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Associations of Inflammatory Markers With AIDS and Non-AIDS Clinical Events After Initiation of Antiretroviral Therapy: AIDS Clinical Trials Group A5224s, a Substudy of ACTG A5202

McComsey, Grace A. MD*; Kitch, Douglas MS; Sax, Paul E. MD; Tierney, Camlin PhD; Jahed, Nasreen C. MS§; Melbourne, Kathleen PharmD; Ha, Belinda MD; Brown, Todd T. MD#; Bloom, Anthony MS**; Fedarko, Neal MD††; Daar, Eric S. MD‡‡

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: February 1st, 2014 - Volume 65 - Issue 2 - p 167-174
doi: 10.1097/01.qai.0000437171.00504.41


In the current era of potent antiretroviral therapy (ART), cross-sectional measurements of inflammation markers, notably interleukin-6 (IL-6) and high-sensitivity C-reactive protein (hsCRP) are linked to higher risk of subsequent mortality.1 Recently the International Network for Strategic Initiatives in Global HIV Trials study group reported that higher pre-ART levels of IL-6 and hsCRP were associated with increased risk of AIDS events and mortality on ART.2 Detailed measurements of markers of tumor necrosis factor α (TNF-α) and adhesion molecules were not performed in these aforementioned studies. Moreover, in past cross-sectional studies (not necessarily pre-ART measurements), the results have been conflicting in terms of the association between TNF-α levels and higher mortality or AIDS progression.3–5 No study has yet investigated the association between time-updated inflammatory marker levels after ART initiation and the occurrence of AIDS and non-AIDS events in the setting of a prospective randomized ART-initiation study.


AIDS Clinical Trials Group (ACTG) A5224s was a metabolic substudy of ACTG A5202. In A5202, ART-naive subjects aged ≥16 years with HIV-1 RNA of >1000 copies per milliliter were randomized in a double-blinded fashion to co-formulated tenofovir disoproxil fumarate/emtricitabine (TDF/FTC) or abacavir/lamivudine (ABC/3TC), along with open-labeled efavirenz or atazanavir/ritonavir. Randomization was stratified by screening HIV-1 RNA (< vs. ≥100,000 copies/mL) and by intent to participate in A5224s. A secondary biomarker substudy of A5224s included all subjects with available stored plasma at baseline and week 24 and/or 96 and was designed with the primary objective to compare the effect of ART initiation on inflammation markers, results that were already published.6 A secondary objective was to assess the association between baseline and on-ART markers of inflammation and clinical events, separately categorized as AIDS-defining event (CDC category C clinical events) or non–AIDS-defining events (including cardiovascular disease, non–AIDS-defining malignancies, diabetes, liver disease, serious infection that does not fit CDC category C clinical event) and bone fractures. The classification of non-AIDS events was similar to that used in a recently published analysis conducted within the ACTG,7 except that a priori, we selected to consider bone fractures as a separate events category and not lump them within the non-AIDS events category because all bone fractures that occurred within A5224s were the result of a trauma. A5224s' major exclusion criteria were endocrine diseases including diabetes mellitus. The duration of the substudy was 96 weeks after the last subject enrolled into A5202, and subjects were followed regardless of their antiretroviral treatment status. Each subject signed an informed consent that was approved by participating site's local Institutional Review Board.

Biomarker Assays

Plasma samples were stored at −80°C without previous thawing until analysis. Assays were performed at Johns Hopkins Bayview Advanced Chemistry Laboratory, Baltimore, MD. We measured 7 markers, hsCRP (μg/mL), IL-6 (pg/mL), TNF-α (pg/mL), and the soluble receptors of TNF-α (sTNFR-I and -II, both in pg/mL), along with the endothelial activation markers soluble vascular cellular and intercellular adhesion molecules (sVCAM-1 and sICAM-1, both in ng/mL). High-sensitivity C-reactive protein was measured using a highly sensitive enzyme-linked immunosorbent assay (ALPCO Diagnostics, Windham, NH). Other markers were measured using an enzyme-linked immunosorbent assay (R&D Systems, Minnesota, WI). Markers were measured in duplicate, and values averaged for analysis. The intra-assay and inter-assay precisions of these assays were 1.3%–7.6% coefficient of variation (average 3.3%) and 1.8%–9.0% coefficient of variation (average 6.9%), respectively.

