Changes in Plasma HIV-1 RNA and CD4+ Lymphocyte Counts and the Risk of Progression to AIDS
William A. O'Brien, M.S., M.D., Pamela M. Hartigan, Ph.D., David Martin, Pharm.D., James Esinhart, Ph.D., Andrew Hill, Ph.D., Sharon Benoit, M.P.H., Marc Rubin, M.D., Michael S. Simberkoff, M.D., and John D. Hamilton, M.D.
Background Clinical trials of antiretroviral drugs can takeyears to complete because the outcomes measured are progressionto the acquired immunodeficiency syndrome (AIDS) or death. Trialscould be accelerated by the use of end points such as changesin CD4+ lymphocyte counts and plasma levels of human immunodeficiencyvirus type 1 (HIV-1) RNA and 2-microglobulin, but there is uncertaintyabout whether these surrogate measures are valid predictorsof disease progression.
Methods We analyzed data from the Veterans Affairs CooperativeStudy on AIDS, which compared immediate with deferred zidovudinetherapy. Patients' plasma levels of HIV-1 RNA and 2-microglobulinwere measured in stored plasma.
Results Among the 129 patients in the immediate-treatment group,34 had disease that progressed to AIDS, as compared with 57of the 141 patients in the deferred-treatment group (P = 0.03).Progression to AIDS correlated strongly with base-line CD4+lymphocyte counts (P = 0.001) and plasma levels of HIV-1 RNA(P<0.001), but not with base-line levels of 2-microglobulin(P = 0.14). A decrease of at least 75 percent in the plasmalevel of HIV-1 RNA over the first six months of zidovudine therapyaccounted for 59 percent of the benefit of treatment, definedas the absence of progression to AIDS (95 percent confidenceinterval, 13 to 112 percent). Plasma 2-microglobulin levelsand CD4+ lymphocyte counts explained less of the effect of treatment.A 75 percent decrease in the plasma HIV-1 RNA level plus a 10percent increase in the CD4+ lymphocyte count could explain79 percent of the treatment effect (95 percent confidence interval,27 to 145 percent).
Conclusions Treatment-induced changes in the plasma HIV-1 RNAlevel and the CD4+ lymphocyte count, taken together, are validpredictors of the clinical progression of HIV-related diseaseand can be used to assess the efficacy of zidovudine and possiblyother antiretroviral drugs as well.
Assessments of the efficacy of antiretroviral therapy basedon clinical end points in patients with early or intermediatestages of human immunodeficiency virus (HIV) infection typicallytake many years.1-5 As new antiretroviral agents become available,retaining patients in randomized, prospective trials for longperiods will be increasingly difficult. Thus, to acceleratethe evaluation of new drugs, determining whether other markersof HIV type 1 (HIV-1) infection can be used to predict an effectof treatment is a matter of great interest.6
There are several candidate markers for HIV-1 infection.7-9The CD4+ lymphocyte count is the best characterized and is currentlyused as a guide for antiretroviral therapy. Although this countoften increases after the initiation of effective antiretroviraltherapy, counts can differ between treated and placebo (or control)patients even in the absence of a significant treatment effect.2,5Neopterin and 2-microglobulin levels are nonspecific markersof immune activation and tend to increase progressively duringthe course of HIV-1 disease,10-13 although their response totreatment and relation to the clinical progression of diseasehave not been extensively studied.
A more direct measure of antiviral response may be the decreasein levels of circulating virus.14 The measurement of plasmaHIV-1 RNA is more sensitive than the quantitation of eitherHIV-1 p24 core antigen in plasma or infectious virus in blood.15-17Plasma levels of HIV-1 RNA decrease profoundly after the startof antiretroviral therapy.18-20
The usefulness of quantitative methods to assess the efficacyof antiretroviral therapy against HIV-1 must be validated ina longitudinal, controlled trial that includes a treatment benefitfor the markers to explain.21 We performed a retrospective studyto determine whether changes in plasma levels of HIV-1 RNA,plasma levels of 2-microglobulin, and CD4+ lymphocyte countscould predict the likelihood of progression to the acquiredimmunodeficiency syndrome (AIDS) in patients in the VeteransAffairs trial of zidovudine therapy.
