Proposed CD4+T-Cell Criteria for Staging Human Immunodeficiency Virus-Infected Chinese Adults

CLINICAL IMMUNOLOGY AND IMMUNOPATHOLOGY

Vol. 89, No. 1, October, pp. 11–22, 1998 Article No. II984570

Proposed CD41 T-Cell Criteria for Staging Human Immunodeficiency Virus-Infected Chinese Adults1 Kai Man Kam,*,2 Ka Hing Wong,† Patrick Chung Ki Li,‡ Shui Shan Lee,† Wai Lin Leung,* and Mei Yee Kwok* *Pathology Service, Department of Health, Hong Kong Special Administrative Region Government, Sai Ying Pun, Hong Kong; †AIDS Unit, Department of Health, Yaumati Polyclinic; and ‡Special Medical Service, Queen Elizabeth Hospital, Kowloon

urgent need to examine the parameters which have traditionally been used to stage, monitor, and guide therapy for HIV-positive individuals and assess the possible use of these criteria in our HIV-infected population. In particular, although CD4 is widely used as a surrogate marker, there has not been any longitudinal study of its use in monitoring an HIV-infected Chinese adult population. Using standardized and quality-controlled flow cytometric techniques, we previously determined the lymphocyte subset reference ranges in HIV-negative Chinese adults and found significantly lower CD4 values but higher natural killer (NK) cell values, in terms of both absolute counts and percentage peripheral lymphocytes, in our healthy adult population compared with the Caucasian adult (17, 18). We have also correlated clinical events with CD4 and found significantly lower CD4 values for AIDS-defining conditions in our HIV-infected patients (19, 20). In this study, we present longitudinal data on changes in CD4 over a 30-month period. With these results, we propose a set of CD4 values which can be used as criteria for staging HIV-infected Chinese adults. Using estimation of proportion survival by stratified baseline CD4 values and the measurement of death incidences as the basis of analyses, we performed a comparison between the Centers for Disease Control and Prevention (CDC) CD4 criteria and our proposed criteria in our study population. We also assess the potential impact on initiation of current antiretroviral treatment (ART) and Pneumocystis carinii pneumonia prophylaxis (PCPP) when using the CDC recommended criteria compared to our proposed set of values.

The present treatment, prophylaxis, and prognostic staging of human immunodeficiency virus (HIV) disease rely heavily on peripheral CD41 T lymphocyte (CD4) changes. We correlated the clinical course of events and CD4 changes among consecutive HIV-infected ethnic Chinese adults in Hong Kong. Using death as end point, the estimated proportion survival and death incidences were used to compare CDC and proposed staging criteria based on stratified baseline CD4. A separate set of baseline CD4 per microliter (/ml) (percentage lymphocytes) stratification criteria of 1, >220/ml (>12%); 2, 100 –220/ml (6 –12%); and 3, <100/ml, (<6%) is proposed which can be used for staging HIVinfected Chinese adults. For our study population, our proposed criteria for stratifying baseline CD4 gave better discrimination and more predictive power than the CDC criteria. We assessed the potential impact of these new proposed criteria on anti-retroviral treatment and prophylaxis against opportunistic infections in our adult HIV-infected population. © 1998 Academic Press INTRODUCTION

Since the discovery of the human immunodeficiency virus (HIV) and the accompanying peripheral CD41 T-lymphocyte (CD4) changes in acquired immunodeficiency syndrome (AIDS) in the human host (1–3), most of the guidelines and recommendations (4) on staging (5–7), treatment (8 –10), and prophylaxis (11, 12) regimens have been based on studies done in developed countries. Data on use of these guidelines in less developed areas have been few, except in parts of Africa (13–15). Since the next wave of HIV infections and AIDS will be expected to occur in Asia (16), we felt the 1 Part of this work was presented at the First Joint Meeting of Japan Cytometry Society and the International Society for Analytical Cytology, Hachimantai National Park, Iwate, Japan, October 1–3, 1997. 2 To whom correspondence should be addressed at Room 802, 8/F, Public Health Laboratory, Department of Health, Hong Kong Special Administrative Region Government, 134 Queen’s Road West, Sai Ying Pun, Hong Kong. Fax: (852) 2858-2684.

METHODS AND MATERIALS

Study Population In Hong Kong, all new HIV infections are currently reported voluntarily to the Department of Health, which provides a centralized counseling, assessment, 11

0090-1229/98 $25.00 Copyright © 1998 by Academic Press All rights of reproduction in any form reserved.

