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Lodi S, Phillips A, Lundgren J, Logan R, Sharma S, Cole SR, Babiker A, Law M, Chu H, Byrne D, Horban A, Sterne JAC, Porter K, Sabin C, Costagliola D, Abgrall S, Gill J, Touloumi G, Pacheco AG, van Sighem A, Reiss P, Bucher HC, Montoliu Giménez A, Jarrin I, Wittkop L, Meyer L, Perez-Hoyos S, Justice A, Neaton JD, Hernán MA. Effect Estimates in Randomized Trials and Observational Studies: Comparing Apples With Apples. Am J Epidemiol 2019; 188:1569-1577. [PMID: 31063192 DOI: 10.1093/aje/kwz100] [Citation(s) in RCA: 79] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Accepted: 04/17/2019] [Indexed: 12/25/2022] Open
Abstract
Effect estimates from randomized trials and observational studies might not be directly comparable because of differences in study design, other than randomization, and in data analysis. We propose a 3-step procedure to facilitate meaningful comparisons of effect estimates from randomized trials and observational studies: 1) harmonization of the study protocols (eligibility criteria, treatment strategies, outcome, start and end of follow-up, causal contrast) so that the studies target the same causal effect, 2) harmonization of the data analysis to estimate the causal effect, and 3) sensitivity analyses to investigate the impact of discrepancies that could not be accounted for in the harmonization process. To illustrate our approach, we compared estimates of the effect of immediate with deferred initiation of antiretroviral therapy in individuals positive for the human immunodeficiency virus from the Strategic Timing of Antiretroviral Therapy (START) randomized trial and the observational HIV-CAUSAL Collaboration.
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Affiliation(s)
- Sara Lodi
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Andrew Phillips
- Institute for Global Health, University College London, United Kingdom
| | - Jens Lundgren
- Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Denmark
| | - Roger Logan
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Shweta Sharma
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | | | - Abdel Babiker
- Medical Research Council, Clinical Trials Unit in University College London, London, United Kingdom
| | | | - Haitao Chu
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Dana Byrne
- Division of Infectious Diseases, Department of Medicine, Cooper University Hospital, Cooper Medical School at Rowan University, New Jersey
| | - Andrzej Horban
- Medical University of Warsaw, Department for Adult's Infectious Diseases, Warsaw, Poland
| | - Jonathan A C Sterne
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, North Carolina
- Department of Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Kholoud Porter
- Institute for Global Health, University College London, United Kingdom
| | - Caroline Sabin
- Institute for Global Health, University College London, United Kingdom
| | - Dominique Costagliola
- INSERM, Sorbonne Université, Institut Pierre Louis d’Épidémiologie et de Santé Publique (IPLESP), Paris, France
| | - Sophie Abgrall
- INSERM, Sorbonne Université, Institut Pierre Louis d’Épidémiologie et de Santé Publique (IPLESP), Paris, France
- AP-HP, Hôpital Antoine Béclère, Service de Médecine Interne, Clamart, France
| | - John Gill
- Southern Alberta Clinic, Calgary, Canada
- Department of Medicine, University of Calgary, Canada
| | - Giota Touloumi
- National and Kapodistrian University of Athens, Faculty of Medicine, Dept. of Hygiene, Epidemiology and Medical Statistics, Greece
| | - Antonio G Pacheco
- Programa de Computação Científica, Fundacao Oswaldo Cruz, Rio de Janeiro, Brasil
| | | | - Peter Reiss
- Stichting HIV Monitoring, Amsterdam, the Netherlands