Methods
Study Population
Patients with symptomatic HIV-1 infection and 200 to 500 CD4+lymphocytes per cubic millimeter were enrolled in Veterans AffairsCooperative Studies Program trial 298, a blinded, randomizedcomparison of immediate with deferred zidovudine therapy. Theresults of part 1 of that study (conducted from January 1987through January 1991) have been published.1 All the patientsin the immediate-therapy group received open-label zidovudinefor the entire study period, whereas those in the deferred-therapygroup received placebo until their CD4+ lymphocyte counts fellbelow 200 cells per cubic millimeter or an AIDS-defining illnessdeveloped,22 when they were switched to open-label zidovudine.In addition, after part 1 of the study, there was a three-yearfollow-up period (from January 1991 to January 1994) duringwhich all the patients were offered open-label zidovudine.23In the current study, we evaluated a subgroup of the originalstudy population that included all patients for whom we hadbase-line plasma samples and at least one follow-up sample obtainedduring the six months after randomization. To record additionalinstances of clinical progression of disease and permit effectsof treatment to be shown in our subgroup, we extended the observationperiod to include the first year of the three-year follow-upperiod.
Plasma Samples
At intervals of one to four months during the trial, plasmaspecimens were collected, cryopreserved, and stored at repositoriesin Baltimore and Durham, North Carolina. Because the collectionand storage procedures at the two repositories differed, weused samples from only one repository for each patient (73 percentwere from Baltimore, where they were stored at -20°C, and27 percent were from Durham, where they were stored at -70°C).All the samples for a given patient were retrieved at the sametime from various freezer boxes and analyzed in a batch at theRoche Biomedical Laboratory, Research Triangle Park, North Carolina.For the quantitation of HIV-1 RNA in plasma, RNA was extractedfrom the plasma sample by the method of Boom et al.24 and thereverse-transcriptase polymerase chain reaction (PCR) was performedwith the GeneAmp kit (Roche Diagnostics, Nutley, N.J.).25 Plasma2-microglobulin was measured by radioimmunoassay (2-micro RIA,Kabi Pharmacia Diagnostics, Uppsala, Sweden). The methods usedto count CD4+ lymphocytes have been described elsewhere.1
Statistical Analysis
The Wilcoxon rank-sum test and the chi-square test were usedto compare groups with regard to continuous and discrete variables,respectively.26 In the time-to-event analyses, life-table methodsthat included Cox models were used, with stratification accordingto the place where the specimens were stored.27 The mean changefrom base line over the six-month period after randomizationwas our primary analytic measure of each marker. This changewas calculated for each patient as the mean of the measurementsobtained during the six months after randomization, minus thebase-line measurement. Plasma levels of HIV-1 RNA were expressedas the log10 of the number of copies of RNA per milliliter ofplasma in order to account for the wide range of values, whichencompassed more than five orders of magnitude. The value foreach marker was expressed as the percentage of change from baseline on the arithmetic scale.
The method proposed by Freedman et al.28 was adapted to validatethe use of the markers as surrogate end points. A sequence offour Cox proportional-hazards models that related each markerand the effect of treatment to the risk of progression to AIDS27was used, with adjustment in each model for base-line values.Model 1 measured the effect of treatment; model 2, the changein the marker; and model 3, both the effect of treatment andthe change in the marker. In model 4, a term for the interactionbetween the effect of treatment and the change in the markerwas added to model 3. The coefficients for the treatment effectin the model that also included the change in the marker (model3) were compared with those in the model for treatment only(model 1) in order to calculate the ability of the change inthe marker to "explain" the effect of treatment; these valueswere expressed as percentages. Bootstrap methods were used tocalculate 95 percent confidence intervals for these percentages,conditional on an effect of treatment.
Conditional relative risks and 95 percent confidence intervalsfor the magnitude of the effects of the markers were calculatedfrom the Cox models, which included base-line values and treatmenteffects. Patients were classified in one of four categoriesaccording to their responses to treatment during the study period,as determined by measurement of the markers. The classificationswere correlated with the progression to AIDS by means of life-tablemethods and validated with use of three indicator variablesas the marker in the first three steps of the modeling procedure.All analyses in this study were performed according to the intention-to-treatapproach, and all reported P values are two-tailed.