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KAM ET AL.

monitoring, and treatment service to the HIV-infected individual on an anonymous basis. Over 90% of reported HIV cases in the territory are seen at either of two public Special Medical Clinics which cater to the specific needs of the HIV-positive patient. All of these HIV-positive patients attended these two clinics voluntarily and were recruited for the present study. We included all patients of Chinese ethnicity, over the age of 14 years, who attended these two clinics between the period January 1, 1994, and June 30, 1996, completed a full clinical assessment, staged according to CDC clinical criteria, and had blood taken for CD4 cell estimation. All patients were seropositive for HIV type 1 by enzyme-linked immunosorbent assay and as confirmed by Western blot. All peripheral blood taken from these two clinics for the purpose of CD4 estimations was analyzed at one flow cytometric immunophenotyping laboratory by trained and experienced technical staff. Patients of non-Chinese ethnicity comprised only a small percentage of attending patients and were excluded from analysis. There was no selection of patients and there were no reporting delays. Follow-up of Cohort At each visit in the two HIV clinics, each patient was assessed and staged independently according to CDC clinical criteria into stage A, B, or C (4). In order to ensure strict adherence to CDC criteria for clinical staging, all patient records were reviewed and resolved by two of us (K.H.W. and P.C.L.) to minimize possible disparate clinical observations. The follow-up period was counted from the day when the baseline CD4 was taken (time 0) and the last date of follow-up at either clinic or the date of death. Subsequent timing of CD4 determinations is derived from time 0; i.e., times 1, 2, 3, 4, and 5, equal an interval of 6, 12, 18, 24, and 30 months from time 0, respectively. The date of seroconversion was known for eight cases and these were included as time 0 in stage A. At each follow-up at 3-month intervals, each patient was assessed clinically and staged, and peripheral blood was taken for CD4 estimation. For patients who missed a follow-up visit but were readmitted later on, the time period between the two CD4 estimations was adjusted accordingly. For patients who progressed from one clinical stage to the next during the 30-month period, the date of determination of the new clinical stage was taken as time 0 of that new clinical stage, and the time for previous CD4 determinations was similarly adjusted for the previous stage. For those who presented very late and died soon after diagnosis of AIDS, the determination of CD4 (,6 months) before death was taken as time 5 in stage C. Time to death, rather than time to development of AIDS, was taken as end point in each case to minimize

possible subjective elements which may be present in establishing a diagnosis of AIDS. Determination of Lymphocyte Subsets Peripheral blood taken for CD4 estimations was collected between approximately 9:00 AM and 12 noon on the day of analysis. Blood samples were drawn simultaneously for the hematology laboratory and for flow cytometric analysis. Absolute counts of cells were obtained by multiplication of the percentage of lymphocytes (% lym) by the leukocyte differential obtained from a simultaneous blood sample analyzed with an automated hematological instrument (Coulter MAXM; Coulter Corp., Miami, FL). A standardized method using a recommended panel (21) of two-color combinations of fluorescein isothiocyanate (FITC)- and phycoerythrin (PE)-conjugated monoclonal antibody reagents obtained from a single manufacturer (Becton Dickinson, San Jose, CA) was used to determine the expression of each antigen or antigen combination. Data acquisition was performed on configured FACScan flow cytometers and appropriate quality control procedures were done as described elsewhere (18). As an additional quality check, all blood specimens for CD4 estimations were also simultaneously analyzed on a separate instrument (FACSCount) with the given set of reagents according to the manufacturer’s instructions, which gave an absolute count of CD4 cells per microliter (/mL) only. All reported results are from the FACScan instrument. The results of the FACSCount machine were then compared and correlated with those generated from the FACScan instrument. Statistical Analysis 1. Evaluating the change in CD4 over time. (a) For individuals with two CD4 determinations done at 3-month intervals, the mean of the two values was taken for that 6-month period. The means and standard deviations (SD) of CD4 were calculated and plotted for changes within the 30-month study period with respect to the different clinical stages. The separations between different clinical stages were read from this longitudinal plot (Fig. 1). (b) In order to overcome the possible heterogeneity in baseline CD4 measurements of the study population, we also analyzed the observed CD4 counts changes for each clinical stage (A, B, and C) by splitting up the CD4 observations into each stage. Each individual may contribute data to one or the other stages. For each consecutive pair of observations on the same person, the change in CD4 was then calculated. Individuals contributing only one observation will not contribute to the change. The distribution of values of CD4 change per day were then analyzed and the median and interquartile range values determined.