Statistical Analysis

This exploratory and secondary analysis of the association between baseline and time-updated biomarker levels and times to first AIDS-defining event, non–AIDS-defining event, and bone fracture used Cox proportional hazards regression. Multivariable models adjusted for the following prespecified covariates that could affect inflammation: ART assignment, then ART assignment plus each of the following individually; baseline CD4, baseline HIV-1 RNA, time-updated CD4, time-updated HIV-1 RNA suppression <50 copies per milliliter, and time-updated HIV-1 RNA suppression <200 copies per milliliter.

In time-updated analysis, for subjects with missing week 24 or 96 biomarker levels, their last observed value, including the baseline value, was carried forward. In addition, to account for the potential confounding effect on the time-updated analysis of the early events that occurred before week 24, we performed a 24-week landmark analysis that excluded subjects with early events before week 24, subjects with missing week 24 sample and subjects with HIV-1 RNA level ≥50 copies per milliliter at week 24. In all models, CD4 was modeled with a linear and a quadratic term. P values below 0.05 were considered statistically significant; no adjustments were made for multiple comparisons. Analyses were performed using SAS, version 9.2 (SAS Institute). Because of skewed distributions, biomarkers were loge transformed before analysis.


Subject Characteristics

As previously detailed,8,9 269 subjects were enrolled in A5224s. Of these 269 subjects, 244 (91%) with available stored plasma from baseline and week 24 and/or 96 were included in this biomarker substudy. Baseline characteristics were previously reported.6 Table S1 is added to show baseline characteristics by study population (see Supplemental Digital Content, Overall, 85% were men, 48% white non-Hispanics, and among 205 subjects with available data, 41% were smokers. Median age was 39 years, CD4 240 cells per microliter, and HIV-1 RNA 4.64 log10 copies per milliliter. None of the subjects had a previous history of myocardial infarction and 1 had a history of stroke. Baseline characteristics were similar between the 244 included in the biomarker substudy, and the 25 A5224s subjects not included (data not shown).

At week 24, 171 (70%) had HIV-1 RNA<50 copies per milliliter (70% on TDF/FTC; 70% on ABC/3TC). Among subjects who had screening HIV-1 RNA ≥100,000 copies per milliliter, 56% on TDF/FTC and 60% on ABC/3TC had HIV-1 RNA <50 copies per milliliter.

Characteristics of Clinical Events

Only the first clinical event was considered for each subject in time to event analyses. There were a total of 13 AIDS events that occurred during the study: recurrent bacterial pneumonia (1), CMV retinitis (1), cryptosporidiosis (1), esophageal candidiasis (1), non-Hodgkin's lymphoma (2), Kaposi sarcoma (1), Mycobacterium avium complex (4), and Pneumocystis jirovecii pneumonia (2). These AIDS events happened after a median (range) of 15.6 (2.0–132.6) weeks on study, with 7 events occurring before week 24. A total of 18 subjects had at least 1 non-AIDS event that occurred during the study: acute myocardial infarction (2), pulmonary embolism (1), cancers (4: Hodgkin's disease 1, hypopharyngeal cancer 1, and prostate cancer 2), diabetes (6), isolated episode of non-pneumocystis pneumonia (5). These non-AIDS events happened after a median (range) of 81.4 (3.6–165.1) weeks on study, with 4 events occurring before week 24. When considering time to first AIDS or non-AIDS event, a total of 28 subjects had at least 1 event that occurred during study, 11 of which occurring before week 24. In addition, a total of 15 bone fractures occurred during the study, all of which were associated with a trauma.

