How to RESPOND to Modern Challenges for People Living with HIV: A Profile for a New Cohort Consortium
Abstract
:1. Introduction
2. Materials and Methods:
2.1. Cohort Participation
2.2. Inclusion Criteria
2.3. Ethical Considerations
2.4. Consortium Organization and Governance:
2.5. Scientific Focus and Development of Scientific Agendas
2.6. Data Collection and Quality Assurance
3. Results
3.1. Baseline Demographics and Clinical Caracteristics
3.2. ART Exposure
3.3. Clinical Events
3.4. First RESPOND Findings
4. Discussion
4.1. Pharmacovigilance and Comorbidities in a Modern Era
4.2. Hepatitis and Other Infectious Diseases
4.3. Using Cohort Data to Support Public Health Challenges
4.4. Limitations
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Writing Group Members
- CHIP, Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark;
- Centre for Clinical Research, Epidemiology, Modelling and Evaluation (CREME), Institute for Global Health, University College London, London, UK;
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Switzerland;
- Austrian HIV Cohort Study (AHIVCOS), Medizinische Universität Innsbruck, Innsbruch, Austria;
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich Switzerland;
- Royal Free HIV Cohort, London, England;
- Department of Infectious Diseases, St Pierre University Hospital Bruxelles, Brussels, Belgium;
- Modena HIV Cohort, Università degli Studi di Modena, Modena, Italy;
- San Raffaele Scientific Institute, Università Vita-Salute San Raffaele, Milano, Italy;
- Italian Cohort Naive Antiretrovirals (ICONA), ASST Santi Paolo e Carlo, Milano, Italy;
- University Hospital Cologne, Cologne, Germany;
- Universitätsklinikum Bonn und Medizinische Fakultät, Bonn, Germany;
- Nice HIV Cohort, Université Côte d’Azur et Centre Hospitalier Universitaire, Nice, France;
- Georgian National AIDS Health Information System (AIDS HIS), Infectious Diseases, AIDS and Clinical Immunology Research Center, Tbilisi, Georgia;
- AIDS Therapy Evaluation in The Netherlands (ATHENA) cohort, Stichting HIV Monitoring, Amsterdam, The Netherlands;
- The Australian HIV Observational Database (AHOD), UNSW Sidney, Sydney, Austalia;
- Swedish InfCare HIV Cohort, Karolinska University Hospital, Stockholm, Sweden;
- PISCIS Cohort Study, Centre Estudis Epidemiologics de ITS i VIH de Catalunya (CEEISCAT), Badalona, Spain;
- Frankfurt HIV Cohort Study, Johann Wolfgang Goethe-University Hospital, Frankfurt, Germany;
- ViiV Healthcare, RTP, North Carolina, USA;
- Gilead Sciences, Foster City, California;
- Medical University of Warsaw, Poland;
- Hosp. Universitari Germans Trias i Pujol, Badalona, Spain;
- Austrian HIV Cohort Study (AHIVCOS), Medizinische Universität Wien, Vienna, Austria;
- European AIDS Treatment Group (EATG)
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RESPOND Core Variables | Study Specific Variables | |
---|---|---|
Demographics and Basic Information | Date of birth | Ethnicity |
Sex | Country of origin | |
Date first seen at department | Non-intravenous illicit drug use | |
Date of first positive HIV1-Ab/Ag test | Intravenous drug use | |
Height | ||
Weigth | ||
Baseline smoking status | ||
Current smoking status | ||
Risk of HIV acquisition of infection | ||
Risk of HCV acquisition of infection | ||
Risk of HBV acquisition of infection | ||
Infection Related Laboratory Values | HIV RNA | CD8 counts |
CD4 counts | HLA B*57:01 | |
HCV-antibodies | HCV genotype (and subtype) | |
HCV RNA | Blood samples | |
HBS Antigen | Tuberculosis diagnosis | |
HBV DNA | Tuberculosis resistance | |
Laboratory Values | Creatinin | ALT |
Total cholesterol | AST | |
