies36 have examined separately the risk of death and the risk of clinical progression; predictors may vary for these 2 outcomes.

The main aim of this study was to assess the ability of biological parameters, including HIV-1 RNA levels and CD4+ cell counts, to predict death and clinical progression in a general population of HIV-infected patients. Secondary aims were to assess the predictive value of HIV-1 RNA levels and CD4+ cell counts at various levels of disease severity, to evaluate whether predictors differ for death and clinical progression, and to identify the most efficient way of expressing the prognostic information conveyed by these biological parameters.

STUDY DESIGN AND VARIABLES

This prospective study examined the value of baseline HIV-1 RNA levels, CD4+ and CD8+ cell counts, β2-microglobulin levels, immune complex dissociated (ICD) p24 antigen levels, clinical stage, patient age, patient sex, mode of HIV transmission in predicting death (HIV related or not), and clinical disease progression. Clinical progression was defined as occurrence of Centers for Disease Control and Prevention (CDC) stage B or C diseases (CDC 1993 criteria13) of equal or greater severity than the baseline clinical status, including HIV-related death. Patients were enrolled between January 1991 and December 1993, with follow-up until April 1996.

STUDY POPULATION

Patients enrolled in the Swiss HIV Cohort Study14 in Bern and Geneva, Switzerland, who had a frozen plasma sample (stored at −75°C) collected between January 1991 and December 1993 were eligible. Of 622 eligible patients, 400 were selected at random, stratified on the basis of initial CD4+ cell counts (×109/L), with 100 patients in each of 4 strata (0 to <0.05, 0.05 to <0.20, 0.20 to <0.50, and ≥0.50). Proportions of patients selected within the eligible population according to strata of CD4+ cell counts were 78%, 65%, 47%, and 78%, respectively. When several plasma samples were available for a given patient, the first one was used as the baseline sample.

LABORATORY METHODS

Levels of HIV-1 RNA were measured by polymerase chain reaction using the Amplicor HIV Monitor assay (Roche, Basel, Switzerland). The lowest detection threshold of the assay was 100 copies per milliliter. CD4+ and CD8+ cell counts were determined by flow cytometry (Coulter EPICS IV, Instrumente Gesellschaft AG, Basel). β2-Microglobulin levels were determined by enzyme immunoassay (IMX Diagnostic System, Abbott Laboratories, North Chicago, Ill). The level of ICD p24 antigen was measured in heat-denatured plasma using DuPont HIV-1 p24 Antigen and DuPont ELAST ELISA Amplification System (DuPont, Boston, Mass).15 Results of HIV-1 RNA and ICD p24 antigen measurements were expressed on a logarithm scale (base 10).

STATISTICAL ANALYSIS

Relationships between baseline predictor variables (categorized by quartile) and outcome variables were assessed using Kaplan-Meier analyses, log-rank tests for linear trend, and proportional hazards models.16 The predictive value of HIV-1 RNA level was also examined across quartiles of CD4+ cell counts; in these analyses, log HIV-1 RNA/mL was treated as a continuous variable; similarly, the predictive value of CD4+ cell counts (on a continuous scale) was examined across quartiles of HIV-1 RNA. In the latter models, an interaction term was used to determine whether the risk of event associated with one predictor changed significantly across quartiles of the other predictor. The RNA/CD4+ ratio was calculated by dividing log HIV-1 RNA/mL by CD4+ cells/mL. P values less than .05 were considered significant.

PATIENT CHARACTERISTICS

Six patients were withdrawn from the original sample: HIV-1 RNA levels could not be measured in 3 patients due to inhibition of polymerase chain reaction, and follow-up data were not available for 3 other patients. The 394 remaining patients were, on average, 35 years old (range, 18-66 years), and 307 (78%) were men. Risk stratification included 211 men who have sex with men (54%), 107 persons infected through heterosexual contact (27%), 67 intravenous drug users (17%), and 11 with other or unknown risks (2%). At baseline, 150 patients (38%) had disease that was in clinical stage A, 114 (29%) in stage B, and 130 (33%) in stage C. All predictor variables were widely distributed (Table 1). In 8 patient samples (2%), HIV-1 RNA was below the detection limit of the assay, and these patients were assigned the threshold value of 100 copies/mL. Quartiles of log HIV-1 RNA were less than 3.87, 3.87 to 4.45, 4.46 to 4.92, and 4.93 to 6.24 copies/mL. Levels of HIV-1 RNA were significantly associated with CDC stages, CD4+ and CD8+ cell counts, β2-microglobulin levels, ICD p24 antigen levels, and age (data not shown). Fifty-five percent of patients received antiretroviral treatment at any time during follow-up, mainly zidovudine, didanosine, or zalcitabine as monotherapy, and 47% received prophylaxis for Pneumocystis carinii pneumonia.