Deaths were not included in the AIDS event or in the non-AIDS events. A total of 2 deaths were reported in the analysis sample. One subject was diagnosed with diabetes at week 24 then at week 106 was diagnosed with septic shock, non-Hodgkin's lymphoma, and a pulmonary embolism followed by death. The second subject died without a previous event at week 25 with the cause of death reported as substance abuse.

The week 24 landmark analysis included 5 AIDS-defining events (3 that occurred between weeks 24 and 96, and 2 that occurred after week 96), 12 non–AIDS-defining events (6 between weeks 24 and 96 and 6 after week 96), and for the combined event analysis, 14 AIDS or non-AIDS events (9 between 24 and 96 weeks and 5 after week 96).

Biomarker Associations With CD4 Counts

At baseline, CD4 count was inversely but not strongly correlated with levels of IL-6 (Spearman rank correlation r = −0.20, P = 0.002), sTNF-RI (r = −0.25, P < 0.001), and sTNF-RII (r = −0.30, P < 0.001) (see Table S2, Supplemental Digital Content, Also, the change in CD4 count from baseline to week 24 was inversely correlated with baseline to week 24 changes in levels of sVCAM-1 (r = −0.40, P < 0.001), sICAM-1 (r = −0.22, P = 0.001), sTNF-RII (r = −0.36, P < 0.001), sTNF-RI (r = −0.16, P = 0.015), and TNF-α (r = −0.29, P < 0.001). Similarly, the change in CD4 count from baseline to week 96 was correlated with baseline to week 96 changes in levels of sVCAM-1 (r = −0.36, P < 0.001), sTNF-RII (r = −0.23, P = 0.001), sTNF-RI (r = −0.14, P = 0.046), and TNF-α (r = −0.22, P = 0.001). Notably, neither baseline nor changes in CD4 count correlated with baseline or changes in hsCRP levels (r ≤ 0.07, P ≥ 0.31).

Biomarker Associations With HIV-1 RNA Levels

At baseline, HIV-1 RNA level correlated with levels of IL-6 (r = 0.17, P = 0.008), sVCAM-1 (r = 0.45, P < 0.001), sICAM-1 (r = 0.26, P < 0.001), sTNF-RII (r = 0.52, P < 0.001), sTNF-RI (r = 0.43, P < 0.001), and TNF-α (r = 0.38, P < 0.001), but not with hsCRP (r = 0.04, P = 0.49). Only for sTNFR-I was mean change from baseline to week 24 significantly different between subjects who at week 24 were virologically suppressed (<50 copies/mL) or not [estimated mean (standard deviation) −0.18 (0.23) vs. −0.12 (0.17) pg/mL; P = 0.018]. The mean (standard deviation) change from baseline to week 96 in sTNFR-II, sVCAM-1, and TNF-α were statistically significantly different between subjects who were virologically suppressed (<50 copies/mL) or not [−0.73 (0.43) vs. −0.52 (0.56) pg/mL; P = 0.019 and −0.53 (0.33) vs. −0.25 (0.42) ng/mL; P < 0.001, and −0.75 (0.42) vs. −0.37 (0.52) pg/mL; P < 0.001, respectively].

Biomarker Association With AIDS-Defining Event

We first examined for each of the 7 biomarkers the association between baseline biomarker value and time to first AIDS-defining event (Table 1). Higher values in baseline IL-6, sTNF-RI, sTNF-RII, and sICAM-1 were significantly associated with an increased risk of AIDS-defining event. Adjustment for ART assignment and for baseline HIV-1 RNA did not change the results (data not shown). Adjusting for baseline CD4 count attenuated the association of higher values with increased risk with these biomarkers, with baseline sICAM-1 remaining significantly associated with increased risk of events.

