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Associations of Inflammatory Markers with AIDS and non-AIDS Clinical Events after Initiation of Antiretroviral Therapy (ART): AIDS Clinical Trials Group A5224s, a substudy of ACTG A5202 Grace A McComsey , Douglas Kitch, Paul E Sax, Camlin Tierney, Nasreen C Jahed, Kathleen Melbourne, Belinda Ha, Todd T Brown, Anthony Bloom, Neal Fedarko, and Eric S Daar on behalf of the ACTG A5224s team

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Grace A McComsey , Douglas Kitch, Paul E Sax, Camlin Tierney, Nasreen C Jahed, Kathleen Melbourne, Belinda Ha, Todd T Brown, Anthony Bloom, Neal Fedarko, and Eric S Daar on behalf of the ACTG A5224s team. - PowerPoint PPT Presentation

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Page 1: Background

Associations of Inflammatory Markers with AIDS and non-AIDS Clinical Events

after Initiation of Antiretroviral Therapy (ART): AIDS Clinical Trials Group A5224s, a substudy of ACTG

A5202

Grace A McComsey, Douglas Kitch, Paul E Sax, Camlin Tierney, Nasreen C Jahed, Kathleen Melbourne, Belinda Ha, Todd T Brown, Anthony Bloom, Neal Fedarko, and Eric S Daar on behalf of the ACTG A5224s team

Page 2: Background

Background

Increased inflammation persists on ART and may drive clinical events and mortality

Several studies have found associations between

single measurements of selective inflammatory markers and mortality

The purpose of this presentation is to present the associations between inflammatory markers (pre-ART and after ART initiation) and clinical events in a prospective clinical trial

A5224s

Page 3: Background

A5224s design: Metabolic substudy of A5202

A5224s

Page 4: Background

Biomarker Substudy

• Significant decreases in TNF-, sTNFR-I, sTNFR-II, sVCAM-1, and sICAM-1 levels within all arms, without differences between ABC/3TC and TDF/FTC or ATV/r and EFV

• More favorable changes in IL-6 at week 24 and hsCRP at weeks 24 and 96 with TDF/FTC vs. ABC/3TC

McComsey, AIDS 2012 A5224s

Page 5: Background

Study Objective and Statistical Methods

Exploratory analysisTo assess the association between

baseline and time-updated inflammatory biomarker levels and time to first AIDS-defining and/or non-AIDS-defining events

Cox proportional hazards regression models

Only first event occurring in each category in each subject was used in analysis

Page 6: Background

Baseline characteristics

N=244Age years, median (Q1, Q3) 39 (31, 44)Male (%) 85%White non-Hispanic Race/Ethnicity (%) 48%

HIV-1 RNA log10 c/mL, median (Q1, Q3)

4.64 (4.26, 4.91)

HIV RNA ≥ 100,000 c/mL Stratum (%) 41%CD4 cells/mm3, median (Q1, Q3) 240 (106, 335)CD4 < 200 cells/mm3 (%) 43%hsCRP g/mL, median (Q1, Q3) 1.7 (0.7, 4.0)

IL-6 pg/mL, median (Q1, Q3) 0.8 (0.5, 1.4)

TNF-α pg/mL, median (Q1, Q3)11.0 (8.2,

14.7)

sTNF-RI pg/mL, median (Q1, Q3)1277 (1105,

1538)

sTNFR-II pg/mL, median (Q1, Q3)5350 (3965,

7756)

sVCAM-1 ng/mL, median (Q1, Q3)1187 (939,

1599)

sICAM-1 ng/mL, median (Q1, Q3) 330 (267, 402)

A5224s

Page 7: Background

Correlations Among Markers at Baseline

A5224sSpearman’s rank correlation coefficient

Page 8: Background

Correlations Among Markers at Week 24

A5224sSpearman’s rank correlation coefficient

Page 9: Background

Description of Events

AIDS-defining events (CDC classification) 13 events: 9 OIs; 3 AIDS-cancers, 1 recurrent bacterial pneumonia Events occurred between 2 and 133 weeks, median 16 weeks Of these, 7 events occurred within first 24 weeks

Non-AIDS events 18 events: 6 diabetes, 4 cancers, 3 cardiovascular, 5 pneumonias Events occurred between 3.5 and 165 weeks, median 81 weeks Of these, 4 events occurred within first 24 weeks

AIDS- or Non-AIDS events 28 events Events occurred between 2 and 164 weeks, median 32 weeks Of these, 11 events occurred within first 24 weeks

A5224s

Page 10: Background

AIDS Defining Events

Page 11: Background

Baseline associations with time to first AIDS-defining event

HR= hazard ratio from Cox Proportional Hazard model

Page 12: Background

Time-updated associations with time to first AIDS-defining event

HR= hazard ratio from Cox Proportional Hazard model

Page 13: Background

Non- AIDS Defining Events

Page 14: Background

Baseline associations with time to first non-AIDS defining event

HR= hazard ratio from Cox Proportional Hazard model

Page 15: Background

Time-updated associations with time to first non-AIDS defining event

HR= hazard ratio from Cox Proportional Hazard model

Page 16: Background

AIDS and Non- AIDS Defining Events Combined

Page 17: Background

Baseline associations with time to first AIDS or non-AIDS Event

HR= hazard ratio from Cox Proportional Hazard model

Page 18: Background

Other Results

A5224s

Page 19: Background

Time-updated associations with time to first AIDS or non-AIDS defining event

HR= hazard ratio from Cox Proportional Hazard model

Page 20: Background

Bone Fractures

15 (traumatic) fractures occurred Considered separate from non-AIDS

eventsNeither baseline nor time-updated

biomarker values were significantly associated with an increased risk of fracture

Page 21: Background

Correlation of markers with CD4 count and HIV-1 RNA levels

At baseline, CD4 count correlated with IL6, sTNFR-I and II

Changes in CD4 correlated with changes in TNF- , sTNF-Rs and adhesion molecules

At baseline, HIV-1 RNA correlated with all markers except for hsCRP

Only change (0-24 w) in sTNFR-I level significantly different between suppressed subjects vs. those >50 copies/mL at week 24

Page 22: Background

Conclusion

Higher levels of several inflammatory biomarkers were associated independently of CD4 count with increased risk of AIDS and non-AIDS events.

Time-updated levels in markers of TNF- and/or sTNF receptors were associated with clinical events whereas this was not observed for hsCRP.

Page 23: Background

Study Limitations

Small number of events Relatively short follow up Time-updated for AIDS events driven by

early events Large number of analyses performed Adjusted analyses to be interpreted with

caution (small events n)

Larger and longer studies needed to investigate the use of these markers as predictors of clinical endpoints.

Page 24: Background

Thank yous

Study Participants and ACTG sites

ACTG 5224s team: Douglas Kitch and Camlin Tierney (SDAC), Paul Sax, Eric Daar, Pablo Tebas, Nasreen Jahed, Laurie Myers, Belinda Ha, Kathleen Melbourne, Lynda Szczech, David Currin, Lori Mong-Kryspin

ACTG 5202 team

ACTG and NIH (NIAID) for supporting A5202/5224 studies

GSK and Gilead for supporting inflammatory markers cost

A5224s