CD4 FOR STAGING HIV1 CHINESE

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FIG. 1. Correlation between FACScan (Y axis) and FACScount (X axis) CD41 T-lymphocyte values. The FACScan values were obtained by multiplying the percentage lymphocyte (FACScan) by the absolute lymphocyte values (Coulter MAXM). The FACScount values were read directly from the software (version 1.2). The regression formula is y 5 1.012x 23.507 and R2 5 0.974.

2. Comparing the two staging systems. (a) Time to death distributions were obtained using KaplanMeier curves (22). The x2 log-rank test statistic was used to measure prognostic significance of the CDC clinical staging (Fig. 2) and to compare the CDC methods and proposed methods of stratification of baseline CD4 levels (Fig. 3). The CD4 groupings were according to CDC staging criteria of CD4/mL (% lym) of: 1 5 .500 (.28%), 2 5 200 –500 (14 –28%), and 3 5 ,200 (,14%), while those of our proposed set of CD4 stratification criteria, i.e., 1 5 .220 (.12%), 2 5 100 –220 (6 –12%), 3 5 ,100 (,6%), were based on observations from our longitudinal study (Fig. 1) and gave a clear separation between the different groupings with respect to the Kaplan-Meier curves (Figs. 4A– 4D). Statistical significance of x2 values, the relevant degrees of freedom with the corresponding P values, and 95% confidence intervals (95% CI) were calculated using standardized methods (23). All reported P values are two-tailed. (b) In addition to the time to death analysis, the incidence of death for each of the CDC staging and the proposed staging systems was compared. The denominator was the sum of the number of personyears of observation for each stage separately. Only the time between the baseline CD4 count and either the time of death or the time at which the last CD4 measurement was taken into account in the denominator. If someone changes stages, the time is split equally among the appropriate denominators of the

stages. For example, consider someone had the following measurements: Time from initial visit (days): CD4:

0 100 200 400 600 800 1000 1300 700 606 450 420 320 203 101 dead.

Then the contribution to the stage 1 denominator was taken as 150 person-days: 100 from the first interval and 50 from the second interval. The contribution to the stage 2 denominator would be 700 person-days: 600 from time 200 to time 800 and then 100 from time 800 to time 1000. Classification of each death, the numerator, that occurred in stages 1, 2, and 3 was done by looking at the CD41 cell count taken closest to death. If the last CD4 measurement was above 500, then that death is included in the numerator of the incidence of death for CDC stage 1; if between 500 and 200, included in the numerator of incidence for CDC stage 2; if below 200, then the death contributes to stage 3. For the purpose of comparison with the proposed staging system, the data set was reanalyzed using proposed cut-off breakpoints of CD4 values 220 and 100 in place of the CDC values of 500 and 200, respectively. RESULTS

Of a total of 254 ethnic Chinese patients who attended the two HIV clinics and had their blood collected for CD4 determination during the study period, 238 (93.7%) were included while 16 (6.3%) were excluded because of incomplete history and other data. As we included all cases who presented in the two

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KAM ET AL.

FIG. 2. Changes in CD41 T-lymphocyte mean 6 SD (Y axis) over 30 months (X axis, in 6-month intervals) in the three clinical stages A, B, and C (CDC clinical criteria) of HIV-infected Chinese adults. Time 0 is time of first blood collection for CD41 determination or progression from the preceding clinical stage. Time 5 in clinical stage C is the time of last follow-up or death. The number of observations for stages A, B, and C at time 0 was 234, 130, and 104, respectively.

clinics, there were no available data on nonparticipants including those HIV cases that were not reported at all or were reported but not seen in the two clinics. For cases who defaulted follow-up, no information could be obtained anywhere to determine their subsequent course of disease or death. Baseline Characteristics of Study Population Table 1 shows the baseline characteristics of the study population. Males (206, 86.6%) comprised the major part of cases, with peak age occurring in the 40 – 49 years group (44.2%) while that for females was in the younger, 30 –39 years group (42.5%). This distribution reflected the general scene of notified HIV cases in the territory. Heterosexual transmission was the most common (41.2%) identified route while the risk behavior of homosexual/bisexual practices and IV drug abuse constituted 36.6 and 2.1%, respectively. The distribution of length of follow-up period showed a fairly even distribution of censored cases from 100 to 700 days (mean 330 days, SD 233 days) and provided 200.8 person-years of experience. The mean, median, 25th percentile, 75th percentile, and SD of baseline CD4/mL (% lymphocytes) were 300 (16%), 290 (17%), 80 (7%), 470 (23%), and 238 (9.9%), respectively. For patients in clinical stages A, B, and C, 31 (22.1%), 26 (52%), and 45 (93.8%) received both zidovu-

