Moore, David M MDCM, MHSc*†‡; Awor, Anna MSc*; Downing, Robert PhD*; Kaplan, Jonathan MD, MPH§; Montaner, Julio S G MD†‡; Hancock, John MSc*; Were, Willy MBChB, MPH*; Mermin, Jonathan MD, MPH*
Treatment guidelines from the World Health Organization (WHO) regarding the use of antiretroviral therapy (ART) in resource-limited settings recommend the use of CD4+ T-lymphocyte (CD4) counts to monitor response to therapy in programs where HIV-1 viral load (VL) testing is not available.1 Consequently, CD4 cell counts have become the most common laboratory method for evaluating eligibility for ART and monitoring response to treatment in such settings. The WHO guidelines recommend a change in drug regimen for individuals on ART who have a return of CD4 cell counts to pretherapy levels or a ≥50% decrease in CD4 cell counts from peak levels, both in the absence of intercurrent infections. The large majority of HIV-infected individuals will achieve virologic suppression in response to ART within the first year of treatment2,3,4; therefore, monitoring ART response is used primarily to identify the minority of persons who fail to achieve an initial response to ART and to detect subsequent treatment failure after an initial response to therapy has occurred.
In high-income countries, treatment failure on ART is primarily defined as the failure to suppress VL or experiencing a VL rebound after initial suppression5,6; immunologic parameters alone are not used to determine the need for drug regimen switches. An analysis from British Columbia, Canada, found that observing no increase in CD4 counts at 6 months had a sensitivity of 0.34 and a positive predictive value (PPV) of 0.75 for predicting failure to achieve 2 successive VL measurements <500 copies per milliliter in the first year on ART.7 Furthermore, the performance of immunologic parameters was even worse when attempting to predict VLs ≥ 50 copies per milliliter. However, the clinical performance of immunologic responses to ART, without concomitant virologic monitoring, in predicting response to therapy has been evaluated in very few resource-limited settings, where adherence rates, virologic suppression rates, and immunologic responses to ART may differ from those in high-income countries.
We designed a study to evaluate the clinical utility of immunologic parameters at 6, 12, and 18 months after ART initiation in identifying patients who fail to achieve or maintain virologic suppression on their primary ART regimen, using data from a home-based ART program in rural Uganda.
The Home-Based AIDS Care Project (HBAC) is a clinical trial of 3 different monitoring strategies for patients receiving ART in Tororo and Busia Districts in eastern Uganda. The study has been described in detail elsewhere.8 In brief, HIV-infected adults recruited from The AIDS Support Organization, Tororo branch, were randomly assigned to (1) quarterly CD4 cell count and VL, with weekly home visits by a trained layperson for clinical monitoring using a standard symptom questionnaire; (2) quarterly CD4 cell count and clinical monitoring with weekly home visits; or (3) clinical monitoring with weekly home visits alone. The primary outcome of the study is the proportion of individuals who experience a new opportunistic infection or death in each monitoring arm at the end of 3 years of follow-up. The studies were approved by the Science and Ethics Committee of the Uganda Virus Research Institute, the Uganda National Council of Science and Technology, and the Institutional Review Boards of the Centers for Disease Control and Prevention and the University of California, San Francisco. A data safety and monitoring board reviews HBAC data at 3-monthly intervals.
All participants aged 18 years and older, who had CD4 cell counts ≤250 cells per microliter or WHO stage III or stage IV disease, excluding isolated pulmonary tuberculosis, were offered lamivudine, stavudine, and nevirapine as the primary ART regimen. If patients were receiving rifampicin-containing tuberculosis treatment at screening, they were initiated on efavirenz-based ART or deferred ART initiation until the rifampicin treatment was completed. Patients were included in analyses if they had both VL and CD4 count available for each time point and had not yet been switched to a regimen containing lopinavir/ritonivir, a drug primarily used for persons who fail the first-line therapy as defined for each of the assigned monitoring arms of the HBAC study. The present analysis includes persons who were enrolled between May 2003 and December 2005.
We collected whole blood specimens from all participants in the HBAC clinic during screening and during home visits at 3-month intervals during follow-up. Blood samples were transported to the Centers for Disease Control and Prevention laboratory in Entebbe where CD4 cell counts, CD4 percentages, and VL were performed on all specimens. CD4 counts were measured by a dual-platform protocol using a FACScan instrument and Tritest reagents (Becton-Dickinson, San Carlos, CA) and VL with the Cobas Amplicor HIV-1 Monitor v1.5 assay (Roche Diagnostics, Laval, Quebec), in normal mode for screening and in ultrasensitive mode during follow-up. Results of CD4 cell count and VL testing were reported back to clinicians as per the arm-specific protocol. Prescribed drug regimens were obtained from pharmacy records, and deaths were recorded during weekly home visits by field officers.