Results
There were sufficient cryopreserved plasma samples for 270 ofthe 338 patients in the original study population to be assessed(80 percent); of the 270, 129 were assigned to immediate therapyand 141 to deferred therapy. The number of copies of HIV-1 RNAand the 2-microglobulin level were measured in 2202 plasma samples(median number of samples per patient, 9; range, 2 to 17). Thecharacteristics of the 270 patients before treatment did notdiffer from those of the whole group of 338 patients, nor didthe characteristics differ between treatment groups. Among thepatients studied, HIV-1 disease progressed to AIDS in 34 membersof the immediate-therapy group and 57 members of the deferred-therapygroup (relative risk associated with immediate vs. deferredtherapy, 0.63; 95 percent confidence interval, 0.43 to 0.92;P = 0.03). The relative risk of death when the immediate-treatmentgroup was compared with the deferred-treatment group was notsignificant at any time in this study.
Effect of Base-Line Values on Outcome
When the base-line values for all three markers were analyzedindependently, each was related to the occurrence of progressionto AIDS, regardless of treatment group. In a multivariate Coxregression analysis, however, the base-line plasma level of2-microglobulin was not significant (P = 0.14), although thereremained strong relations between both the base-line plasmalevel of HIV-1 RNA (relative risk for each increase of 0.5 login the level, 1.27; P<0.001) and the base-line CD4+ lymphocytecount (relative risk for each increase of 35 CD4+ lymphocytesper cubic millimeter, 0.85; P = 0.001) and the progression toAIDS. In a bivariate Cox regression analysis, the base-lineplasma level of HIV-1 RNA (relative risk, 1.25; P<0.001)and base-line CD4+ lymphocyte count (relative risk, 0.82; P<0.001)were also strongly related to the incidence of death. Sincethe base-line values for both markers were important for outcome,all analyses of treatment or treatment-induced changes in eithermarker have been adjusted for the base-line values of that marker.
Changes in Markers over Time
The changes from base line in the CD4+ lymphocyte count andthe plasma level of HIV-1 RNA are shown in Figure 1A and Figure 1B.The treatment-induced increase in the CD4+ lymphocyte countwas smaller and more short-lived than the corresponding decreasein the plasma HIV-1 RNA level, which did not return to the base-linevalue for 12 months. Levels of 2-microglobulin had a substantialtreatment-induced decline, similar to the decline in plasmaHIV-1 RNA (data not shown). The values in the deferred-therapygroup were affected by the crossover of patients from placeboto open-label treatment with zidovudine, which occurred a meanof 16 months (range, 1 to 24) after the start of the study in114 of the 141 patients.
Figure 1. Changes from Base Line in the CD4+ Lymphocyte Count (Panel A) and the Log10 Number of Copies of HIV-1 RNA in Plasma (Panel B) in the Two Treatment Groups.
Positive numbers indicate an increase, and negative numbers a decrease. When multiple measurements were made in a patient close to a given time, only the measurement made closest to that time is shown. The numbers of patients shown do not decrease linearly over time because not all patients were tested at each time point. Vertical bars denote 95 percent confidence intervals.
Relation between Treatment-Induced Changes in Markers and Progression to AIDS
We used Cox models to summarize the relation between the meanchanges in markers during the six months after randomizationand the progression to AIDS. In the univariate model, the relativerisk for each increase of 0.5 log in the plasma level of HIV-1RNA was 1.5 (95 percent confidence interval, 1.23 to 1.83; P<0.001).For each increment of 35 CD4+ lymphocytes per cubic millimeter,the relative risk was 0.83 (95 percent confidence interval,0.76 to 0.91; P<0.001), and for each increment of 0.33 µgper milliliter in the plasma level of 2-microglobulin, the relativerisk was 1.11 (95 percent confidence interval, 0.99 to 1.24;P = 0.08). We also performed these analyses using changes ofvarious magnitudes, including decreases in plasma levels ofHIV-1 RNA by factors of three to seven, 5 to 25 percent increasesin the CD4+ lymphocyte count, and 5 to 25 percent decreasesin the plasma level of 2-microglobulin. Table 1 shows the resultsof the univariate and multivariate analyses in which the valuesclosest to the mean change for each marker were used as thresholds:a decrease of 75 percent (0.6 log) in the plasma level of HIV-1RNA, a 10 percent increase in the CD4+ lymphocyte count, anda 15 percent decrease in the plasma level of 2-microglobulin.These data show the importance of the relations between theprogression to AIDS and these changes in the plasma HIV-1 RNAlevel and the CD4+ lymphocyte count. For the other specifieddegrees of change in each marker, the results were similar.
