|
Advertisement |
|
|
||
 |
|
|||||
|
|||||
|
 |
||||||
|
||||||
|
||||||
|
Originally published as JCO Early Release 10.1200/JCO.2007.10.7219 on April 30 2007 © 2007 American Society of Clinical Oncology. Prognostic Significance of Immune Subset Measurement in Individuals With AIDS-Associated Kaposi's Sarcoma
From the Imperial College of Science, Medicine, and Technology, Departments of Oncology and HIV Medicine, The Chelsea and Westminster Hospital, London, United Kingdom Address reprint requests to Justin Stebbing, MA, MRCP, MRCPath, PhD, Imperial College of Science, Medicine, and Technology, Charing Cross Hospital, Department of Oncology, First Floor, East Wing, Fulham Palace Rd, London W6 8RF, United Kingdom; e-mail: j.stebbing{at}imperial.ac.uk
Purpose: A prognostic index for AIDS-associated Kaposi's sarcoma (KS) diagnosed in the era of highly active antiretroviral therapy (HAART) was based on routine clinical and laboratory characteristics. Because immune subset measurement is often performed in HIV-positive individuals, we examined whether these were predictive of mortality independently of the prognostic index, or could predict time to progression of KS. Patients and Methods: We performed univariate and multivariate Cox regression analyses on a data set of 326 individuals with AIDS-associated KS to identify immune subset covariates predictive of overall survival and time to progression. Adaptive (CD8 T cell and CD19 B cell) and innate (CD16/56 natural-killer cell) immune parameters were studied by flow cytometry. Results: In univariate analyses, all three immune subsets had significant effects on overall survival (P < .025). In multivariate analyses including the prognostic index, only CD8 counts remained significant (P = .026), although its effect on the overall prognostic index is small. An increase of 100 cells/mm3 in the CD8 count confers a 5% improvement in overall survival. Individuals with a higher CD8 count did not have an increased time to progression. Patients who were already on HAART at the time of KS diagnosis did not have a shorter time to progression than those who were antiretroviral naïve at KS diagnosis. Conclusion: The CD8 count appears to provide independent prognostic information in individuals with AIDS-associated KS. Measurement of the CD8 count is clinically useful in patients with KS.
In persons with HIV/AIDS, the use of highly active antiretroviral therapy (HAART) has reduced the incidence of opportunistic infections1,2 and decreased the incidence of HIV-associated cancers.3-5 The association between Kaposi's sarcoma (KS) and HIV was made at the onset of the epidemic6 and it remains the most common HIV-associated malignancy.7 A recently published8 prognostic index for AIDS-associated KS demonstrated that having KS as the AIDS-defining illness (–3 points) and increasing CD4 count (–1 for each complete 100 cells/mm3 in counts at KS diagnosis) improved prognosis, whereas age at KS  50 years old (+2) and having another AIDS-associated illness at the same time (+3) conveyed a poorer prognosis. Individuals with a prognostic score of 0, 10, and 15 (scoring started at 10) had 5-year survival rates of 98.4%, 63.1% and 8.4%, and increasing the prognostic score by 1 increased the 1-year death hazard ratio (HR) by 40% (95% CI, 28% to 53%; bootstrapped HR, 1.39; 95% CI, 1.25 to 1.51). The formulation of this index, including its external validation, was based on routinely measured clinical and laboratory variables (HIV viral load and CD4 count) to ensure utility in the developing world. However, in multivariate analyses, we have previously demonstrated that decreases in adaptive immune parameters (T- and B-cell counts),9 but not innate ones (natural-killer counts),10 predispose individuals to KS and similarly increases confer protection. Such variables are routinely measured in established market economies, although the clinical consequences of their measurement are not established, despite the fact that it is well-known that immune parameters, such as CD8 positive cytotoxic T lymphocytes (CTLs), control both HIV11-13 and to a lesser extent Kaposi's sarcoma-associated herpes virus (KSHV) replication.14,15 To study the role of immune-related prognostic factors in persons with HIV/AIDS with established KS, we investigated the role of routinely measured immune subset parameters in individuals diagnosed in the HAART era with AIDS-associated KS, including the effect on time to progression as well as overall survival.