Table Graphic Jump LocationTable 1. Baseline Variables of HIV-1–Infected Patients (N=394)*
PATIENT SURVIVAL

During follow-up (mean, 29 months; range, 0.5-54 months), 169 patients (43%) died; 148 deaths were related to HIV and 21 were not (suicides, homicides, or other causes). The overall mortality rate was 18 per 100 person-years (95% confidence interval [CI], 16-20).

Levels of HIV-1 RNA strongly predicted survival (log-rank P<.001) (Figure 1, A). Mortality rates in increasing quartiles of HIV-1 RNA were 4, 7, 27, and 44 deaths per 100 person-years. Similarly, CD4+ cell counts strongly predicted survival (log-rank P<.001) (Figure 1, B). Mortality rates for decreasing quartiles of CD4+ cell counts were 3, 6, 22, and 60 deaths per 100 person-years. In univariate analysis, patient sex and transmission mode were not associated with death (both P=.8). All other predictors, including patient age (relative hazards, 1.3; 95% CI, 1.1-1.5 per 10 years older), significantly predicted death (Table 2). In multivariate analysis, only HIV-1 RNA levels, clinical stage, CD4+ cell counts, and β2-microglobulin levels predicted death. The strongest gradient of risk was observed for CD4+ cell counts, for which relative hazards ranged from 1.0 to 5.4. In contrast, relative hazards ranged only from 1.0 to 1.8 for HIV-1 RNA. A significantly increased risk of death was also observed for patients with β2-microglobulin levels greater than 305 nmol/L (3.6 mg/L), and for those who had the acquired immunodeficiency syndrome (AIDS) at baseline.

Place holder to copy figure label and caption
Figure 1.

Relation between human immunodeficiency virus type 1 (HIV-1) RNA levels or CD4+ cell counts and clinical outcomes. Kaplan-Meier curves for survival stratified by quartiles of log HIV-1 RNA/mL (A) and CD4+ cell counts (B), and for clinical progression stratified by quartiles of HIV-1 RNA/mL (C) and CD4+ cell counts (D). Quartiles of log HIV-1 RNA/mL: 1, <3.87; 2, 3.87-4.45; 3, 4.46-4.92; and 4, 4.93-6.24. Quartiles of CD4+(×109/L): 1, ≥0.50; 2, 0.20 to <0.50; 3, 0.05 to <0.20; and 4, <0.05.

Graphic Jump Location
Table Graphic Jump LocationTable 2. Relative Hazards of Death and Clinical Progression Associated With Clinical and Biological Markers*
CLINICAL DISEASE PROGRESSION

During follow-up, 270 patients (69%) experienced clinical progression (106 CDC stage B events in patients who did not have AIDS at baseline, 146 AIDS-defining events, and 18 HIV-related deaths without prior recorded clinical progression). The overall clinical progression rate was 43 per 100 person-years (95% CI, 40-46).

Low HIV-1 RNA levels were significantly associated with fewer events (log-rank P<.001) (Figure 1, C). Progression incidence rates in increasing quartiles of HIV-1 RNA were 16, 37, 65, and 93 per 100 person-years. In decreasing quartiles of CD4+ cell counts, progression incidence rates were 17, 26, 70, and 108 per 100 person-years (log-rank P<.001) (Figure 1, D). In univariate analysis, patient sex and transmission mode were not associated with clinical progression (P=.4 and P=.9, respectively). All biological markers, clinical stage, and patient age (relative hazards, 1.2; 95% CI, 1.1-1.4 per 10 years) significantly predicted clinical progression (Table 2). However, only HIV-1 RNA levels and CD4+ cell counts were still statistically significant predictors in a multivariate model. Gradients of risk were similar for quartiles of CD4+ cell counts (1.0-4.2) and HIV-1 RNA levels (1.0-3.1).

INTERACTIONS BETWEEN EFFECTS OF CD4+ CELL COUNTS AND HIV RNA LEVELS

In the whole sample, a 10-times higher HIV-1 RNA level was associated with a 4-fold increase in mortality and a 2.6-fold increase in the risk of clinical progression. Similarly, a 10-times lower CD4+ cell count was associated with a 5-fold increase in mortality and a 2.8-fold increase in the risk of clinical progression.