Table 1. Cox Models Relating Changes in Markers and Antiretroviral Treatment to the Risk of Progression to AIDS.
Validation with Mean Values during the Six Months after Randomization
Detailed results of the validation analyses of the effect ofa 75 percent decrease in the plasma level of HIV-1 RNA and a10 percent increase in the CD4+ lymphocyte count from the base-linevalues are provided for both markers in Table 2. A significantbenefit of treatment in terms of the progression to AIDS wasfound in model 1 for each marker (P = 0.03). A 75 percent decreasein the plasma level of HIV-1 RNA during the six months afterrandomization markedly reduced the risk of progression to AIDS,as shown in model 2 (P<0.001), regardless of treatment group.When treatment assignment and the change in the plasma levelof HIV-1 RNA were considered together in model 3, the treatmentassignment was no longer significant (P = 0.33), but a decreasein the plasma level of HIV-1 RNA remained significant (P = 0.004),indicating the importance of such a decrease as a predictorof the progression to AIDS. The interaction between treatmentand either marker, shown in model 4, was not significant.
Table 2. Sequential Cox Proportional-Hazards Models Relating Progression to AIDS to Antiretroviral Treatment and Either a 75 Percent Decrease from Base Line in the Plasma HIV-1 RNA Level or a 10 Percent Increase from Base Line in the CD41 Lymphocyte Count.
The proportion of the effect of treatment or trend toward reductionin the rate of progression to AIDS that was explained by theplasma level of HIV-1 RNA was estimated by dividing the differencebetween the coefficients for model 3 and model 1 by the coefficientfor model 1; this estimate was 59 percent (95 percent confidenceinterval, 13 to 112 percent). The percentage of the treatmenteffect that was explained by decreases from base line in plasmaHIV-1 RNA levels by factors of three, five, and seven was alsoapproximately 60 percent, whereas a decrease by a factor of10 explained 42 percent of the treatment effect. In these analysesof changes of varying magnitudes in the plasma level of HIV-1RNA, the differences between the treatment groups were significantin each case (P<0.005 for all).
The proportion of the treatment effect accounted for by a 10percent increase in the CD4+ lymphocyte count was 31 percent(95 percent confidence interval, 4 to 58 percent). The effectof a given increase in the CD4+ lymphocyte count ranged from22 percent of the treatment effect (for a 5 percent increase)to 37 percent (for an increase of either 15 or 25 percent) (P<0.01for all these changes). The proportion of the effect of treatmentexplained by a 15 percent decrease in the plasma level of 2-microglobulinwas 28 percent, but the effect of this or any other degree ofchange that was tested for this variable was not significant(P>0.05 for all). When continuous changes in plasma HIV-1RNA levels were analyzed, the percentage of the treatment effectthat was explained was higher than when thresholds of changewere analyzed. Thus, we found that a decrease in the plasmalevel of HIV-1 RNA was a better predictor of outcome than waseither an increase in the CD4+ lymphocyte count or a decreasein the plasma level of 2-microglobulin.