We identified all persons with HIV/AIDS who were observed at the Chelsea and Westminster Hospital, one of the largest HIV cohorts in Europe, since routine prospective data collection commenced in 1983. We defined HAART as therapy consisting of at least three antiretroviral drugs in accordance with American and European published guidelines (dual nucleoside analogs alone are not considered HAART)16-18 and we focused on cohort members who continued to receive follow-up since January 1, 1996, when HAART became routinely available at our institution as well as many others. Appropriate ethical approval was given. Total lymphocyte and subset analysis was performed using whole blood stained with murine antihuman monoclonal antibodies to CD4 (T-helper cells), CD8 (a cytotoxic T-cell marker), CD19 (B cells), and CD16/56 (natural-killer cells; TetraOne; Beckman Coulter, High Wycombe, United Kingdom) and were evaluated on an Epics XL-MCL (Beckman Coulter) multiparametric four-color flow cytometer. Immune subset cell counts were measured at varying times after diagnosis for each patient and the data were assembled in two forms: one listing the covariates at the time of KS diagnosis; and a second prepared in a counting process format,19,20 which incorporated HAART status using a time-dependent covariate and time to progression as a covariate synthesized from the existing measurements (data were prepared using a Perl script and analyzed using the R-computer language21,22). Curves for overall duration of survival were plotted by the Kaplan-Meier approach.23 The log-rank method was used to test for the significance of differences in survival distributions.24 Univariate Cox regression of CD8, CD16/56, and CD19 cell counts was performed. Multivariate Cox proportional hazards regression was carried out on the covariates of interest: CD8, CD16/56, and CD19 cell counts, together with the prognostic index. The final multivariate model included the prognostic index and CD8. Time to progression was defined as the time from KS diagnosis to death or new therapy for progressive KS, whichever was sooner. Curves for overall time to progression were plotted by the Kaplan-Meier approach.23 The log-rank method was used to test for the significance of differences in times to progression. Univariate Cox regressions of CD8 cell count and HAART were carried out.
From the previously published studies of 5,873 patients observed in the HAART era, a total of 326 (5.5%) individuals with AIDS-associated KS were identified.8 Figure 1 demonstrates the changes in the probability of survival over time for high and low CD8 cytotoxic T-cell counts, CD16/56 natural-killer, and CD19 B-cell counts. For CD16/56 and CD19 counts, the 95% CIs between high and low counts overlap widely, although the cut offs are chosen for graphical illustration only and analyses were performed on continuous variables.
Table 1 demonstrates that for all three immune subsets examined herein—CD8, CD16/56, and CD19—the univariate P values exhibit statistical significance for an effect on survival. However, for the CD16/56 and CD19 counts, their coefficients are close to 1, so their effect is not clinically significant. For both of these parameters an increase of 100 cells/mm3 led to a 1% decrease in overall survival. Higher CD8 counts have a positive influence on survival such that in a univariate analysis a 7% improvement in survival was observed per 100 cells/mm3 increase in CD8 count.
In addition, when multivariate analyses are performed on these immune subsets, CD16/56 and CD19 counts are no longer significant (Table 2). The previous index remains highly statistically significant, and CD8 counts are also significant with a P value of .024. When CD16/56 and CD19 counts are removed and a Cox regression is performed on the prognostic index and CD8 counts, an increase of 100 cells/mm3 confers a 5% increase in survival (P = .026; Table 3). Inclusion of the new covariates has no significant effect on the P value for the prognostic index or the magnitude of its effect on survival.8
As well as examining the data set and prognostic index for overall survival, we also investigated the effect on time to progression of CD8 counts (Fig 2), and being treated with or without HAART at the time of KS diagnosis (Fig 3). The overall time to progression for the entire cohort is shown in Figure 2A, and Figure 2B demonstrates the time to progression for high and low CD8 counts. Figure 3 demonstrates the time to progression for patients with or without HAART. Neither the measured CD8 count nor the effect of HAART on time to progression were statistically significant (Table 4), although both approached significance.