Baseline and Time-Updated Biomarker Association With AIDS-Defining Events

Table 1 also shows the associations between time-updated biomarker values and time to first AIDS event. The time-updated values in IL-6, sTNF-RI, sTNF-RI, and sICAM-1 were significantly associated with increased risk of AIDS-defining events. Adjustment for ART assignment and for baseline or time-updated CD4 counts attenuated the relationship (Table 1). Also, adjustment for ART assignment and for baseline HIV-1 RNA levels or for achieving virological suppression did not change the results. Results were similar whether virological suppression was defined as HIV-1 RNA <50 copies per milliliter or <200 copies per milliliter.

Biomarker Association With Non–AIDS-Defining Event

We also examined the associations between biomarker levels at baseline and time to first non–AIDS-defining event (Table 2). Baseline hsCRP was significantly associated with developing a non-AIDS event, and there was a trend for an association with IL-6. Adjustment for ART assignment and for baseline HIV-1 RNA levels did not change either of the results. Adjustment for baseline CD4 did not change the hsCRP results.

Baseline and Time-Updated Biomarker Association With Non–AIDS-Defining Events

Table 2 shows the associations between time-updated biomarkers and non-AIDS events. Only the time-updated TNF-α values were statistically significantly associated with an increased risk of non–AIDS-defining events. Adjustment for ART assignment, and for baseline or time-updated CD4 count, or baseline HIV-1 level or for achieving virological suppression (defined at <50 copies/mL or <200 copies/mL) did not change the results.

We considered fracture events as a separate category because of its unclear association with inflammation and the other categories of non-AIDS events. Neither baseline nor time-updated biomarker values were significantly associated with time to first fracture (data not shown).

Biomarker Association With First Clinical Event (AIDS or Non-AIDS Events)

A total of 28 first clinical events (AIDS or non-AIDS) were combined (Table 3). Higher values in baseline hsCRP, IL-6, sTNF-RI, and sTNF-RII were significantly associated with an increased risk of time to first AIDS- or non-AIDS clinical event. The Kaplan–Meier plots are shown in Figure 1, stratified by tertiles for these 4 markers. There was also a trend toward higher baseline TNF-α being associated with increased risk. Adjustment for ART assignment and for baseline HIV-1 RNA or CD4 count did not change the results for any of the baseline biomarkers associations with clinical events with the exception of sTNF-RI after adjustment for baseline CD4 which was no longer statistically significant.

Baseline and Time-Updated Biomarker Association With AIDS and Non–AIDS-Defining Events
Kaplan–Meier plots stratified by tertiles for hsCRP, IL-6, sTNFR-I, and sTNF-RII.

The association between time-updated biomarker value and the composite endpoint of clinical events was also assessed. Only the time-updated values for sTNF-RI and sTNF-RII were significantly associated with an increased risk of clinical events. In addition, time-updated biomarker value for TNF-α trended toward being associated with increased risk. Adjustment for ART assignment, for baseline or time-updated CD4 count, or baseline HIV-1 level, or for achieving virological suppression (defined at <50 copies/mL or <200 copies/mL) did not change the results for sTNF-RI but sTNF-RII was no longer statistically significant. Adjusting for ART assignment and for achieving virological suppression (HIV-1 RNA <200 copies/mL) did strengthen the TNF-α association.

Week 24 Landmark Analysis

Among virologically suppressed subjects (HIV-1 RNA <50 copies/mL at week 24), additional analyses were undertaken to explore the association between week 24 biomarker level and time to first event occurring after week 24 (Table 4).

Landmark Analyses, Week 24 Biomarker Associations Among Subjects Without a Previous Event and HIV RNA Level <50 Copies/mL at Week 24

For time to first AIDS or non–AIDS defining event, 171 subjects were virologically suppressed and an additional 8 subjects were removed because of having an early event within the first 24 weeks (5 subjects) or having their baseline biomarker level carried forward to week 24 (3 subjects). Among the 163 subjects analyzed, there were 14 events (9 between week 24 and 96 and 5 after week 96). Week 24 sTNF-RI, sTNFR-II, TNF-α, and sVCAM-1 (per 0.5 loge higher) were significantly associated with developing an AIDS or non-AIDS event [hazard ratio (HR) = 3.53, 95% confidence interval (CI): 1.02 to 12.18, P = 0.046; HR = 1.80, 95% CI: 1.05 to 3.08, P = 0.033; HR = 1.75, 95% CI: 1.04 to 2.96, P = 0.035; and HR = 1.96, 95% CI: 1.02 to 3.76, P = 0.044, respectively]. After adjustment for ART assignment and week 24 CD4 count, only sTNF-RI remained statistically significant (HR = 4.20, 95% CI: 1.10 to 16.03, P = 0.036).