dine (AZT) treatment and PCPP, respectively, at some time during the study period, while another 41 (29.3%), 7 (14.0%), and 0 (0%) received AZT only, and another 1 (0.7%), 5 (10.0%), and 1 (2.1%) received PCPP only. This gave a total of 73 (52.1%), 38 (76.0%), and 46 (95.8%) patients who received either AZT or PCPP in any amount for any time during the study period for stages A, B, and C, respectively. A small percentage of patients received some ddI, ddC, or d4T at some stage of the disease. Because of the small numbers, these forms of ART, other than AZT, were not included in our analyses. None received AZT on entry or any protease inhibitors during the course of study. Correlation between FACScan and FACScount Results The flow cytometric results from the two sets of machines were compared and correlated to see how much they differed. Figure 1 illustrates the excellent correlation between CD4 results generated from the two instruments used and helps to confirm the reliability of CD4 values used in the study. Longitudinal Study of CD4 T-Cell Changes Figure 2 shows the changes in CD4 T-cells in the three clinical stages analyzed by method 1a above. Of a

CD4 FOR STAGING HIV1 CHINESE

total of 1043 CD4 determinations made for the 238 individuals (i.e., mean of 4.4 observations per patient), 565 (54.2%), 279 (26.7%), and 199 (19.1%) were from patients in clinical stages A, B, and C (AIDS), respectively. During the 30-month study period, 29 and 7 patients progressed from stage A to B and from stage B to C, respectively. The mean CD4/mL (% lym) dropped from that in normal healthy adults of 725, SD 256 (36.4% SD 7.5%) to 447 SD 232 (21.8% SD 7.5%) at time 0 in stage A. If the entry point to stage A (time 0) was the nearest point to seroconversion (assuming a 6-month period from infection to seroconversion), this represented a 38.3% drop of CD4 cells in this period. At time 5 (30-month) of stage A, the mean CD4 value of 211/mL SD 168 (12.0% SD 6.8%) was very close to the mean value of CD4 of 228/mL SD 178 (13.7% SD 8.4%) at time 0 of stage B patients, meaning a decline of 47 (2.0%) CD4 cells per 6 months throughout the stage A period. Examination of stage B patients showed a slower decline of 31 (1.2%) CD4 cells per 6 months. No significant difference in rate of decline of CD4 cells was found between stage A patients who did or did not receive any AZT at any time. However, a

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TABLE 1 Baseline Characteristics of Study Population Females Males

32 206

Age (years)

M

(%)

F

(%)

10–19 20–29 30–39 40–49 50–59 60–69 70–79 80–89

1 5 64 91 24 15 5 1

0.5 2.4 31.1 44.2 11.7 7.3 2.4 0.5

0 3 14 9 4 2 0 0

0 9.4 42.5 28.3 12.5 6.3 0 0

Total

206

100

32

100

Risk Behavior/Factor

N

(%)

Homo/bisexual Heterosexual Hemophiliac IV drug abuser Transfusion before 1985 Undetermined

87 98 29 5 1 18

36.6 41.2 12.2 2.1 0.4 7.6

Total

238

100

Distribution of length of follow-up period Days

N

(%)

0–99 100–199 200–299 300–399 400–499 500–599 600–699 700–799 .799 Mean SD

62 31 32 27 24 25 24 12 1 329.5 233.3

26.1 13.0 13.4 11.3 10.1 10.5 10.1 5.0 0.4

Clinical stage at presentation

N

(%)

Stage A Stage B Stage C

FIG. 3. Kaplan-Meier curves for estimated proportion survival of HIV1 Chinese adults stratified by baseline CDC clinical staging criteria. Numbers of patients at risk at 200, 400, and 600 days are stage A, 112, 82, and 56; stage B, 39, 26, and 12; and stage C, 33, 18, and 8, respectively.

149 46 43

62.6 19.3 18.1

Baseline value

CD4 (% lym)

Median 25% tile 75% tile

17 7 23

CD4 (/mL) 290 80 470

slightly slower rate of decline was found in stage B patients who received AZT at any time, i.e., 29 (1.2%) CD4 cells per 6 months (95% CI: 9 – 49 cells (0.1–2.4%) per 6 months), than those who did not, i.e., 66 CD4 (2.7%) cells per 6 months (95% CI: 25–107 cells (0.9 – 4.5%) per 6 months).