The objective of this prospective cohort study was to examine whether any of the routinely measured adaptive (CD8 and CD19) and innate (CD16/56) immune parameters provided significant prognostic information in persons with HIV/AIDS diagnosed with KS. We found evidence that CD8 counts may provide prognostic information over and above the existing prognostic index, with each increase in 100 cells/mm3 translating to a 5% increase in overall survival (P = .026). The magnitude of the observed effect was not sufficient for it to merit inclusion in the previous prognostic index.8 It would require an improvement in the CD8 count of more than 1,000 cells/mm3 to justify lowering the prognostic index score by a single point (improving the prognosis). However, this analysis does suggest that CD8 counts should continue to be measured and further analysis undertaken when more data is available, to determine definitively whether it has an effect sufficient to merit inclusion in the prognostic index. While CD4 count is known to be prognostic for survival in HIV infection2,25-28 and cancers in immunocompromised patients, including non-Hodgkin's lymphoma as well as KS,8,29,30 the role of immune subsets is less clear. The strongest evidence has always existed for CD8-positive CTLs in controlling both HIV and KSHV replication, the latter being the causative agent of KS.31 The importance of CTLs in controlling HIV replication is supported by models of CD8-depleted animals with AIDS in which decreased numbers of CTLs result in high viral loads13 and by the frequent selection of HIV or simian immunodeficiency virus mutants in vivo that are no longer recognized by CTLs and therefore escape immune surveillance.11,12,32,33 HIV may have a direct effect on KS development: high HIV viral loads may promote KS growth via an increase in levels of HIV-1 transactivating protein34or transactivating-induced angiogenic cytokine release.35 CTLs can themselves appear to control KSHV infection and a number of class I restricted epitopes have been found14,15,36-40 along with the presence of specific anti-KSHV CTLs.41,42 However, accompanying data for an effect of CTLs or even HAART itself on KSHV viral load are less convincing. Some studies have suggested that KSHV viral load is associated with disease progression.43,44 although other work has not supported these findings.45,46
While our measurement of CD8-positive T cells was crude and did not measure degree of activation or specificity, levels of serum interferon- AIDS-associated KS is a disease of immunosuppression,4 so our finding that higher T-cell CD8 counts (and CD4 counts) are associated with better prognosis is unsurprising. However, we did not find that higher CD8 counts or treatment with HAART at the time of KS diagnosis were associated with a significantly decreased time to progression (Figs 2 and 3), demonstrating that once the tumor is established, neither HAART nor CD8 cells are able to mediate effective local control of the disease. They may mediate an improvement in survival via HIV-related as opposed to cancer-related factors, and the treatment with HAART category includes people who are on treatment and undetectable and people who are on therapy but with detectable viremia. It appears likely that the improved prognosis observed with increased CD8 counts is a reflection of improved protection not only from KS-induced death, including death due to KS treatments, but also due to other causes including opportunistic infections. The time to progression HR for receiving HAART was 0.693 (95% CI, 0.464 to 1.04). This finding that there was no difference in time to disease progression between patients who developed KS while on HAART and those who were antiretroviral naïve may reflect the good salvage antiretroviral options available as most persons with HIV/AIDS who developed KS while receiving HAART had virologic evidence of resistance. However, the 30% improvement in time to progression on HAART did approach statistical significance and may reflect a sample size issue. Persons with HIV/AIDS are living longer, and AIDS-associated KS remains a significant cause of morbidity, mortality, and a significant marker of advanced immunosuppression as shown by the preponderance of HIV-related factors, including CD8-positive T cells in the index. The clinical and routine role of immune subset measurement (other than CD4 count) in persons with HIV/AIDS has been unclear. These data demonstrate that the use of the CD8 count in patients with KS is clinically useful.
The authors indicated no potential conflicts of interest.
Conception and design: Justin Stebbing, Alastair Teague Financial support: Justin Stebbing, Mark Nelson Administrative support: Justin Stebbing, Adam Sanitt, Mark Nelson, Brian Gazzard, Mark Bower Provision of study materials or patients: Justin Stebbing, Alastair Teague, Tom Powles, Mark Nelson, Brian Gazzard, Mark Bower Collection and assembly of data: Justin Stebbing, Adam Sanitt, Alastair Teague, Tom Powles, Mark Nelson, Brian Gazzard, Mark Bower Data analysis and interpretation: Justin Stebbing, Adam Sanitt, Tom Powles Manuscript writing: Justin Stebbing, Adam Sanitt, Tom Powles, Mark Bower Final approval of manuscript: Justin Stebbing, Adam Sanitt
published online ahead of print at www.jco.org on April 30, 2007 Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.