The predictive value of HIV-1 RNA differed across quartiles of CD4+ cell counts (test on interaction term: P=.003 for death and P=.03 for clinical progression). Among patients with initial CD4+ counts less than 0.05×109/L, HIV-1 RNA levels predicted neither death nor clinical progression (Figure 2, A). Similarly, a gradient of risk was observed for CD4+ cell counts across quartiles of HIV-1 RNA (Figure 2, B). The risk of death (P=.005) and clinical progression (P<.001) also differed significantly according to HIV-1 RNA levels. The predictive value of CD4+ cell counts was greatest among patients who had low levels of HIV-1 RNA.

Place holder to copy figure label and caption
Figure 2.

Relative hazards (RH), with 95% confidence intervals in logarithmic scale, of death and clinical progression for 10-times higher human immunodeficiency virus type 1 (HIV-1) RNA levels across quartiles of CD4+ cell counts (A) and for 10-times lower CD4+ cell counts across quartiles of HIV-1 RNA (B).

Graphic Jump Location
A NEW MARKER: RNA/CD4+ RATIO

The RNA/CD4+ ratio demonstrated to be an excellent predictor of death and clinical progression in the whole study population. This ratio varied between less than 0.0001 and 183.7 (mean, 3.94; SD, 14.54). In univariate analysis, the gradient of relative hazards went from 1.0 to 30.3 for death, and from 1.0 to 8.9 for clinical progression, across quartiles of the RNA/CD4+ ratio (Table 3). These gradients were stronger than those of CD4+ cell counts or of HIV-1 RNA levels expressed by milliliters. In multivariate models, both RNA/CD4+ ratios and CD4+ cell counts were independent predictors of death and clinical progression (Table 3). When added to a model with the RNA/CD4+ ratio, HIV-1 RNA expressed by milliliters was not a significant predictor (data not shown).

Table Graphic Jump LocationTable 3. Relative Hazards of Death and Clinical Progression Associated With Quartiles of RNA/CD4+ Ratio and CD4+ Cell Counts*

In this study, we assessed the role of HIV-1 RNA levels, CD4+ cell counts, and other markers as predictors of clinical outcomes in an HIV-infected population representative of patients seen in general medical practice. We complement previous studies14 by showing that CD4+ cell counts provide important prognostic information about clinical outcomes even when HIV-1 RNA levels are taken into account. We also observed that the predictive value of clinical and biological markers differed for death and clinical progression. In addition, analysis across quartiles demonstrated that both CD4+ cell counts and HIV-1 RNA levels have a lower predictive value in patients with more advanced disease. Finally, the RNA/CD4+ ratio, which combines information from both markers, was the best single predictor of clinical progression and death.

Although HIV-1 RNA was an excellent predictor of clinical outcome, CD4+ cell counts remained a powerful predictor even when HIV-1 RNA level was accounted for. In earlier studies,14 performed in patients with a narrower range of CD4+ levels, the predictive value of CD4+ cell counts was marginal. However, these studies were not designed to compare the predictive value of HIV-1 RNA and CD4+ cell counts, and have emphasized the predictive value of HIV-1 RNA.

Moreover, predictors provided different information according to the outcome analyzed. In multivariate models, CD4+ cell counts had a similar predictive value for both clinical progression and death, whereas HIV-1 RNA levels were better at predicting clinical progression than death. This finding is similar to previous results seen in a different patient population,5 and suggest that viremia may affect survival and clinical progression in different ways. For example, if the effect of HIV-1 RNA on survival (but not on clinical progression) was mostly mediated by CD4+ cell depletion, the weak ability of HIV-1 RNA to predict death in CD4-adjusted models would be due to overadjustment. On the other hand, high levels of HIV-1 RNA might be associated with an enhanced replication of other pathogens and thus affect clinical progression independently of CD4+ counts.1719

The predictive value of CD4+ cell counts and HIV-1 RNA levels varied across quartiles of the other predictor. Both biological markers lost partially (CD4+ cell counts) or completely (HIV-1 RNA) their predictive ability among patients with more advanced disease (HIV-1 RNA >4.45 copies/mL and CD4+ cell count <0.05×109/L, respectively). Several mechanisms may explain this finding. In patients with very low CD4+ cell counts, the availability of target cells might limit HIV-1 replication and affect HIV-1 RNA levels. If so, HIV-1 RNA levels would not adequately reflect clinical prognosis in CD4+-depleted patients. Another possibility is that among the most CD4+-depleted patients, extrinsic factors, such as exposure to pathogens, may be more important for prognosis than intrinsic factors, such as viremia or CD4+ counts. Last, a 10-fold difference in either HIV-1 RNA levels or CD4+ cell counts may have a different biological meaning depending on the absolute level of each predictor. Because HIV-1 RNA levels and CD4+ cell counts were correlated, stratifying on the first variable also partially stratifies on the second. Whichever explanation is correct, our findings suggest that measurement of HIV-1 RNA contributes little prognostic information in patients with very low CD4+ cell counts.