The absolute CD4 cell count has been extensively used as a tool to predict HIV disease progression and morbidities. A more recent focus has been on the association between immune activation and inflammatory biomarkers and HIV mortality and co-morbidities on ART. Thus far, several studies have linked a single measurement of an inflammatory marker to subsequent mortality,10–12 myocardial infarction risk,13 and increased intima media thickness14,15 (a marker of vascular disease). In contrast, very limited data exist on the association between either pre-ART or on-ART biomarker values to clinical events. To our knowledge, our study is the largest and longest study to use such an approach to assess this association in a randomized ART-initiation clinical trial. We showed that higher pre-ART and on-ART levels of several inflammatory biomarkers were associated independently of CD4 count with increased risk of progression to AIDS and/or non-AIDS events.

The association between pre-ART inflammatory marker levels and the risk of progression to clinical events on suppressive ART has been investigated in few studies. Our findings that higher pre-ART IL-6 is associated with increased risk of AIDS-defining event is consistent with the results of 2 case–control studies.2,16 One of these studies also found that pre-ART sTNF-RI (but not sTNF-RII) was associated with such a risk.16 However, in contrast to one of these studies,2 we did not find an association with baseline hsCRP. Rather, we found that higher baseline hsCRP is associated with increased rate of progression to a non-AIDS event. When we combined progression to AIDS and non-AIDS events, baseline hsCRP and IL-6 were associated with increased risk of clinical progression.

Limited data exist on serial measurements of inflammatory markers in HIV-infected subjects starting their first ART regimen. It was notable in our study that overall, in both unadjusted and CD4-adjusted or HIV-1 RNA–adjusted analyses, time-updated levels in markers of TNF-α levels (levels of TNF-α or its soluble receptors) were associated with clinical events, whereas this was not observed for hsCRP, and less consistently so with IL-6. Importantly, our analyses were also adjusted for ART assignment. The lack of association between hsCRP and events is notable because of our previously described findings of more favorable changes in hsCRP after initiation of TDF/FTC versus ABC/3TC-containing regimens.6 However, we cannot rule out the possibility that hsCRP could be specifically associated with cardiovascular events as shown by others12 because only 3 cardiovascular events occurred during study. Also notable is that the findings of an association between markers of TNF-α levels with events is consistent with a previous case–control study in which 48 weeks after initiation of ART, levels of sTNFR-I and sTNFR-II but not CRP or IL-6 were independently associated with incident diabetes.17

The lack of association between any baseline or time-updated inflammatory markers and bone fractures is not too surprising because a relationship between HIV-associated heightened inflammation and changes in bone health remains speculative and not proven. Indeed, in 1 previous study, we showed that changes in the inflammatory markers sTNFR-I and -II were not associated with changes in whole-body bone mineral density.18 Also, all bone fractures that occurred in A5224s were associated with a traumatic event, and thus may not represent pathologic bone health.

Our study has some limitations, including relatively small number of events that limits the precision on the hazard ratio estimates, resulting in wide CIs, possible selection bias of A5224s subjects who have available week 24 and/or 96 samples (possibly favoring healthier subjects with lower inflammation and maybe lower event rates) and the large number of analyses performed without adjustment for multiple comparisons, which may increase the probability of erroneously declaring an association. Also, because we had a relatively small number of events, the adjusted analyses should be interpreted with caution, as the number of events per covariate in some of these models was <10.19 The small number of events also limited our ability to adjust for all potential confounders such as smoking or hepatitis. The time-updated analyses need to be interpreted with caution because 7 of 13 AIDS events and 4 of 18 non-AIDS occurred before the first postbaseline biomarker measurement time point at week 24, where subjects had to remain event free before through that time point before the baseline value was updated. Nonetheless, this study is the longest study to date that investigated biomarker associations with clinical events in a group of subjects who recently initiated ART with regimens that are still current today. Also, an additional strength of the study is the randomization to the ART regimen, which provides balance in unmeasured covariates.