1. Palella FJ Jr, Delaney KM, Moorman AC, et al: Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection: HIV Outpatient Study Investigators. N Engl J Med 338:853-860, 1998 2. Sterne JA, Hernan MA, Ledergerber B, et al: Long-term effectiveness of potent antiretroviral therapy in preventing AIDS and death: A prospective cohort study. Lancet 366:378-384, 2005[CrossRef][Medline] 3. International Collaboration on HIV and Cancer: Highly active antiretroviral therapy and incidence of cancer in human immunodeficiency virus-infected adults. J Natl Cancer Inst 92:1823-1830, 2000 4. Portsmouth S, Stebbing J, Gill J, et al: A comparison of regimens based on non-nucleoside reverse transcriptase inhibitors or protease inhibitors in preventing Kaposi's sarcoma. Aids 17:F17-F22, 2003[CrossRef][Medline] 5. Stebbing J, Gazzard B, Mandalia S, et al: Antiretroviral treatment regimens and immune parameters in the prevention of systemic AIDS-related non-Hodgkin's lymphoma. J Clin Oncol 22:2177-2183, 2004 6. Friedman-Kien AE, Laubenstein LJ, Rubinstein P, et al: Disseminated Kaposi's sarcoma in homosexual men. Ann Intern Med 96:693-700, 1982[CrossRef][Medline] 7. Clifford GM, Polesel J, Rickenbach M, et al: Cancer risk in the Swiss HIV cohort study: Associations with immunodeficiency, smoking, and highly active antiretroviral therapy. J Natl Cancer Inst 97:425-432, 2005 8. Stebbing J, Sanitt A, Nelson M, et al: A prognostic index for AIDS-associated Kaposi's sarcoma in the era of highly active antiretroviral therapy. Lancet 367:1495-1502, 2006[CrossRef][Medline] 9. Stebbing J, Gazzard B, Newsom-Davis T, et al: Nadir B cell counts are significantly correlated with the risk of Kaposi's sarcoma. Int J Cancer 108:473-474, 2004[CrossRef][Medline] 10. Stebbing J, Gazzard B, Flore O, et al: Natural killer cells are not infected by Kaposi's sarcoma-associated herpesvirus in vivo, and natural killer cell counts do not correlate with the risk of developing Kaposi's sarcoma. Aids 17:1998-2000, 2003[Medline] 11. Phillips RE, Rowland-Jones S, Nixon DF, et al: Human immunodeficiency virus genetic variation that can escape cytotoxic T cell recognition. Nature 354:453-459, 1991[CrossRef][Medline] 12. Evans DT, O'Connor DH, Jing P, et al: Virus-specific cytotoxic T-lymphocyte responses select for amino-acid variation in simian immunodeficiency virus Env and Nef. Nat Med 5:1270-1276, 1999[CrossRef][Medline] 13. Schmitz JE, Kuroda MJ, Santra S, et al: Control of viremia in simian immunodeficiency virus infection by CD8+ lymphocytes. Science 283:857-860, 1999 14. Wang QJ, Jenkins FJ, Jacobson LP, et al: Primary human herpesvirus 8 infection generates a broadly specific CD8(+) T-cell response to viral lytic cycle proteins. Blood 97:2366-2373, 2001 15. Wang QJ, Jenkins FJ, Jacobson LP, et al: CD8+ cytotoxic T lymphocyte responses to lytic proteins of human herpes virus 8 in human immunodeficiency virus type 1-infected and -uninfected individuals. J Infect Dis 182:928-932, 2000[CrossRef][Medline] 16. Gazzard B, Bernard AJ, Boffito M, et al: British HIV Association (BHIVA) guidelines for the treatment of HIV-infected adults with antiretroviral therapy (2006). HIV Med 7:487-503, 2006[CrossRef][Medline] 17. Gazzard B: British HIV Association (BHIVA) guidelines for the treatment of HIV-infected adults with antiretroviral therapy (2005). HIV Med 2:1-61, 2005 (suppl 6)[CrossRef] 18. Hammer SM, Saag MS, Schechter M, et al: Treatment for adult HIV infection: 2006 recommendations of the International AIDS Society-USA panel. JAMA 296:827-843, 2006 19. Andersen P, Gill R: Cox's regression model for counting processes, a