The relative hazards reported in this study may be underestimated, because the sickest patients have preferentially received antiviral drugs, which in turn may improve their outcome. Because antiviral drugs were not administered at random, we did not examine whether antiviral treatment improved clinical outcome.20

Replication of HIV is the main factor leading to CD4+ cell death21,22 and HIV-1 RNA levels reflect the number of HIV-infected cells. Thus, the HIV-1 RNA/CD4+ ratio represents the contributions of these 2 markers to patient prognosis. Indeed, the RNA/CD4+ ratio was the best single predictor of clinical disease progression and death in our population. The high predictive ability of the ratio may be due to the fact that it best reflects viral dynamics, which plays a central role in a patient's prognosis. Alternatively, the RNA/CD4+ ratio may be a strong predictor because it combines information from 2 variables (viral replication and immune response) that influence outcome independently. Regardless of the underlying mechanism, the RNA/CD4+ ratio was a much better predictor than HIV-1 RNA expressed by plasma volume: the ratio predicted death even in CD4+-depleted patients, and patients in the highest quartile of the RNA/CD4+ ratio had a 30-fold increase in mortality, compared with the lowest quartile. Such patients may qualify for aggressive antiretroviral treatment even in the absence of evidence from controlled trials. The RNA/CD4+ ratio may also deserve an evaluation as surrogate marker of clinical outcomes in clinical trials.

In summary, HIV-1 RNA level is a useful prognostic marker in HIV-infected patients, but its importance may have been overestimated in recent literature. In particular, viremia levels have virtually no predictive ability in patients with severe immunosuppression. Viremia should not be used in isolation, as CD4+ cell counts contribute important and independent prognostic information, particularly when predicting death. Finally, the HIV-1 RNA/CD4+ ratio is the most useful predictor of clinical outcome and deserves further attention.

Accepted for publication June 16, 1997.

Presented in part at the 11th International Conference on AIDS, Vancouver, British Columbia, July 10, 1996.

We thank K. Zollinger for excellent technical assistance, V. Gabriel for database management, and O. Rutschmann, MD, A. Halfon-Poletti, MD, G. Figueras, MD, P. Lorenzi, MD, A. Mendoula, MD, and H. Wolff, MD, for reviewing all patient clinical charts.

This study took advantage of the infrastructure of the Swiss HIV Cohort Study, whose members are M. Battegay, Ph. Bürgisser, R. Doorly, M. Egger, P. Erb (chair, "Laboratories"), W. Fierz, M. Flepp (chair, "Clinics"), P. Francoli (president), P. Grog, U. Grüninger, B. Hirschel (chair of the scientific board), B. Ledergerber, R. Lüthy, R. Malinverni, L. Matter, M. Opravil, F. Paccaud, L. Perrin, W. Pichler, M. Rickenbach (manager of the data center), O. Rutschmann, P. Vernazza, and J. von Overbeck.

Reprints: Luc Perrin, MD, Laboratory of Virology, Geneva University Hospital, 1211 Geneva 14, Switzerland (e-mail: perrin@hcuge.ch).