In summary, we showed that higher levels of several inflammatory biomarkers were associated independently of CD4 with increased risk of AIDS or non-AIDS events. Larger and longer studies should investigate the use of these markers as predictors of clinical end points, especially during long-term viral suppression on ART.

AIDS Clinical Trials Group A5224s

Sadia Shaik, MD and Ruben Lopez, MD—Harbor-UCLA Medical Center (Site 603) CTU Grant AI0694241 and UL1-RR033176. Susan L. Koletar, MD and Diane Gochnour, RN—The Ohio State University Medical Center (Site 2301) CTU Grant AI069474. Geyoul Kim, RN and Mark Rodriguez, RN—Washington University (Site 2101) CTU Grant U01AI069495 and GCRC Grant UL1 RR024992. Elizabeth Lindsey, RN and Tamara James, BS—Alabama Therapeutics CRS (Site 5801) CTU Grant U01 AI069452. Ann C. Collier, MD and Jeffrey Schouten, MD, JD—University of Washington (Site 1401) CTU Grant AI069434 and UL1 RR025014. Jorge L. Santana Bagur, MD and Santiago Marrero, MD—Puerto Rico-AIDS Clinical Trials Unit (Site 5401) CTU Grant 5 U0I AI069415-03. Jenifer Baer, RN, BSN and Carl Fichtenbaum, MD—University of Cincinnati (Site 2401) CTU Grant AI069513. Patricia Walton, BSN, RN and Barbara Philpotts, BSN, RN—Case Western Reserve (Site 2501) CTU Grant AI69501. Princy Kumar, MD and Joseph Timpone, MD—Georgetown University (Site 1008) CTU Grant ACTG and Grant 5U01AI069494. Donna Pittard, RN, BSN and David Currin, RN—University of North Carolina (Site 3201) CTU Grant 5-U01 AI069423-03, UNC CFAR, P30 AI050410(-11), UNC CTRC, and UL 1RR 025747. Julie Hoffman, RN and Edward Seefried, RN—San Diego Medical Center UC (Site 701) CTU Grant AI69432. Susan Swindells, MBBS and Frances Van Meter, APRN—University of Nebraska (Site 1505) CTU Grant AI 27661. Deborah McMahon, MD and Barbara Rutecki, MSN, MPH, CRNP—University of Pittsburgh (Site 1001) CTU Grant 1 U01 AI069494-01. Michael P. Dube, MD and Martha Greenwald, RN, MSN—Indiana University (Site 2601) CTU Grant 5U01AI025859, GCRC M01 RR00750. Ilene Wiggins, RN and Eric Zimmerman, RN—Johns Hopkins University (Site 201) CTU Grant AI27668 and CTSA Grant UL1 RR 025005. Judith Aberg, MD and Margarita Vasquez, RN—New York University/NYC HHC at Bellevue Hospital Center (Site 401) CTU Grant AI27665, New Grant AI069532. Martin McCarter and M. Graham Ray, RN, MSN—Colorado AIDS Clinical Trials Unit (Site 6101) CTU Grant AI69450 and RR025780. Mamta