Effect of Combination Therapy on Immunologic Progression of Human Immunodeficiency Virus at a Population Level
Tamiza Parpia1,
Gillian M. Raab1,
David J. Goldberg2,
Gwen M. Allardice2,
Jim McMenamin2,
Jim Whitelaw3,
Charles McSharry4,
Robert Potts5 and
Richard Herriot6
1 Applied Statistics Group, School of Mathematics, Napier University, Edinburgh, Scotland.
2 Scottish Centre for Infection and Environmental Health, Glasgow, Scotland.
3 HIV Immunology Unit, Edinburgh Royal Infirmary, Edinburgh, Scotland.
4 Department of Immunology, Western Infirmary, Glasgow, Scotland.
5 Department of Immunology, Ninewells Hospital, Dundee, Scotland.
6 Department of Immunology, Royal Infirmary, Aberdeen, Scotland.
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ABSTRACT
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There is accumulating evidence from clinical trials and cohort studies that highly active antiretroviral combination therapy is effective at halting immunologic and clinical progression of human immunodeficiency virus (HIV). Its impact at a population level is less well known because the regimes may be difficult to tolerate and compliance poorer. The authors make use of population data for almost all of the HIV-infected people in Scotland in 1997 who were under clinical care and monitor their response to therapy during the first year when these effective treatments became widely available. More than two thirds of the HIV-positive patients were on some form of antiretroviral therapy during the year. The authors show that all treated groups, even those who were on changing regimes, showed net improvement in immunologic status during the year. For the group of patients on triple or quadruple therapy, there was an average increase of more than 100 CD4 cells/mm3 over the year, with other treatment groups showing more modest, but significant, increases.
acquired immunodeficiency syndrome; CD4 lymphocyte count; HIV; treatment outcome
Abbreviations:
CD4 percent, CD4 counts as a percentage of the total lymphocyte counts; HIV, human immunodeficiency virus; HAART, highly active combination antiretroviral therapy
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INTRODUCTION
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Therapeutic trials provide strong evidence of a reduction in viral load, an increase in CD4 cell counts, and prolonged survival in human immunodeficiency virus (HIV)-infected persons treated with highly active combination antiretro-viral therapy (HAART) (1

4
). These effects have also been seen in cohort data; Egger et al. (5
) describe reduced disease progression and mortality with HAART in a Swiss HIV cohort during 19881996. Similar effects have been seen in the HIV-positive population of Scotland, with a reduction in deaths and in acquired immunodeficiency syndrome diagnoses (6
, 7
) that coincided with the availability of HAART from late 1996/early 1997.
In Scotland, almost all HIV-positive patients are treated in four regional centers, with treatment policies at each center determined by budgetary constraints imposed by local health authorities. We show that, during the first 12 months when HAART was available, treated patients no longer exhibited a decline in CD4 levels. We also document the proportion of patients who were maintained on therapy and the factors influencing this.
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MATERIALS AND METHODS
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Data sources
Since 1992, the Scottish Centre for Infection and Environmental Health has coordinated the Immunologic Monitoring Surveillance Scheme, collecting CD4 results and details of antiretroviral drugs taken in the preceding month. The data cover more than 95 percent of the patients in medical care for HIV in Scotland (8
). Prior to 1997, the treatment part of the form was never completed well. Accordingly, in January 1997, the form was simplified by replacing details of the drugs with two general questions: 1) Has the patient been on any antiretroviral drugs in the past month? 2) If yes, please tick one of the following: monotherapy; dual therapy; triple therapy; quadruple therapy or more; other. These questions resulted in much more complete data.
A total of 1,209 patients in the Immunological Monitoring Surveillance database were not known to have died or to have left the country as of December 31, 1997. Eighty-two percent (994 of 1,209) of these patients presented for a CD4 test in 1997 (table 1). A total of 13,324 CD4 test results were available on these 994 patients over the period January 1992 to December 31, 1997. A total of 3,548 of these tests were carried out during 1997, and the number of tests per patient ranged from 1 to 11. In 1997, 836 patents (84 percent) had five or fewer tests, and 166 had only one test.