large sample study. Annals of Statistics 10:1100-1120, 1982 20. Gill R: Understanding Cox's regression model. Experientia 41:187-199, 1982 (suppl)[CrossRef] 21. Venables W, Ripley B: Modern applied statistics with S-PLUS (ed 3rd). New York, NY, Springer, 1999 22. Fleming TR, Lin DY: Survival analysis in clinical trials: Past developments and future directions. Biometrics 56:971-983, 2000[CrossRef][Medline] 23. Kaplan E, Meier P: Nonparametric estimation from incomplete observations. J Am Stat Assoc 53:457-481, 1958[CrossRef] 24. Cox D: Regression models and life tables. J Royal Stat Soc 34:187-220, 1972 25. Mocroft AJ, Johnson MA, Sabin CA, et al: Staging system for clinical AIDS patients: Royal Free/Chelsea and Westminster Hospitals Collaborative Group. Lancet 346:12-17, 1995[CrossRef][Medline] 26. Turner BJ, Markson L, Taroni F: Estimation of survival after AIDS diagnosis: CD4 T lymphocyte count versus clinical severity. J Clin Epidemiol 49:59-65, 1996[CrossRef][Medline] 27. Pedersen C, Katzenstein T, Nielsen C, et al: Prognostic value of serum HIV-RNA levels at virologic steady state after seroconversion: Relation to CD4 cell count and clinical course of primary infection. J Acquir Immune Defic Syndr Hum Retrovirol 16:93-99, 1997[Medline] 28. Kassa E, Rinke de Wit TF, Hailu E, et al: Evaluation of the World Health Organization staging system for HIV infection and disease in Ethiopia: Association between clinical stages and laboratory markers. Aids 13:381-389, 1999[CrossRef][Medline] 29. Bower M, Gazzard B, Mandalia S, et al: A prognostic index for systemic AIDS-related non-Hodgkin lymphoma treated in the era of highly active antiretroviral therapy. Ann Intern Med 143:265-273, 2005 30. Mounier N, Spina M, Gabarre J, et al: AIDS-related non-Hodgkin lymphoma: Final analysis of 485 patients treated with risk-adapted intensive chemotherapy. Blood 107:3832-3840, 2006 31. Chang Y, Cesarman E, Pessin MS, et al: Identification of herpesvirus-like DNA sequences in AIDS-associated Kaposi's sarcoma. Science 266:1865-1869, 1994 32. Leslie A, Kavanagh D, Honeyborne I, et al: Transmission and accumulation of CTL escape variants drive negative associations between HIV polymorphisms and HLA. J Exp Med 201:891-902, 2005 33. Friedrich TC, Dodds EJ, Yant LJ, et al: Reversion of CTL escape-variant immunodeficiency viruses in vivo. Nat Med 10:275-281, 2004[CrossRef][Medline] 34. Ensoli B, Barillari G, Salahuddin SZ, et al: Tat protein of HIV-1 stimulates growth of cells derived from Kaposi's sarcoma lesions of AIDS patients. Nature 345:84-86, 1990[CrossRef][Medline] 35. Mariotti M, Castiglioni S, Maier JA: Expression analysis and modulation by HIV-Tat of the tyrosine phosphatase HD-PTP. J Cell Biochem 98:301-308, 2006[CrossRef][Medline] 36. Brander C, O'Connor P, Suscovich T, et al: Definition of an optimal cytotoxic T lymphocyte epitope in the latently expressed Kaposi's sarcoma-associated herpesvirus kaposin protein. J Infect Dis 184:119-126, 2001[CrossRef][Medline] 37. Micheletti F, Monini P, Fortini C, et al: Identification of cytotoxic T lymphocyte epitopes of human herpesvirus 8. Immunology 106:395-403, 2002[CrossRef][Medline] 38. Stebbing J, Bourboulia D, Johnson M, et al: Kaposi's sarcoma-associated herpesvirus cytotoxic T lymphocytes recognize and target Darwinian positively selected autologous K1 epitopes. J Virol 77:4306-4314, 2003 39. Wang QJ, Huang XL, Rappocciolo G, et al: Identification of an HLA A*0201-restricted CD8(+) T-cell epitope for the glycoprotein B homolog of human herpesvirus 8. Blood 99:3360-3366, 2002 40. Wilkinson J, Cope A, Gill J, et al: Identification