Jain, MD—PI and Tianna Petersen, MS—University of Texas Southwestern Medical Center (Site 3751) CTU Grant 3U01AI046376-05S4. Emily Stumm, BS and Pablo Tebas, MD—University of Pennsylvania, Philadelphia (Site 6201) CTU Grant P30-AI0450008-11 and CFAR Grant UO1-AI069467-04. Mary Albrecht, MD and Neah Kim, NP—Beth Israel Deaconess (Partners/Harvard) CRS (Site 103) CTU Grant U01 AI 069472-04 Paul Edward Sax, MD and Joanne Delaney, RN—Brigham and Women's Hospital (Site 107) CTU Grant UOI AI 069472. Christine Hurley, RN and Roberto Corales, DO—AIDS Care (Site 1108) CTU Grant U01AI069511-02 (as of December 2, 2008); GCRC: UL1 RR 024160. Keith Henry, MD and Bette Bordenave, RN—Hennepin County Medical Center (Site 1502) CTU Grant N01 AI72626. Wendy Armstrong, MD and Ericka R. Patrick, RN, MSN, CCRC—Emory University HIV/AIDS Clinical Trails Unit (Site 5802) CTU Grant UO1Al69418-01/CFAR Grant P30Al050409. Jane Reid, RNC, MS and Mary Adams, RN, MPh—University of Rochester (Site 1101) CTU Grant U01AI069511-02 (as of December 2, 2008); GCRC: UL1 RR 024160. Gene D. Morse, PharmD, FCCP, BCPS—SUNY Buffalo, Erie County Medical Center (Site 1102) CTU Grant AI27658. Michael P. Dube, MD and Martha Greenwald, RN, MSN—Wishard Memorial Hospital Indiana University (Site 2603) CTU Grant 5U01AI025859 and GCRC: M01 RR00750. Kimberly Y. Smith, MD, MPH and Joan A. Swiatek, APN—Rush University Medical Center (Site 2702) CTU Grant U01 AI069471. Nancy Hanks, RN and Debra Ogata-Arakaki, RN—University of Hawaii at Manoa, Leahi Hospital (Site 5201) CTU Grant AI34853. Ardis Moe, MD and Maria Palmer, PA-C—UCLA Medical Center (Site 601) CTU Grant 1U01AI069424-01. Jeffery Meier, MD and Jack T. Stapleton, MD—University of Iowa Hospitals and Clinics (Site 1504) CTU Grant UL1RR024979. Gary Matthew Cox, MD and Martha Silberman, RN—Duke University Medical Center Adult CRS (Site 1601) CTU Grant 5U01 AI069 484-02. 2705—Cook County Hospital. Gerianne Casey, RN and William O'Brien, MD—University of Texas, Galveston (Site 6301) CTU Grant AI32782. Valery Hughes, FNP and Todd Stroberg, RN—Cornell CRS (Site 7803, 7804)—CTU Grant U01 AI069419; CTSC: UL1 RR024996. Nyef El-Daher, MD—McCree McCuller Wellness Center at the Connection (Site 1107) CTU Grant U01AI069511-02 (as of December 2, 2008); GCRC: UL1 RR 024160. Rebecca J. Basham, BS and Husamettin Erdem, MD—Vanderbilt Therapeutics CRS (Site 3652) CTU Grant AI46339-01 and MO1 RR 00095.