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TABLE 1. Number of patients classified by treatment sequence group, Immunological Monitoring Surveillance Scheme, 1997
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Definition of treatment groups
Treatment information available at each CD4 test recorded in 1997 is classified as monotherapy, dual therapy, triple therapy, quadruple therapy, no treatment, or not known, if the questions were not completed by the reporting physician. A sequence of treatments taken during 1997 was derived for each patient to provide patterns in the uptake of treatment during the year. For the 21 percent of unknown values, data were imputed by "last value carried forward" from the patient's preceding test. The sequence of treatments in 1997 for each patient was classified as follows: 1) triple/quadruple: triple/quadruple at every test; 2) increasing: treatment increasing; 3) fluctuating: treatment decreasing or a combination of changes; 4) mono/dual: monotherapy or dual therapy at every test; 5) no therapy: not on treatment at any test; 6) not known: treatment not known at any test.
Statistical analyses
Trends in the uptake of treatment by risk group and center were investigated by log-linear analysis (9
). Random effects models (10
), fitted with SAS PROC MIXED (Version 6.11, SAS Institute, Cary, North Carolina) were used to estimate the effect of HAART on CD4 profiles for the 742 patients who had presented for monitoring in 1996 and in 1997. This compares the effectiveness of treatments in 1997 with that in earlier years. Since there was relatively little use of HAART before 1997 (10
), this will capture the major effect of its introduction.
The dependent variable was the square root of the CD4 counts as a percentage of the total lymphocyte counts (CD4 percent) with random patient-specific intercepts and slopes. Mean pretreatment intercepts and slopes were estimated for each group. Various models of the effect of treatment that allowed changes in the mean level and rate of decline in CD4 levels to occur on January 1, 1997 were compared. Details are in the thesis by Parpia (11
).
Choice of immunologic marker
Therapeutic decisions have generally been based on CD4 counts. However, there is considerable evidence (6
, 12

15
) that monitoring CD4 percent provides a better indication of disease progression, particularly when different laboratories are involved. For the purpose of presentation, the results can be converted to equivalent ranges of CD4 counts by using the method of instrumental variables (16
) (Appendix 1).
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RESULTS
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Trends in the uptake of treatment using a log-linear analysis
The log-linear analysis to investigate trends in the uptake of treatment showed that the CD4 level was the major predictor, but that there were differences between regions and, to a lesser extent, by risk groups. The main trends are shown in table 1. More than 90 percent of the patients with CD4 percent below 10 percent in 1996 were on some form of therapy, but only 24 percent of those with CD4 percent above 24 percent were on therapy. After adjustment for CD4 levels, patients treated in center 4 were more likely to be administered triple/quadruple therapy continuously than were those treated in centers 1, 2, and 3, where higher proportions are treated with mono/dual therapy.
Random effects models
For an adequate fit to the data, it was necessary to fit treatment-specific changes in mean level and in slope at January 1, 1997. Figure 1, left panel, shows the overall estimates of the treatment effects.

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FIGURE 1. Fitted values of CD4 percent from model 5. Each line corresponds to a 1997 treatment group in Scotland, in which 1 = triple/quadruple; 2 = increasing; 3 = fluctuating; 4 = mono/dual; and 5 = no therapy.
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Positive changes in average CD4 percent and in the rate of change of CD4 percent were seen in all treated groups. The greatest changes were seen in patients who received triple/quadruple therapy continuously and who were also the most immunosuppressed prior to the availability of HAART. Figure 1 shows the model of disease progression fitted separately to the data from centers 1, 2, and 3 together (center panel) and from center 4 (right panel). Table 2 gives the corresponding estimates of treatment effects and their 95 percent confidence intervals of square root CD4 percent. The effect of treatment appears to be somewhat different in the two center groupings. In center 4, it is characterized by a sharp increase in level at January 1, 1997, followed by little change during 1997. In centers 1, 2, and 3, the change in level at January 1, 1997 is less pronounced, but the increase during 1997 is greater. The overall change in the square root of CD4 percent from January 1, 1997 to January 1, 1998 is very consistent between centers. Patients on continuous triple/quadruple therapy show an increase of 0.94 over the year, those groups in which therapy is increasing or fluctuating increase by 0.54, and patients on monotherapy or dual therapy have a smaller increase of 0.32. In contrast, the levels for untreated patients declined by 0.26 during the year. The apparent differences between centers in the patterns of these increases during the year may relate to the particular regimes used, to compliance with treatment, or to the effects of drug therapy before 1997. The largest risk group in center 4 comprises homosexuals who are known to have better compliance to treatment regimens compared with injection drug users, the largest risk group in centers 1, 2, and 3 (17
). The results showed apparent differences in the effect of treatment by risk group, but these were not consistent between centers.