HDL cholesterol | INR | |
LDL cholesterol | Hemoglobin | |
Triglycerides | Bilirubin | |
HbA1C or blood glucose | Albumin | |
Urine dipstick tests for proteinuria | ||
Antiviral Treatment Treatment * | Nucleos(t)ide reverse transcriptase inhibitors | Hepatitis C treatment |
Non-nucleotide reverse transcriptase inhibitors | ||
Protease inhibitors (cobicistat/ritonavir boosted or upboosted) | ||
Integrase strand transfer inhibitors Entry inhibitors | ||
Fusion inhibitors | ||
Non-Antiviral Treatment Treatment * | Anti-thrombotic drugs | Opioid substitution therapy |
Anti-hypertensive drugs | Anti-Tuberculosis treatment | |
Anti-diabetic drugs | ||
Lipid lowering drugs | ||
Other Paraclinical Data | Blood pressure | Bone Mass density: t-score |
Bone Mass density: z-score | ||
Bone Mass density area | ||
Liver trans elastography (fibroscan) | ||
Liver biopsy (metavir stage) | ||
Acoustic radiation force impulse (ARFI) | ||
HCC screening (Abdominal CT/MRI and ultrasound) | ||
Clinical Events | Myocardial Infarctions ** | Pregnancy |
Stroke ** | ||
Invasive cardiovascular procedures (coronary angioplasty/stenting, coronary bypass surgery, and carotid endarterectomi) ** | ||
Non-AIDS defining malignancies ** | ||
End-stage liver disease ** | ||
End-stage renal disease ** | ||
Fracture ** | ||
AIDS events (including AIDS defining cancers **) | ||
Deaths *** |
n | % | ||
---|---|---|---|
All | 26,258 | 100 | |
Age (Years) | ≤40 | 6488 | 24.9 |
41–50 | 7909 | 30.4 | |
51–60 | 7811 | 30.0 | |
>60 | 3810 | 14.6 | |
Region | Southern Europe (plus Argentina) | 6933 | 26.6 |
Western Europe | 13,320 | 51.2 | |
Northern Europe (plus Australia) | 2524 | 9.7 | |
Central Eastern Europe | 1421 | 5.5 | |
Eastern Europe | 1820 | 7.0 | |
Sex | Male | 19,329 | 74.3 |
Female | 6679 | 25.7 | |
Race | White | 18,834 | 72.4 |
Black | 4368 | 16.8 | |
Other/Unknown | 2816 | 10.8 | |
HIV Acquisition Risk | Men-sex-with-men | 11,300 | 43.4 |
Intraveneous drug use | 3883 | 14.9 | |
Heterosexual | 8931 | 34.3 | |
Other/Unknown | 1904 | 7.3 | |
Viral load (copies/mL) * | <200 | 24,073 | 89.5 |
≥200 | 2185 | 10.5 | |
<LOD, where LOD> 200 cp/mL ** | 165 | 0.6 | |
ART naïve | No | 24,634 | 94.7 |
Yes | 1384 | 5.3 | |
CD4 (cells/μL) *** | ≤200 | 1410 | 5.4 |
201–350 | 2689 | 10.3 | |
351–500 | 4429 | 17.0 | |
501–750 | 8758 | 33.7 | |
>750 | 8861 | 33.3 | |
CD4 Nadir (cells/μL) | ≤50 | 4268 | 16.4 |
51–200 | 8233 | 31.6 | |
201–350 | 7813 | 30.0 | |
>350 | 5544 | 21.3 | |
Date of HIV diagnosis | ≤2011 | 20,723 | 79.6 |
>2012 | 4494 | 17.3 | |
Unknown | 801 | 3.1 | |
HBV status | Negative | 21,088 | 81.1 |
Positive | 1347 | 5.2 | |
Unknown | 3583 | 13.8 | |
HCV status | Negative | 16,727 | 64.3 |
Positive | 6622 | 25.5 | |
Unknown | 2669 | 10.3 | |
Median | Interquartile Range | ||
Age (years) | 48 | 40–56 | |
CD4 (cells/μL) | 621 | 438–830 | |
CD4 Nadir (cells/μL) | 208 | 91–327 | |
Baseline date (month/year) | 6/17 | 12/15–9/17 |
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The RESPOND Study Group. How to RESPOND to Modern Challenges for People Living with HIV: A Profile for a New Cohort Consortium. Microorganisms 2020, 8, 1164. https://doi.org/10.3390/microorganisms8081164
The RESPOND Study Group. How to RESPOND to Modern Challenges for People Living with HIV: A Profile for a New Cohort Consortium. Microorganisms. 2020; 8(8):1164. https://doi.org/10.3390/microorganisms8081164
Chicago/Turabian StyleThe RESPOND Study Group. 2020. "How to RESPOND to Modern Challenges for People Living with HIV: A Profile for a New Cohort Consortium" Microorganisms 8, no. 8: 1164. https://doi.org/10.3390/microorganisms8081164