1. Neaton JD, Neuhaus J, Emery S. Soluble biomarkers and morbidity and mortality among people infected with HIV: summary of published reports from 1997 to 2010. Curr Opin HIV AIDS. 2010;5:480–490. PMCID: 3079321.
2. Boulware DR, Hullsiek KH, Puronen CE, et al.. Higher levels of CRP, D-dimer, IL-6, and hyaluronic acid before initiation of antiretroviral therapy (ART) are associated with increased risk of AIDS or death. J Infect Dis. 2011;203:1637–1646. PMCID: 3096784.
3. Medrano FJ, Leal M, Arienti D, et al.. Tumor necrosis factor beta and soluble APO-1/Fas independently predict progression to AIDS in HIV-seropositive patients. AIDS Res Hum Retroviruses. 1998;14:835–843.
4. Zangerle R, Steinhuber S, Sarcletti M, et al.. Serum HIV-1 RNA levels compared to soluble markers of immune activation to predict disease progression in HIV-1-infected individuals. Int Arch Allergy Immunol. 1998;116:228–239.
5. Havlir DV, Torriani FJ, Schrier RD, et al.. Serum interleukin-6 (IL-6), IL-10, tumor necrosis factor (TNF) alpha, soluble type II TNF receptor, and transforming growth factor beta levels in human immunodeficiency virus type 1-infected individuals with Mycobacterium avium complex disease. J Clin Microbiol. 2001;39:298–303. PMCID: 87718.
6. McComsey GA, Kitch D, Daar ES, et al.. Inflammation markers after randomization to abacavir/lamivudine or tenofovir/emtricitabine with efavirenz or atazanavir/ritonavir: ACTG A5224 s, A5202 substudy. AIDS. 2012;26:1371–1385.
7. Overton ET, Kitch D, Benson CA, et al.. Effect of statin therapy in reducing the risk of serious non-AIDS-defining events and nonaccidental death. Clin Infect Dis. 2013;56:1471–1479.
8. McComsey G, Kitch D, Daar E, et al.. Bone mineral density and fractures in antiretroviral-naive subjects randomized to abacavir/lamivudine or tenofovir disoproxil fumarate/emtricitabine along with efavirenz or atazanavir/ritonavir: AIDS Clinical Trials Group A5224s, a substudy of ACTG A5202. J Infect Dis. 2011;203:1791–1801.
9. McComsey G, Kitch D, Sax PE, et al.. Peripheral and central fat changes in subjects randomized to abacavir/lamivudine or tenofovir/emtricitabine with atazanavir/ritonavir or efavirenz: ACTG study A5224s. Clin Infect Dis. 2011;53:185–196.
10. Kuller LH, Tracy R, Belloso W, et al.. Inflammatory and coagulation biomarkers and mortality in patients with HIV infection. PLoS Med. 2008;5:e203. PMCID: 2570418.
11. Feldman JG, Goldwasser P, Holman S, et al.. C-reactive protein is an independent predictor of mortality in women with HIV-1 infection. J Acquir Immune Defic Syndr. 2003;32:210–214.
12. Drain PK, Kupka R, Msamanga GI, et al.. C-reactive protein independently predicts HIV-related outcomes among women and children in a resource-poor setting. AIDS. 2007;21:2067–2075.
13. Triant VA, Meigs JB, Grinspoon SK. Association of C-reactive protein and HIV infection with acute myocardial infarction. J Acquir Immune Defic Syndr. 2009;51:268–273. PMCID: 2763381.
14. Ross AC, Rizk N, O'Riordan MA, et al.. Relationship between inflammatory markers, endothelial activation markers, and carotid intima-media thickness in HIV-infected patients receiving antiretroviral therapy. Clin Infect Dis. 2009;49:1119–1127.
15. Ross AC, O'Riordan MA, Storer N, et al.. Heightened inflammation is linked to carotid intima-media thickness and endothelial activation in HIV-infected children. Atherosclerosis. 2010;211:492–498.
16. Kalayjian RC, Machekano RN, Rizk N, et al.. Pretreatment levels of soluble cellular receptors and interleukin-6 are associated with HIV disease progression in subjects treated with highly active antiretroviral therapy. J Infect Dis. 2010;201:1796–1805. PMCID: 2873127.
17. Brown TT, Tassiopoulos K, Bosch RJ, et al.. Association between systemic inflammation and incident diabetes in HIV-infected patients after initiation of antiretroviral therapy. Diabetes Care. 2010;33:2244–2249. PMCID: 2945167.
18. Brown TT, McComsey GA, King MS, et al.. Loss of bone mineral density after antiretroviral therapy initiation, independent of antiretroviral regimen. J Acquir Immune Defic Syndr. 2009;51:554–561.
19. Peduzzi P, Concato J, Feinstein AR, et al.. Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates. J Clin Epidemiol. 1995;48:1503–1510.

inflammation markers; AIDS events; non-AIDS events; C-reactive protein; interleukin-6; endothelial activation markers; TNF-α

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