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TABLE 2. Estimates and 95% confidence intervals for the effect of treatment on square root CD4%*, Immunological Monitoring Group, 1997
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Since this is an observational study, there is the potential for our results to be affected by selection bias if the measured count value is used to determine the treatment allocation. Investigation of the scale of this bias showed that it was small (11
).
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DISCUSSION
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Caution is necessary in interpreting observational data, especially when studying treatment effects. However, the effects here are large and are unlikely to reflect selection bias. The largest effects of treatment were seen in patients on triple/quadruple therapy. Translating the results in table 2 into equivalent CD4 count (appendix 1), the average increase in 1997 for a patient with a count of about 200 m3 is 40 or more counts for monotherapy, 60 or more counts for patients changing or reducing therapy, and 130 or more counts for patients on triple/quadruple therapy. Veuglars et al. (18
) reported benefits of treatments on survival for HIV-infected persons at a population level, but this was before HAART.
We have presented group mean changes in CD4 percent slopes and intercepts. Plots for patients with several measurements in 1997 show differences between patients in response to therapy. Some patients' CD4 values continued to rise throughout the year, while others had an initial rise that was maintained at that value. These data support an analysis that attempts to identify groups that benefit most from therapy. The changing nature of therapeutic regimes will make this question difficult to answer in any case.
Our results confirm the beneficial effects of combination therapy, despite the recent worries over compliance and adherence rates. A major unanswered question is the extent to which these benefits will be found to continue over the medium to long term. This will depend crucially on future clinical and fundamental research into viral resistance and on the availability of even further generations of HIV therapeutic agents.
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APPENDIX I.
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Instrumental variables method for translating CD4 percent into absolute CD4 counts
The method of instrumental variables is used to fit a line when both the x and the y variables are subject to measurement error (16
). The data are grouped by factors that are not themselves correlated with measurement error. The mean values of x and y within each group are used to determine the relation between the true values of x and y, by "drawing" a line through the points. We grouped the patients by the presence or absence of a diagnosis of acquired immunodeficiency syndrome and by treatment groups. Appendix table 1 shows the corresponding values of CD4 percents and CD4 counts. We do not quote equivalent CD4 count and CD4 percent for low counts because the group means for low counts did not lie on a single line. There are various possible explanations for this, including laboratory differences in CD4 count measurement and the possibility that therapy may have a different effect on CD4 counts than on CD4 percents. Note that the corresponding values at 200 cells/mm3 and 500 cells/mm3 correspond to the levels stated by the Centers for Disease Control, Atlanta, Georgia (19
).
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ACKNOWLEDGMENTS
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Supported by research grant K/MRS/50/C2413 from The Chief Scientist's Office, Scottish Office Home & Health Department.
Thanks are due to our colleagues who have carried out the data management and organization of the Immunological Monitoring Surveillance study: L. Shaw, P. Cassels, B. Smyth, and G. Codere (Scottish Center for Infection and Environmental Health).
The authors also acknowledge the following collaborators: D. N. Bhattacharya, R. P. Brettle, D. Clutterbuck, G. Douglas, A. Downie, R. Fox, A. J. France, A. Ghaly, J. Harvey, R. Hillman, D. Kennedy, R. Laing, C. L. S. Leen, G. Lowe, C. Ludlum, L. Macallum, G. McKenna, A. McMillan, R. Nandwani, D. Nathwani, M. Pakinathan, A. Pithie, R. Robertson, G. Scott, A. Scoular, C. Smith, G. Sharp, A. Todd, E. Walker, P. Welsby, L. Wilks, G. Williams, P. L. Yap (HIV clinicians), S. Armstrong-Fisher, E. Galloway, J. Gibbs, I. Gray, H. Mason, C. Molyneaux, C. Ross, J. Westwater, and D. Wilson (HIV immunologists).
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NOTES
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Reprint requests to Professor Gillian M. Raab, Applied Statistics Group, School of Mathematics, Napier University, 10 Colinton Road, Edinburgh, EH10 5DT, Scotland (e-mail: G.Raab{at}napier.ac.uk).
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Received for publication March 17, 1999.
Accepted for publication August 30, 2000.