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KAM ET AL.

At time of diagnosis of AIDS (stage C), the mean CD4 cells at entry (time 0) was 72/mL SD 75 (6.8% SD 6.4%) which declined at a rate of 11 (0.9%) CD4 cells per 6 months to mean of 15/mL SD 5 (2.5% SD 0.5%) CD4/mL at time 5. There was, however, a slight rise of CD4 in terms of both absolute counts and % lym from time 1 (6 months) to time 3 (18 months) before a sustained fall to time 5. There were too few patients in stage C that were not treated by AZT to assess a possible difference in rate of decline of CD4 cells among those did or did not receive AZT therapy. Longitudinal study, therefore, showed that the transition between CDC clinical stages A and B occurred at a CD4 of 220/mL (12%) while that of stage B and C occurred at 100/mL (6%). During the study period, a total of 31 patients died from AIDS-related conditions, giving a crude death rate of 15.4 per 100 person-years from the time of blood being taken for CD4 estimation. The changes in CD4 over time were evaluated by statistical method 1b above. The median (interquartile range) changes in CD4 cells per month for each clinical stage A, B, and C were 29.72 (219.9 to 16.45), 22.90 (212.2 to 15.46), and 21.40 (26.93 to 13.15), respectively. These results also confirmed that the CD4 decline was most pronounced for clinical stage A and that in stage B was more pronounced than that in stage C. CDC Clinical Staging Figure 3 shows that the Kaplan-Meier estimates of the proportion (95% CI) of patients surviving stratified according to baseline CDC clinical stages A, B, and C were, respectively, 0.98 (0.95–1.0), 0.84 (0.71– 0.97), and 0.66 (0.48 – 0.84) at 12 months; and 0.97 (0.89 – 1.0), 0.57 (0.27– 0.88), and 0.52 (0.16 – 0.88) at 24 months (log rank x2 37.9). No statistically significant difference in estimated proportion survival was found between those patients who received or did not receive AZT treatment in stages A and B (x2 5 0.12, P 5 0.42). There were too few patients who were at stage C and did not receive any AZT at all to give valid comparisons with those who received AZT at this stage. Comparison of the Two Staging Systems: Baseline CD4 T-Cell for Staging In view of the longitudinal study of CD4 changes during the clinical course of HIV infection in the Chinese adult, we attempted to compare the prognostic significance of baseline CD4 values stratified according to CDC criteria and that of our proposed criteria. Figures 4A– 4D show the Kaplan-Meier estimates of proportion survival using these two different staging criteria. When the CDC criteria of absolute counts of 1, .500, 2, 200 –500, and 3, ,200 CD4/mL were used for

stratification of baseline CD4 values (Fig. 4A), the proportion survival (95% CI) was 1, 1, and 0.74 (0.64 – 0.85) at 12 months; and 1, 1, and 0.55 (0.39 – 0.78) at 24 months, respectively (log rank x2 47.0). When the .500 cells/mL group was taken as the control, the x2 value dropped to 0.002 (P 5 0.97). Although the 200 CD4 cells/mL level cut off a distinctively separate group, the 500 cells/mL level did not appear to be useful prognostically in our study population within our period of follow-up. When the proposed values of .220, 100 –220, ,100 CD4 cells/mL were used (Fig. 4B), the estimated proportion survival was 1, 0.94 (0.85–1.0), and 0.63 (0.48 – 0.78) at 12 months; and 1, 0.85 (0.63–1.0), 0.37 (0.11– 0.63) at 24 months, respectively (log rank x2 63.6). When the .220 cells/mL group was taken as the control, the x2 was 12.1 (P 5 0.0005). For the purpose of comparison, we also used the CDC % lym criteria of ,14, 14 –28, .28% to stratify baseline CD4 (Fig. 4C) and calculate the estimated proportion survival; the corresponding values were 1, 0.99 (0.96 – 1.0), and 0.75 (0.64 – 0.86) at 12 months; and 1, 0.97 (0.88 –1.0), and 0.54 (0.28 – 0.80) at 24 months, respectively (log rank x2 31.5). From our data, the 28% lym level was too high to be of use prognostically in our population. On the other hand, the 14% lym level contributed to the overall significance. When the .28% lym group of patients was taken as control, the x2 was 6.3 (P 5 0.01). The CD41 T-cell level of 28% lym did not appear to be useful as a prognostic criterion in our study population. When the proposed values of .12%, 6 –12%, ,6% CD4 cells were used (Fig. 4D), the estimated proportion survival was 0.98 (0.98 – 0.99), 0.86 (0.85– 0.87), and 0.64 (0.61– 0.66) at 12 months; and 0.97 (0.90 –1.0), 0.73 (0.42–1.0), and 0.31 (0.014 – 0.62) at 24 months, respectively (log rank x2 55.9). When the .12% lym group of patients was taken as control, the x2 was 39.3 (P ,0.0001). Comparison of Death Incidences in CDC and Proposed Criteria for Stratification Table 2 shows the results of the comparison of death incidences when the statistical method detailed in 2b above was used. The person-years of observations, the denominators, for CDC stages 1, .500, 2, 200 –500, and 3, ,200 were 48.4, 30.4, 122.9 years, respectively, while the corresponding values for proposed staging 1, .220, 2, 100 –220, and 3, ,100 were 74.3, 93.1, and 34.2 years, respectively. This comparison of death incidences confirmed the above findings that the .500 category for stratification was not helpful in representing death incidences in our HIV population.