of Kaposi's sarcoma-associated herpesvirus (KSHV)-specific cytotoxic T-lymphocyte epitopes and evaluation of reconstitution of KSHV-specific responses in human immunodeficiency virus type 1-Infected patients receiving highly active antiretroviral therapy. J Virol 76:2634-2640, 2002 41. Stebbing J, Gazzard B, Portsmouth S, et al: Disease-associated dendritic cells respond to disease-specific antigens through the common heat shock protein receptor. Blood 102:1806-1814, 2003 42. Stebbing J, Gazzard B, Patterson S, et al: Antibody-targeted MHC complex-directed expansion of HIV-1- and KSHV-specific CD8+ lymphocytes: A new approach to therapeutic vaccination. Blood 103:1791-1795, 2004 43. Quinlivan EB, Zhang C, Stewart PW, et al: Elevated virus loads of Kaposi's sarcoma-associated human herpesvirus 8 predict Kaposi's sarcoma disease progression, but elevated levels of human immunodeficiency virus type 1 do not. J Infect Dis 185:1736-1744, 2002[CrossRef][Medline] 44. Engels EA, Biggar RJ, Marshall VA, et al: Detection and quantification of Kaposi's sarcoma-associated herpesvirus to predict AIDS-associated Kaposi's sarcoma. Aids 17:1847-1851, 2003[CrossRef][Medline] 45. Marcelin AG, Gorin I, Morand P, et al: Quantification of Kaposi's sarcoma-associated herpesvirus in blood, oral mucosa, and saliva in patients with Kaposi's sarcoma. AIDS Res Hum Retroviruses 20:704-708, 2004[CrossRef][Medline] 46. Bourboulia D, Aldam D, Lagos D, et al: Short- and long-term effects of highly active antiretroviral therapy on Kaposi sarcoma-associated herpesvirus immune responses and viraemia. Aids 18:485-493, 2004[CrossRef][Medline] 47. Pugliese A, Torre D, Saini A, et al: Cytokine detection in HIV-1/HHV-8 co-infected subjects. Cell Biochem Funct 20:191-194, 2002[CrossRef][Medline] 48. Sirianni MC, Vincenzi L, Fiorelli V, et al: Gamma-interferon production in peripheral blood mononuclear cells and tumor infiltrating lymphocytes from Kaposi's sarcoma patients: Correlation with the presence of human herpesvirus-8 in peripheral blood mononuclear cells and lesional macrophages. Blood 91:968-976, 1998 49. Fiorelli V, Gendelman R, Sirianni MC, et al: Gamma-interferon produced by CD8+ T cells infiltrating Kaposi's sarcoma induces spindle cells with angiogenic phenotype and synergy with human immunodeficiency virus-1 Tat protein: An immune response to human herpesvirus-8 infection? Blood 91:956-967, 1998 50. Galon J, Costes A, Sanchez-Cabo F, et al: Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science 313:1960-1964, 2006 51. Moir S, Malaspina A, Ogwaro KM, et al: HIV-1 induces phenotypic and functional perturbations of B cells in chronically infected individuals. Proc Natl Acad Sci U S A 98:10362-10367, 2001 52. Ancuta P, Autissier P, Wurcel A, et al: CD16+ monocyte-derived macrophages activate resting T cells for HIV infection by producing CCR3 and CCR4 ligands. J Immunol 176:5760-5771, 2006 53. Stebbing J, Bower M, Mandalia S, et al: Highly active anti-retroviral therapy (HAART)-induced maintenance of adaptive but not innate immune parameters is associated with protection from HIV-induced mortality. Clin Exp Immunol 145:271-276, 2006[CrossRef][Medline] Submitted January 9, 2007; accepted March 9, 2007.
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|||||||||||
|
|||||||||||
|
|
Copyright © 2007 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
|
TOP
ABSTRACT
INTRODUCTION
in a subset of patients (n = 16) demonstrated no significant correlations with any of the measured immune subsets (data not shown). A previous study in KSHV-HIV coinfection has also failed to show a correlation