Henrard  DRPhillips  JFMuenz  LR  et al.  Natural history of HIV-1 cell-free viremia. JAMA. 1995;274554- 558
Link to Article
Mellors  JWKingsley  LARinaldo  CR  et al.  Quantitation of HIV-1 RNA in plasma predicts outcome after seroconversion. Ann Intern Med. 1995;122573- 579
Link to Article
Mellors  JWRinaldo  CRGupta  PWhite  RMTodd  JAKingsley  LA Prognosis in HIV-1 infection predicted by the quantity of virus in plasma. Science. 1996;2721167- 1170
Link to Article
O'Brien  TRBlattner  WAWaters  D  et al.  Serum HIV-1 RNA levels and time to development of AIDS in the Multicenter Hemophilia Cohort Study. JAMA. 1996;276105- 110
Link to Article
Galetto-Lacour  AYerly  SPerneger  TV  et al.  Prognostic value of viremia in patients with long-standing human immunodeficiency virus infection. J Infect Dis. 1996;1731388- 1393
Link to Article
Ruiz  LRomeu  JClotet  B  et al.  Quantitative HIV-1 RNA as a marker of clinical stability and survival in a cohort of 302 patients with a mean CD4 cell count of 300×106/l. AIDS. 1996;10F39- F44
Link to Article
Phillips  ANEron  JJBartlett  JA  et al.  HIV-1 RNA levels and the development of clinical disease. AIDS. 1996;10859- 865
Link to Article
Yerly  SKaiser  LMermillod  BBaumberger  CHirschel  BPerrin  L Response of HIV RNA to didanosine as predictive marker of survival. AIDS. 1995;9159- 163
Link to Article
O'Brien  WAHartigan  PMMartin  D  et al.  Changes in plasma HIV-1 RNA and CD4+ lymphocyte counts and the risk of progression to AIDS. N Engl J Med. 1996;334426- 431
Link to Article
Welles  SLJackson  JBYen-Liebermen  B  et al.  Prognostic value of plasma human immunodeficiency virus type 1 (HIV-1) RNA levels in patients with advanced HIV-1 disease and with little or no prior zidovudine therapy. J Infect Dis. 1996;174696- 703
Link to Article
Coombs  RWWelles  SLHooper  C  et al.  Association of plasma human immunodeficiency virus type 1 RNA level with risk of clinical progression in patients with advanced infection. J Infect Dis. 1996;174704- 712
Link to Article
Katzenstein  DAHammer  SMHughes  MD  et al.  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. N Engl J Med. 1996;3351091- 1098
Link to Article
Center for Disease Control and Prevention, 1993 Revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR Morb Mortal Wkly Rep. 1993;41 ((RR-17)) 1- 19
Ledergerber  Bvon Overbeck  JEgger  MLüthy  R The Swiss HIV Cohort Study: rationale, organization and selected baseline characteristics. Soz Praventivmed. 1994;39387- 394
Link to Article
Schüpbach  JBöni  JTomasik  ZJendis  JKind  C Sensitive detection and early prognostic significance of p24 antigen in heat-denatured plasma of human immunodeficiency virus type 1-infected infants. J Infect Dis. 1994;170318- 324
Link to Article
Collett  D Modelling Survival Data in Medical Research.  London, England Chapman & Hall1994;
Sieczkowski  LChandran  BWood  C The human immunodeficiency virus tat gene enhances replication of human herpesvirus-6. Virology. 1995;211544- 553
Link to Article
Biggs  BAHewish  MKent  SHayes  KCrowe  SM HIV-1 infection of human macrophages impairs phagocytosis and killing of Toxoplasma gondiiJ Immunol. 1995;1546132- 6139
Telfer  PTBrown  DDevereux  HLee  CADuSheiko  GM HCV RNA levels and HIV infection: evidence for a viral interaction in haemophilic patients. Br J Haematol. 1994;88397- 399
Link to Article
Glesby  MJHoover  DR Survivor treatment selection bias in observational studies: examples from AIDS literature. Ann Intern Med. 1996;124999- 1005
Link to Article
Wei  XGhosh  SKTaylor  ME  et al.  Viral dynamics in HIV-1 infection. Nature. 1995;373117- 122
Link to Article
Ho  DDNeumann  AUPerelson  ASChen  WLeonard  JMMarkowitz  M Rapid turnover of plasma virion and CD4 lymphocytes in HIV-1 infection. Nature. 1995;373123- 126
Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.

Relation between human immunodeficiency virus type 1 (HIV-1) RNA levels or CD4+ cell counts and clinical outcomes. Kaplan-Meier curves for survival stratified by quartiles of log HIV-1 RNA/mL (A) and CD4+ cell counts (B), and for clinical progression stratified by quartiles of HIV-1 RNA/mL (C) and CD4+ cell counts (D). Quartiles of log HIV-1 RNA/mL: 1, <3.87; 2, 3.87-4.45; 3, 4.46-4.92; and 4, 4.93-6.24. Quartiles of CD4+(×109/L): 1, ≥0.50; 2, 0.20 to <0.50; 3, 0.05 to <0.20; and 4, <0.05.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Relative hazards (RH), with 95% confidence intervals in logarithmic scale, of death and clinical progression for 10-times higher human immunodeficiency virus type 1 (HIV-1) RNA levels across quartiles of CD4+ cell counts (A) and for 10-times lower CD4+ cell counts across quartiles of HIV-1 RNA (B).