CD4 FOR STAGING HIV1 CHINESE

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FIG. 4. Kaplan-Meier curves for proportion survival of HIV1 Chinese adults stratified by baseline CD41 T-cell as absolute counts (/mL) (A and B) according to CDC (A) and proposed (B) staging criteria, and as percentage lymphocytes (C and D) according to CDC (C) and proposed (D) staging criteria. Numbers of patients at risk at 200, 400, and 600 days for (A) ,200 CD4/mL are 74, 44, 23; 200 –500 CD4/mL: 61, 41, 23; .500 CD4/mL: 25, 16, and 11, respectively. For (B) ,100 CD4/mL: 46, 26, 11; 100 –220 CD4/mL: 34, 25, 17; .220 CD4/mL: 109, 77, and 49, respectively. For (C) ,14% lym: 74, 46, 22; 14 –28% lym: 88, 60, 42; .28% lym: 23, 16 and 11, respectively. For (D) ,6% lym: 35, 18, 8; 6 –12% lym: 34, 22, 11; .12% lym: 118, 85, and 58, respectively.

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KAM ET AL.

TABLE 2 Comparison of Death Incidences in Proposed and CDC Criteria for Stratification of Baseline CD4 Values in HIVInfected Chinese Adults Proposed

Deaths (/year)

CDC

Deaths (/year)

Baseline CD4 absolute counts (/mL) ,100 100–220 .220

0.578 0.099 0.008

,200 200–500 .500

0.403 0.011 0.000

Baseline CD4 as % lymphocytes ,6 6–12 .12

0.552 0.182 0.023

,14 14–28 .28

0.390 0.021 0.000

Estimated Potential Impact of Proposed Criteria on Initiation of ART and PCPP In view of the increasing reliance by clinicians on peripheral CD4 values to initiate ART and PCPP, we performed a preliminary estimation of the potential impact of our proposed criteria on present clinical practices which are based on CDC guidelines. Based on the CDC criteria of CD4 ,500 cells/mL, 67.9, 92.0, and 100% of patients in clinical stage A, B, and C, respectively, would have been started on ART, while only 21.4, 58.0, 95.9% of our patients had baseline CD4 ,220/mL and therefore would be started on ART when using our proposed criteria. As expected, the largest difference (46.5%) would be seen in stage A patients, although the actual amount of drugs used would be larger as these patients do live longer than those in stages B and C. When baseline CD4 values expressed as % lym were used, 78.6, 100, and 100% in stages A, B, and C, respectively, would be started on ART based on CDC criteria, while only 15.7, 52, and 89.6% in the respective stages would be initiated when using proposed criteria. Therefore, a 62.9% reduction in use of initial ART for stage A may be expected. PCPP, which is currently recommended by CDC to be started at CD4 ,200/mL, would be initiated for 19.3, 54.0, and 91.7% of stage A, B, and C patients, respectively. If our proposed criterion of ,100 CD4 cells/mL were used, only 5.7, 40.0, and 79.2% of patients would need be started on PCPP. This means a 13.6, 14.0, and 12.5% difference between CDC criteria and ours for stages A, B, and C patients, respectively, when estimated by baseline CD4 values alone. DISCUSSION