Classification of Patients and Combinations of Markers
We analyzed pairwise combinations of markers, using six-monthmean changes of at least a 75 percent decrease in the plasmalevel of HIV-1 RNA, a 10 percent increase in the CD4+ lymphocytecount, and a 15 percent decrease in the plasma level of 2-microglobulin.The effect of treatment was best explained by a decrease ofat least 75 percent in the plasma level of HIV-1 RNA and anincrease of at least 10 percent in the CD4+ lymphocyte count.We then classified the patients into four groups, as follows:group 1 included patients with a decrease in plasma HIV-1 RNAof 75 percent or more and an increase in the CD4+ lymphocytecount of 10 percent or more; group 2, patients with a decreasein plasma HIV-1 RNA of 75 percent or more and an increase inthe CD4+ lymphocyte count of less than 10 percent; group 3,patients with a decrease in plasma HIV-1 RNA of less than 75percent and an increase in the CD4+ lymphocyte count of 10 percentor more; and group 4, patients with a decrease in plasma HIV-1RNA of less than 75 percent and an increase in the CD4+ lymphocytecount of less than 10 percent. When we validated this classificationsystem as a marker of the risk of progression to AIDS, 79 percentof the effect of treatment was explained by its use (95 percentconfidence interval, 27 to 145 percent). Although this is morethan the 59 percent obtained with the use of HIV-1 RNA levelsalone, there is no statistical method available with which totest the difference between the percentages. Combinations ofmarkers that did not include the plasma level of HIV-1 RNA hadconsistently lower predictive value than those that includedthat variable.
We performed a life-table analysis using this classificationsystem, without taking treatment assignment into account. Thepatients in group 1 had the best outcome, whereas the patientsin group 4 had the worst. In the other two groups the resultswere intermediate. Figure 2 shows KaplanMeier curvesfor this analysis, which demonstrate that the plasma level ofHIV-1 RNA and the CD4+ lymphocyte count, used in combination,are a good predictor of the progression to AIDS.
Figure 2. KaplanMeier Analysis of the Time to the Progression to AIDS in Patients Found to Have Both a Six-Month Mean Decrease of at Least 75 Percent in Plasma HIV-1 RNA and a Six-Month Mean Increase of at Least 10 Percent in the CD4+ Lymphocyte Count, One of These Changes, or Neither Change.
Discussion
We evaluated plasma levels of HIV-1 RNA and 2-microglobulinand CD4+ lymphocyte counts as markers of HIV-1 disease becausethey are affected by viral or immune events associated withclinical progression. The results of the study showed that amongthese markers, changes in plasma HIV-1 RNA explain the effectof treatment on clinical outcome the most reliably and thatchanges in the CD4+ lymphocyte count provide additional information.Although there are extravascular sites of viral replication,it is probable that circulating levels of HIV-1 RNA best reflectthe overall replication of the virus in vivo.29,30 This reportshows that treatment-induced changes in HIV-1 RNA can accountfor the clinical outcome of HIV-1 infection in symptomatic patientsat an intermediate stage of disease (with CD4+ lymphocyte countsof 200 to 500 cells per cubic millimeter).
Recent reports have demonstrated a dynamic interaction betweenthe replication of HIV-1 and the destruction of CD4+ lymphocytes.19,20When effective antiretroviral therapy is begun, levels of HIV-1replication decline steeply over a period of one to two weeksand the CD4+ lymphocyte count increases correspondingly.18-20,31The availability of assays with which to quantify HIV-specificRNA permits the assessment of treatment-induced changes in viralreplication, which cannot be done by measuring levels of HIV-1DNA in blood or using any other method of detecting HIV-1.18-20,31-34
In our study, the base-line CD4+ lymphocyte count and plasmalevel of HIV-1 RNA were highly predictive of both the progressionto AIDS and death, which suggests that both variables are usefulmarkers of the disease stage. Recently, Mellors et al.35 showedthat plasma levels of HIV-1 RNA exceeding 10,000 genome equivalentsper milliliter were strongly associated with the progressionto AIDS over a mean period of follow-up lasting nearly fiveyears. Those investigators found that plasma levels of HIV-1RNA predicted clinical outcome independently of CD4+ lymphocytecounts. This finding reinforces our contention that base-lineplasma levels of HIV-1 RNA and CD4+ lymphocyte counts may beused together in determining clinical stages of disease andin therapeutic decision making. Although relative values canbe compared, the relations between absolute plasma levels ofHIV-1 RNA and outcome are difficult to determine from our study,because of the storage conditions and age of the samples; theseassociations should be examined with fresh samples.