We used aggregated data in this analysis with researchers blinded to participant monitoring arm. We performed descriptive statistics of study persons at baseline and during follow-up. Absolute CD4 cell counts and change in CD4 cell counts from baseline were compared for persons who achieved virologic suppression and those who did not, with and without participants stratified by age, using the Wilcoxon rank sum test. The number of individuals at each time point with no change or declines in CD4 counts from baseline were compared with suppressed and unsuppressed patients using the χ2 test. We plotted these values in 6-monthly intervals to examine trends over time. Preliminary analyses examined 4 potential definitions of virologic failure: VL ≥ 50 copies per milliliter, VL ≥ 500 copies per milliliter, VL ≥ 1000 copies per milliliter, and VL ≥ 5000 copies per milliliter. Subsequent analyses were performed using a single definition of virologic failure of VL ≥ 500 copies per milliliter.
We used receiver operating characteristic curves to evaluate the immunologic criteria for treatment failure proposed by the WHO: (1) no change or declines in CD4 cell count from baseline, or (2) a fall in CD4 cell count of ≥50% from peak levels on ART, in terms of their ability to identify patients with a VL ≥ 500 copies per milliliter at 6, 12, and 18 months after treatment initiation. Other definitions of immunologic responses were examined including absolute CD4 cell count, CD4 percentage, and change in CD4 percentage. Given that CD4 responses may lag behind virologic responses, we also examined CD4 parameters measured 3 months after the VL results. Those CD4 parameters with the largest area under the curve (AUC) were further examined to establish specific thresholds, which maximized the PPV and sensitivity to detect those patients with unsuppressed VLs. These thresholds were rounded off to the nearest 5 cells. Individuals with absolute CD4 cell counts below a particular threshold at 6, 12, or 18 months were defined as treatment failures for analyses using absolute CD4 cell counts. Similarly, participants with values below a particular threshold for change in CD4 cell counts, change in CD4 percentage, and change in CD4 count as a percentage of peak CD4 cell counts or absolute CD4 percentage were defined as treatment failures for these analyses. Individuals identified as failing ART as part of the HBAC study had their drug regimens changed to second line and were excluded from analyses thereafter. Analyses were repeated for months 12 and 18 after excluding persons who failed to achieve virologic suppression within the first 6 months of ART. All analyses were conducted using SAS version 9.1 (SAS Institute, Cary, NC).
A total of 1104 individuals initiated ART during the study period of which 808 (73.2%) were female. Median age was 38 years [interquartile range (IQR) 32-44 years], and the median baseline CD4 cell count was 128 cells per microliter (IQR 65-194 cells/μL). A total of 1026 (96.5%) initiated ART on nevirapine, stavudine, and lamivudine and 37 (3.5%) initiated therapy on efavirenz, stavudine, and lamivudine. Median follow-up time from ART initiation was 1.75 years (IQR 1.65-1.99 years). Ninety-six patients died during follow-up (crude mortality rate = 9.0%) and 57 (60%) within the first 6 months of ART. A total of 25 (2.4%) patients were switched to second-line regimens after having met criteria for clinical, immunologic, or virologic failure, as appropriate to their assigned monitoring arm.
The proportion of patients with virologic failure ranged from 1.5% to 16.4% depending on the definition and the time point (Table 1 and Fig. 1). For each time point, absolute CD4 cell counts and change in CD4 cell counts from baseline were lower for patients with virologic failure, with differences being larger with higher VL thresholds for defining failure. However, not all differences were statistically significant when using a definition of VL > 50 copies per milliliter. Although differences between virologic failure and nonfailure patients were greater when failure was defined as VL ≥ 5000 copies per milliliter, the number of individuals classified as failing treatment with this definition was very small, between 6 and 24 at each interval.