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Baseline Variables of HIV-1–Infected Patients (N=394)*
Table Graphic Jump LocationTable 2. Relative Hazards of Death and Clinical Progression Associated With Clinical and Biological Markers*
Table Graphic Jump LocationTable 3. Relative Hazards of Death and Clinical Progression Associated With Quartiles of RNA/CD4+ Ratio and CD4+ Cell Counts*

References

Henrard  DRPhillips  JFMuenz  LR  et al.  Natural history of HIV-1 cell-free viremia. JAMA. 1995;274554- 558
Link to Article
Mellors  JWKingsley  LARinaldo  CR  et al.  Quantitation of HIV-1 RNA in plasma predicts outcome after seroconversion. Ann Intern Med. 1995;122573- 579
Link to Article
Mellors  JWRinaldo  CRGupta  PWhite  RMTodd  JAKingsley  LA Prognosis in HIV-1 infection predicted by the quantity of virus in plasma. Science. 1996;2721167- 1170
Link to Article
O'Brien  TRBlattner  WAWaters  D  et al.  Serum HIV-1 RNA levels and time to development of AIDS in the Multicenter Hemophilia Cohort Study. JAMA. 1996;276105- 110
Link to Article
Galetto-Lacour  AYerly  SPerneger  TV  et al.  Prognostic value of viremia in patients with long-standing human immunodeficiency virus infection. J Infect Dis. 1996;1731388- 1393
Link to Article
Ruiz  LRomeu  JClotet  B  et al.  Quantitative HIV-1 RNA as a marker of clinical stability and survival in a cohort of 302 patients with a mean CD4 cell count of 300×106/l. AIDS. 1996;10F39- F44
Link to Article
Phillips  ANEron  JJBartlett  JA  et al.  HIV-1 RNA levels and the development of clinical disease. AIDS. 1996;10859- 865
Link to Article
Yerly  SKaiser  LMermillod  BBaumberger  CHirschel  BPerrin  L Response of HIV RNA to didanosine as predictive marker of survival. AIDS. 1995;9159- 163
Link to Article
O'Brien  WAHartigan  PMMartin  D  et al.  Changes in plasma HIV-1 RNA and CD4+ lymphocyte counts and the risk of progression to AIDS. N Engl J Med. 1996;334426- 431
Link to Article
Welles  SLJackson  JBYen-Liebermen  B  et al.  Prognostic value of plasma human immunodeficiency virus type 1 (HIV-1) RNA levels in patients with advanced HIV-1 disease and with little or no prior zidovudine therapy. J Infect Dis. 1996;174696- 703
Link to Article
Coombs  RWWelles  SLHooper  C  et al.  Association of plasma human immunodeficiency virus type 1 RNA level with risk of clinical progression in patients with advanced infection. J Infect Dis. 1996;174704- 712
Link to Article
Katzenstein  DAHammer  SMHughes  MD  et al.  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. N Engl J Med. 1996;3351091- 1098
Link to Article
Center for Disease Control and Prevention, 1993 Revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR Morb Mortal Wkly Rep. 1993;41 ((RR-17)) 1- 19
Ledergerber  Bvon Overbeck  JEgger  MLüthy  R The Swiss HIV Cohort Study: rationale, organization and selected baseline characteristics. Soz Praventivmed. 1994;39387- 394
Link to Article
Schüpbach  JBöni  JTomasik  ZJendis  JKind  C Sensitive detection and early prognostic significance of p24 antigen in heat-denatured plasma of human immunodeficiency virus type 1-infected infants. J Infect Dis. 1994;170318- 324
Link to Article
Collett  D Modelling Survival Data in Medical Research.  London, England Chapman & Hall1994;
Sieczkowski  LChandran  BWood  C The human immunodeficiency virus tat gene enhances replication of human herpesvirus-6. Virology. 1995;211544- 553
Link to Article
Biggs  BAHewish  MKent  SHayes  KCrowe  SM HIV-1 infection of human macrophages impairs phagocytosis and killing of Toxoplasma gondiiJ Immunol. 1995;1546132- 6139
Telfer  PTBrown  DDevereux  HLee  CADuSheiko  GM HCV RNA levels and HIV infection: evidence for a viral interaction in haemophilic patients. Br J Haematol. 1994;88397- 399
Link to Article
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