Although the CD4+ lymphocyte count is a useful marker in determiningthe stage of HIV disease, it has not been particularly usefulas a marker of the clinical response to antiretroviral therapy.A retrospective analysis of data presented by Volberding etal.3 showed that the base-line CD4+ lymphocyte count was highlycorrelated with the progression to AIDS (P<0.001). Even so,only a small proportion of the effect of zidovudine on thisprogression (less than 37 percent) was statistically explainedby the effect of the drug on the CD4+ lymphocyte count36 a finding similar to ours and to those of others.9,37 In anotherstudy, the duration of the increase in the CD4+ lymphocyte countin response to antiretroviral therapy appeared to be more importantin predicting disease progression than the magnitude of theinitial response.38
The appropriate measure must be found with which to evaluateantiretroviral therapy in HIV-infected patients with variousstages of disease, particularly those with different base-linelevels of HIV-1 RNA in plasma. On the basis of our data, thisshould be a reduction by a factor of at least three (i.e., by0.5 log) in the plasma level of HIV-1 RNA. The rapid appearanceof resistance to some antiretroviral agents, such as the non-nucleosideinhibitors of reverse transcriptase,39 and the short-lived responseof plasma HIV-1 RNA levels to therapy suggest that the durationof the effect on plasma HIV-1 RNA should also be considered.31,40It is likely that a longer-lasting reduction in the plasma levelof HIV-1 RNA may be associated with greater clinical efficacy.The goal of antiretroviral therapy should be to reduce levelsof circulating virus as much as possible, for as long as possible.The ability to use reverse-transcriptase PCR to measure thetreatment-induced decline in plasma levels of HIV-1 could speedthe evaluation of new therapies in prospective trials, whileclinical data continue to be collected for subsequent correlationwith measurements of changes in markers, including both theCD4+ lymphocyte count and virologic markers.
Supported in part by Medical Research Funds from the Departmentof Veterans Affairs; by the Veterans Affairs Research Centerson AIDS, Durham, N.C., and New York; and by a grant from GlaxoWellcome,Inc.
* The institutions and investigators participating in the VeteransAffairs Cooperative Study Group on AIDS are listed in the Appendix.
Source Information
From the Department of Medicine, West Los Angeles Veterans Affairs Medical Center and University of California at Los Angeles Medical School, Los Angeles (W.A.O.); the Veterans Affairs Cooperative Studies Program Coordinating Center, West Haven, Conn. (P.M.H.); the University of North Carolina, Chapel Hill (D.M.); Glaxo, Inc., Research Triangle Park, N.C. (J.E., A.H., S.B., M.R.); the New York Veterans Affairs Medical Center and New York University School of Medicine, New York (M.S.S.); and the Durham, N.C., Veterans Affairs Medical Center and Duke University Medical Center, Durham, N.C. (J.D.H.). Presented in part at the 10th International Conference on AIDS, Yokohama, Japan, August 712, 1994, and the 2nd National Conference on Human Retroviruses and Related Infections, Washington, D.C., January 29February 2, 1995.
Address reprint requests to Dr. O'Brien at the West Los Angeles VA Medical Center, 11301 Wilshire Blvd., Los Angeles, CA 90073.
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Appendix
In addition to the authors, the following members of the VeteransAffairs Cooperative Study Group on AIDS participated in thisstudy: Houston Veterans Affairs Medical Center (VAMC) C. Lahart and N. Wray; West Los Angeles VAMC S.M. Finegoldand W.L. George; Miami VAMC G.M. Dickinson and N. Klimas;New York VAMC G. Diamond and S.B. Zolla-Pazner; SanFrancisco VAMC P.C. Jensen; Walter Reed Army Hospital,Washington, D.C. C. Hawkes and C. Oster; Washington,D.C., VAMC F. Gordin and A.M. Labriola; Durham, N.C.,VAMC P. Spivey; Duke University Virology Center T. Matthews and K. Weinhold; and University of Maryland PharmacologyLaboratory G. Drusano and M.J. Egorin.
Viral Load and Response to Treatment of HIV
Ioannidis J. P.A., Cappelleri J. C., Lau J., De Gruttola V., Fleming T., Coombs R., Fessel W. J., O'Brien W. A., Hartigan P., Hamilton J. D.
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N Engl J Med 1996;
334:1671-1673, Jun 20, 1996.
Correspondence
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