There were no significant differences between the proportions of individuals with “no increase or declines in CD4 counts” from baseline (one of the WHO definitions of treatment failure) when comparing those with and without virologic failure for all periods and for all definitions of failure, except at 12 months after ART initiation (P < 0.05, for all definitions). Preliminary analyses of the sensitivity and PPV of the "no change or decline in CD4 counts" at 6 and 12 months revealed almost identical estimates for all definitions of virologic failure (data not shown). Therefore, subsequent analyses were conducted using only the definition of virologic failure of VL ≥ 500 copies per milliliter. The numbers of individuals with VL ≥ 500 copies per milliliter at 6, 12, 18, and 24 months after ART initiation were 30 (3.1%), 39 (4.2%), 31 (3.4%), and 11 (2.8%), respectively. There were no significant differences in the proportion of individuals with VL suppression when participants were stratified by age > or ≤ the median age (38 years). Similarly, there were no statistically significant differences between CD4 cell count changes from baseline between individuals older than 38 years or 38 years and younger (data not shown).
Using “no increase in CD4 count at 6 months” as a definition of treatment failure had an AUC of 0.65 with a sensitivity of 0.04 [95% confidence interval (CI) 0.00 to 0.10] and a PPV of 0.03 (95% CI 0.00 to 0.09) at 6 months. (Table 2A). Redefining the definition of failure to “CD4 cell count increases of ≤75 cells per microliter at 6 months” marginally improved the PPV (0.06; 95% CI 0.02 to 0.09) and sensitivity (0.27; 95% CI 0.14 to 0.46). The immunologic measure which had the highest AUC (0.71) was an absolute CD4 cell count of 20 cells per microliter at 6 months which had a sensitivity of 0.07 (95% CI 0.01 to 0.22) and a PPV of 0.50 (95% CI 0.07 to 0.93).
To identify persons with VL ≥ 500 copies per milliliter at 12 months, (using no increase or declines in CD4 count from baseline to 12 months) had a sensitivity of 0.08 (95% CI 0.00 to 0.17) and a PPV of 0.16 (95% CI 0.00 to 0.34) (Table 2B). The combination either no increase from baseline or ≥50% decline from peak CD4 cell count had the highest AUC (0.67) for predicting virologic failure at 12 months with a sensitivity of 0.08 (95% CI 0.00 to 0.16) and a PPV of 0.11 (95% CI 0.00 to 0.22). However, the parameter which had the highest PPV and sensitivity was the 15-month absolute CD4 cell count threshold of 80 cells which were 0.11 (95% CI 0.00 to 0.20) and 0.40 (95% CI 0.10 to 0.70), respectively. Absolute CD4 cell count thresholds also had the highest AUC (0.71) for predicting lack of virologic suppression at 18 months (Table 2C). The threshold of 125 cells per microliter at 21 months had a sensitivity of 0.13 (95% CI 0.01 to 0.21) and a PPV of 0.29 (95% CI 0.10 to 0.44). Applying these criteria at 18 months would have resulted in an appropriate switch of ART regimens for 4 of 31 individuals with unsuppressed VL, but an inappropriate treatment switch for an additional 9 persons with VL measurements <500 copies per milliliter. The receiver operating characteristic curves for the best predictors of virologic failure at 6, 12, and 18 months after ART initiation are shown in Figure 2.
The 30 persons who did not achieve virologic suppression at 6 months accounted for approximately 33% of those with unsuppressed VLs at 12 and 18 months (13/39 and 11/31, respectively) and 5 (17%) died before 18 months. Removing these individuals from the analyses at 12 and 18 months did not result in substantial improvements in the predictive value of the immunologic monitoring (data not shown).
This analysis has shown that the use of CD4 cell count monitoring to identify patients who have not achieved virologic suppression on ART can result in substantial misclassification of treatment responses. Of greatest concern is our observation that large numbers of individuals with CD4 cell count declines at 6, 12, and 18 months from treatment initiation had VL < 500 copies per milliliter. If the current WHO guidelines were applied to these patients, they would have been mistakenly identified as failing ART and prematurely switched from their primary ART regimen which was effectively controlling viral replication. Although immunologic responses were different between subjects with VL < 500 copies per milliliter in comparison to those with VL ≥ 500 copies per milliliter at a population level, the variation in immunologic responses within each group is such that they cannot be applied for individual patient management. Of all the parameters examined, the best measure identified was an absolute CD4 cell count <125 cells per microliter at 21 months for predicting VL ≥ 500 copies per milliliter at 18 months, which still only had a sensitivity of 0.13 and a PPV of 0.29. These results suggest that clinicians caring for patients using immunologic monitoring alone should be very cautious in initiating drug regimen changes using these definitions of treatment failure.