- Amsterdam University Medical Centres, University of Amsterdam, Department of Global Health and Division of Infectious Diseases, Amsterdam, the Netherlands
- Amsterdam Institute for Global Health and Development, and Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Heiner C Bucher
- Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, University of Basel, Switzerland
| | - Alexandra Montoliu Giménez
- Centre for Epidemiological Studies on HIV/STI in Catalonia (CEEISCAT), Agència de Salut Pública de Catalunya (ASPC), Badalona, Spain
| | - Inmaculada Jarrin
- Centro Nacional de Epidemiología, Instituto de Salud Carlos III, Madrid, Spain
| | - Linda Wittkop
- Univ. Bordeaux, ISPED, Inserm, Bordeaux Population Health Research Center, team MORPH3EUS, UMR 1219, CIC-EC 1401, Bordeaux, France
| | - Laurence Meyer
- CHU de Bordeaux, Pôle de santé publique, Service d'information médicale, Bordeaux, France
- Université Paris Sud, UMR 1018, le Kremlin Bicêtre, France
| | | | - Amy Justice
- Yale University School of Medicine, New Haven, Connecticut
| | - James D Neaton
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Miguel A Hernán
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Harvard-MIT Division of Health Sciences and Technology, Boston, Massachusetts
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Cain LE, Caniglia EC, Phillips A, Olson A, Muga R, Pérez-Hoyos S, Abgrall S, Costagliola D, Rubio R, Jarrín I, Bucher H, Fehr J, van Sighem A, Reiss P, Dabis F, Vandenhende MA, Logan R, Robins J, Sterne JAC, Justice A, Tate J, Touloumi G, Paparizos V, Esteve A, Casabona J, Seng R, Meyer L, Jose S, Sabin C, Hernán MA. Efavirenz versus boosted atazanavir-containing regimens and immunologic, virologic, and clinical outcomes: A prospective study of HIV-positive individuals. Medicine (Baltimore) 2016; 95:e5133. [PMID: 27741139 PMCID: PMC5072966 DOI: 10.1097/md.0000000000005133] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2016] [Revised: 07/26/2016] [Accepted: 07/27/2016] [Indexed: 11/25/2022] Open
Abstract
OBJECTIVE To compare regimens consisting of either ritonavir-boosted atazanavir or efavirenz and a nucleoside reverse transcriptase inhibitor (NRTI) backbone with respect to clinical, immunologic, and virologic outcomes. DESIGN Prospective studies of human immunodeficiency virus (HIV)-infected individuals in Europe and the United States included in the HIV-CAUSAL Collaboration. METHODS HIV-positive, antiretroviral therapy-naive, and acquired immune deficiency syndrome (AIDS)-free individuals were followed from the time they started an atazanavir or efavirenz regimen. We estimated an analog of the "intention-to-treat" effect for efavirenz versus atazanavir regimens on clinical, immunologic, and virologic outcomes with adjustment via inverse probability weighting for time-varying covariates. RESULTS A total of 4301 individuals started an atazanavir regimen (83 deaths, 157 AIDS-defining illnesses or deaths) and 18,786 individuals started an efavirenz regimen (389 deaths, 825 AIDS-defining illnesses or deaths). During a median follow-up of 31 months, the hazard ratios (95% confidence intervals) were 0.98 (0.77, 1.24) for death and 1.09 (0.91, 1.30) for AIDS-defining illness or death comparing efavirenz with atazanavir regimens. The 5-year survival difference was 0.1% (95% confidence interval: -0.7%, 0.8%) and the AIDS-free survival difference was -0.3% (-1.2%, 0.6%). After 12 months, the mean change in CD4 cell count was 20.8 (95% confidence interval: 13.9, 27.8) cells/mm lower and the risk of virologic failure was 20% (14%, 26%) lower in the efavirenz regimens. CONCLUSION Our estimates are consistent with a smaller 12-month increase in CD4 cell count, and a smaller risk of virologic failure at 12 months for efavirenz compared with atazanavir regimens. No overall differences could be detected with respect to 5-year survival or AIDS-free survival.