Our present study population consisted of HIV-infected patients who voluntarily attended the two HIV

clinics in Hong Kong, who were of Chinese ethnicity, and who lived in an urban environment with reasonable access to modern Western medical care and counseling services. This study represents longitudinal data from the follow-up of HIV-infected Chinese adults whose CD4 cells were estimated by a standardized, quality-controlled flow cytometric procedure. Comparable longitudinal data among the Caucasian population in developed countries (24–26) showed some notable differences. While the mean CD4 level before infection was much higher in the Caucasian than the Chinese patients, the almost one-third drop of peripheral CD4 cells from time of infection to immediately before seroconversion was comparable. However, the subsequent rate of decline (42 CD4/mL per 6 months) in the AIDS-free prevalent seropositive Caucasian was comparable only to our stage A Chinese patients (47 CD4 cells per 6 months). Thereafter, our patients appeared to decline at a much slower rate (stage B: 31 CD4 cells per months) and especially so after the diagnosis of AIDS (stage C: 11 CD4 cells per 6 months). Because the exact dates of infection were unknown for most of our patients, the possibility of HIV-1 infection months to years before the appearance of a positive test result and therefore before their CD4 cells were measured, though unlikely, could not be entirely excluded. Biases in prevalent cohorts have been previously described and investigated (27) for estimation of both the cumulative distribution function and the hazard ratio for proportional hazard models with both fixed and time-dependent covariates. A number of solutions for handling these problems have been proposed (28) and generally require a seroincident cohort. There are, however, several other potential sources of systematic error in this study. First, participant bias may be present, as cohort members were those who voluntarily turned up at our two clinics. Overestimation of the risk of clinical disease and mortality may have resulted from disproportionate participation from members who had symptoms and desired medical evaluation and interventions. Second, risk of disease and mortality may have been underestimated as a result of nonparticipation due to HIV-related disease or death. As HIV disease is, at present, still a socially stigmatized disease locally, it is possible that a number of very sick persons may have refrained from seeking medical treatment at any time of their disease course. We do not have any accurate estimations on how significantly this factor may have affected our results, except that our unlinked anonymous testing program showed our present estimated endemic level of HIV infection to be very low (,0.1%) in our local Chinese population in Hong Kong (29). Third, other biological and behavioral factors have been associated with immunological deterioration or increased risk of clinical disease including age (30),

CD4 FOR STAGING HIV1 CHINESE

biological properties of virus variants (31) and host genetic factors (32–34), while smoking has not been shown to be associated with progression to AIDS or low CD41 lymphocyte counts (35). At present, we are uncertain whether there are fundamental differences in the pathogenesis of HIV infection in the Chinese population. Also, previous studies have documented that appropriate ART and PCPP may bring about improvements in short-term survival (36 – 40), especially when comparing cohorts of HIV patients who were followed-up longitudinally (41). The nonethnic Chinese patients who attended our clinics could provide a valuable comparison to elucidate possible host and environmental factors. However, their small numbers have precluded their inclusion for a valid comparison. Because our study represents the earliest possible time when standardized flow cytometry laboratory procedures for CD4 testings were available locally, we were unable to compare our results with any previous data which may show changes in patterns of survival in our HIV-infected population over time. Although we found an apparent slower rate of decline of CD4 cells among our patients who received AZT, this did not appear to translate into statistically significant improved survival for the duration of our study. It is known from results of clinical trials that AZT suppresses CD41 cell loss in some subjects, but the CD41 cell-sparing effect has not been demonstrated beyond 24 weeks (8, 42). Other studies have addressed the use of AZT in some minority populations in developed countries (43, 44). However, the recent introduction of treatment regimens which include powerful protease inhibitors has been shown to significantly affect the survival of HIV patients. It would be of interest to study how these therapeutic regimens will affect the survival in our population. Although our longitudinal data may not be sufficiently long enough compared with other larger scale studies (45, 46), our present observations and analyses are based on important evidence, viz, baseline CD4 measurements and time to death, in comparing the two different stratification criteria (CDC and ours). For our study population, our proposed CD4 criteria for stratifying baseline CD4 gave better discrimination and more predictive power than the CDC CD4 criteria. We have shown that the CD4 levels in our HIV-infected Chinese population were sufficiently different from that of the Caucasian so that the present CDC criteria would need to be adapted, if CD4 measurements were to remain optimally useful as a surrogate marker in our HIV patients. We used time to death as our end point in this study. It should be mentioned that time to development of AIDS is a feasible alternative which can shorten the period of observation and thus the follow-up period required for completion. However, there may be inher-