The WHO definitions of treatment failure based on CD4 cell count do not seem to correlate well with lack of VL suppression. Other studies from sub-Saharan Africa, similarly, have found small and often statistically insignificant differences in CD4 cell count responses between individuals with suppressed and unsuppressed VL.9-11 However, both immunologic and virologic parameters have been shown to be independently associated with disease progression and death in persons on ART.12,13 Therefore, people with declining CD4 cell counts, even in the presence of virologic suppression, are at increased risk for poor outcomes. However, it is not known whether switching ART regimens in such patients will improve clinical outcomes and doing so will limit their future treatment options.
The WHO treatment failure criteria have been proposed with the goal of identifying individuals who are not responding adequately to treatment. Drug resistance mutations may develop in such individuals if they have partially suppressed VLs.14 In high-income countries, HIV resistance testing is used to guide changes in treatment regimens. It has been argued that this approach is neither practical nor necessary in resource-limited settings because regimen changes usually involve replacement of all 3 drugs in the initial regimen (usually from a nonnucleoside reverse transcriptase inhibitor-based to a protease inhibitor-based regimen), with the expectation that further accumulation of resistance mutations may have limited impact on the success of second-line regimens. The effectiveness and possible negative consequences of this approach have not, however, been studied. The immunologic criteria proposed by WHO will need to be reevaluated, given their poor correlation with virologic suppression. Our study raises the additional concern that immunologic monitoring might actually result in premature switching to second-line therapy, in addition to late switching.
Although CD4 monitoring may not precisely identify persons who are failing therapy, it may have other beneficial roles in monitoring ART patients. First, CD4 counts have prognostic value that is important for counseling patients regarding their short-term risk of opportunistic infections and their need for continuing prophylaxis and for forecasting their health care needs. Second, CD4 counts could be used as a screening test to identify those persons who require VL testing, potentially reducing the demand for VL testing in situations where it is available.9 However, such a strategy requires that VL testing be at least available on a referral basis, something which is currently not possible in most resource-limited settings. Another way in which CD4 counts could be used to identify treatment failure would be if they were combined with clinical parameters such as weight loss or the occurrence of new HIV-related symptoms.15 It is possible that total lymphocyte count and/or hemoglobin concentration could be used for the same purpose,16,17 but these approaches have not been evaluated.
Our analysis has several limitations. First, we had very few participants with unsuppressed VL at each interval, and our rates of virologic suppression were high relative to that reported from other studies.2,18 This was most likely due to the weekly ART delivery and adherence monitoring that participants received under the HBAC protocol which resulted in very high levels of adherence to therapy, between 89% and 97% of participants took ≥95% of their medications in the first year of ART.8 This likely limited the predictive value of any test for failure. As failure rates increase, the PPV value of immunologic parameters would be expected to improve. However, our previous analysis has shown that even where the failure rate is 40% in the first year of therapy, the maximum achievable PPV was only 0.75.7 Furthermore, applying the best sensitivity and specificity obtained from this analysis at 12 and 18 months to a failure prevalence of 30% at each period could only achieve a maximum PPV of 0.64 (data not shown). As well, we only examined changes within a 6- or 9-month period to look for correlation with VL status. It is possible that CD4 changes over longer periods, which correspond to more prolonged periods of inadequate VL suppression, may perform better.
In conclusion, immunologic parameters do not seem to accurately identify individuals receiving ART with unsuppressed VLs or virologic failure. Guidelines for monitoring individuals on ART in resource-limited settings should be adapted to recognize this limitation. Further research is needed to determine whether the addition of clinical parameters can improve the predictive value of CD4 cell count changes and whether longer periods of observation can detect a greater proportion of true treatment failures. As well, further studies are needed to evaluate the optimal monitoring strategies for patients receiving ART in resource-limited settings. In the interim, clinicians should be cautious in initiating therapy changes based solely on CD4 cell count criteria.
The authors would like to thank the field officers, counselors, and clinical staff who care for patients in the HBAC project; the laboratory team at Centers for Disease Control and Prevention-Uganda who conducted the testing; the informatics team at Centers for Disease Control and Prevention-Uganda who compiled the data for analysis; and the participants in the HBAC project. We would also like to acknowledge the support of the Ugandan Ministry of Health and The AIDS Support Organization. D.M.M. had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
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© 2008 Lippincott Williams & Wilkins, Inc.