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ent biases in the diagnosis of AIDS which are not easy to overcome. Extension of our study period to increase the sample size and number of observations may serve to further enhance the significance of our present observations. In particular, our findings would require confirmation with a much larger sample size in other Asian populations with a higher HIV incidence, such as Thailand. A study in the United States of HIV patients who received intensive and long-term AZT treatment as well as PCPP regimens showed that those whose CD4 fell to less than 50/mL had a median survival of 12.1 months (47). For our HIV-infected Chinese population, the estimated proportion survival for those with the same baseline CD4 (,50/mL) was 0.61 at 12 months (95%CI 0.41– 0.80). Only when baseline CD4 reached the level of less than 30/mL did the estimated proportion survival of 0.42 at 12 months (95%CI 0.18–0.66) become comparable to that of the HIV-infected Caucasian. A smaller scale study of HIV patients in Thailand, using a manual indirect immunofluorescence method of CD4 measurement, did not show significant differences between their CD4 values and the values for Caucasians (48). However, a study involving Ugandans in Africa, also using flow cytometric techniques, showed lower CD4 reference ranges in healthy adults (49). More recently, the question has also been raised by us as well as by researchers in Africa on the applicability of CD41 count standards which are based on European experience (50, 51). It is noted that the staging cut-off of 250, instead of 220, may be chosen because that would make our values exactly half the CDC criteria (i.e., 1/2 of 500 5 250; 1/2 of 200 5 100) and therefore easier for comparisons in future studies. Also the staging cut-off of 200 may be used because round numbers may be easier to remember. After much deliberation with statistical analysis, we chose 220 because that gives the best separation based on our present data set. We do not preclude the possibility of future modifications of our proposed criteria as new data come in, considering the limitations of our study in terms of population size and length of observation. In view of the considerable variations which may result from CD4 measurements (52), it cannot be overemphasized that properly standardized, qualitycontrolled flow cytometric procedures must be strictly followed if CD4 estimations are to be of any use (53, 54). Physician experience (55) has also been studied as an important factor in patients’ survival. While all of these factors may play a definite role in affecting our results, we think that host genetic factors may be the most likely explanation for the differences in estimated proportion survival in our HIV-infected Chinese patients compared with HIV-infected Caucasian patients. It would be interesting to investigate the differ-

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ent viral phenotypes as well as host immune responses in the HIV-infected Chinese adult (56, 57). In particular, the high NK cell levels may be important in the evolution of immunological events in our HIV-infected population. It has been known that once HIV infection occurs there is evidence for progressive depletion of NK cells (CD32 CD81CD161) (58) and that NK cells can also be infected with HIV-1 in vitro (59). Recently, NK cells have also been shown to play a role in polarizing the immune response toward Th1 type immunity (60). Although we estimated the potential impact of our proposed criteria on initiation of ART and PCPP, it should be stated that outcome with antiretroviral therapy and with prophylactic antibiotics will clearly require separate analyses and separate studies. Future studies on our patient population are warranted using therapeutic management in various staging groups. Therefore, the present survival staging should be restricted to staging of patients at diagnosis and must not be used for treatment guidelines. Recently, plasma viral load measurements have been shown to be an important surrogate marker of HIV infection (61– 63). Current recommendations on use of therapeutic combinations are also dependent on both these markers. Our present study did not address this issue but it would be pertinent for future studies of HIV disease in our Chinese population to look into how these drug combination therapeutic regimens, including protease inhibitors, will be guided by these important markers of HIV disease. ACKNOWLEDGMENTS The authors thank the following for their support of this study: the nursing staff in the AIDS Unit in Yaumati Polyclinic, and the Special Medical Service of Queen Elizabeth Hospital, for their expert nursing care of our patients; the technical staff in the Haematology, Serology, and Immunocytometry Laboratory in Sai Ying Pun Polyclinic for excellent immunophenotyping work; and Dr. W. L. Lim and her staff in the Virus Unit for the HIV-1 and HIV-2 ELISA testing and Western blot confirmation. We are grateful to the Director of Health, Dr. Margaret Chan, for permission to publish this report. REFERENCES 1. Barre-Sinoussi, F., Chermann, J. C., and Rey, F., Isolation of a T-lymphotropic retrovirus from a patient at risk for acquired immunodeficiency syndrome (AIDS). Science 220, 868 – 871, 1983. 2. Gallo, R. C., Salahuddin, S. Z., Popovic, M., et al. Frequent detection and isolation of cytopathic retroviruses (HTLV-III) from patients with AIDS and at risk for AIDS. Science 224, 500 –503, 1984. 3. Moss, A. R., and Bacchetti, P., Natural history of HIV infection. AIDS 3, 55– 61, 1989. 4. Centers for Disease Control and Prevention, 1993 revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR 41(No.RR-17), 1–19, 1992.

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