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Affiliation(s)
- Lauren E. Cain
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
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Masiá M, Padilla S, Barber X, Sanchis M, Terol G, Lidón F, Gutiérrez F. Comparative Impact of Suppressive Antiretroviral Regimens on the CD4/CD8 T-Cell Ratio: A Cohort Study. Medicine (Baltimore) 2016; 95:e3108. [PMID: 26986155 PMCID: PMC4839936 DOI: 10.1097/md.0000000000003108] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Although different factors have been implicated in the CD4/CD8 T-cell ratio recovery in HIV-infected patients who receive effective antiretroviral therapy (ART), limited information exists on the influence of the regimen composition. A longitudinal study carried out in a prospective, single-center cohort of HIV-infected patients. ART regimens including non-nucleoside reverse transcriptase inhibitors (NNRTI), protease inhibitors (PI), or integrase strand transfer inhibitors (INSTI) from patients who achieved long-term (≥6-month duration) virological suppression (HIV-RNA < 400 copies/mL) from January 1998 to June 2014 were analyzed. The impact of ART composition on the changes of the CD4/CD8 T-cell ratio was modeled using a mixed linear approach with adjustment for possible confounders. A total of 1068 ART regimens from 570 patients were analyzed. Mean (SD) age of the patients was 42.15 (10.68) years and 276 (48.42%) had hepatitis C virus (HCV) coinfection. Five hundred fifty-eight (52.25%) regimens were PI-based, 439 (40.10%) NNRTI-based, and 71 (6.65%) INSTI-based; 487 (45.60%) were initial regimens, 476 (44.57%) simplification, and 105 (9.83%) salvage regimens. Median (IQR) number of regimens was 1 (1-2) per patient, of 29 (14-58) months duration, and 4 (3-7) CD4/CD8 measurements per regimen. The median baseline CD4/CD8 ratio was 0.42, 0.50, and 0.54, respectively, with the PI-, NNRTI-, and INSTI-based regimens (P = 0.0073). Overall median (IQR) increase of CD4/CD8 ratio was 0.0245 (-0.0352-0.0690) per year, and a CD4/CD8 ratio ≥1 was achieved in 19.35% of the cases with PI-based, 25.97% with NNRTI-based, and 22.54% with INSTI-based regimens (P = 0.1406). In the adjusted model, the mean CD4/CD8 T-cell ratio increase was higher with NNRTI-based regimens compared for PI-based (estimated coefficient for PI [95% CI], -0.0912 [-0.1604 to -0.0219], P = 0.009). Also, a higher CD4/CD8 baseline ratio was associated with higher CD4/CD8 increase in the adjusted model (P = 0.001); by contrast, higher age (P = 0.020) and simplification of ART regimen (P = 0.003) had a negative impact on the CD4/CD8 ratio. Antiretroviral regimen composition has a differential impact on the CD4/CD8 T-cell ratio; NNRTI-based regimens are associated with enhanced CD4/CD8 T-cell ratio recovery compared to PI-based antiretroviral regimens.
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Affiliation(s)
- Mar Masiá
- From the Infectious Diseases Unit, Hospital General de Elche (MM, SP, GT, FL, FG), Universidad Miguel Hernández, Spain; and Statistics (XB, MS), Centro de Investigación Operativa, Universidad Miguel Hernández, Elche, Alicante, Spain
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Yang WL, Kouyos RD, Scherrer AU, Böni J, Shah C, Yerly S, Klimkait T, Aubert V, Hirzel C, Battegay M, Cavassini M, Bernasconi E, Vernazza P, Held L, Ledergerber B, Günthard HF. Assessing efficacy of different nucleos(t)ide backbones in NNRTI-containing regimens in the Swiss HIV Cohort Study. J Antimicrob Chemother 2015; 70:3323-31. [PMID: 26362944 DOI: 10.1093/jac/dkv257] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2015] [Accepted: 07/26/2015] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The most recommended NRTI combinations as first-line antiretroviral treatment for HIV-1 infection in resource-rich settings are tenofovir/emtricitabine, abacavir/lamivudine, tenofovir/lamivudine and zidovudine/lamivudine. Efficacy studies of these combinations also considering pill numbers, dosing frequencies and ethnicities are rare. METHODS We included patients starting first-line combination ART (cART) with or switching from first-line cART without treatment failure to tenofovir/emtricitabine, abacavir/lamivudine, tenofovir/lamivudine and zidovudine/lamivudine plus efavirenz or nevirapine. Cox proportional hazards regression was used to investigate the effect of the different NRTI combinations on two primary outcomes: virological failure (VF) and emergence of NRTI resistance. Additionally, we performed a pill burden analysis and adjusted the model for pill number and dosing frequency. RESULTS Failure events per treated patient for the four NRTI combinations were as follows: 19/1858 (tenofovir/emtricitabine), 9/387 (abacavir/lamivudine), 11/344 (tenofovir/lamivudine) and 45/1244 (zidovudine/lamivudine). Compared with tenofovir/emtricitabine, abacavir/lamivudine had an adjusted HR for having VF of 2.01 (95% CI 0.86-4.55), tenofovir/lamivudine 2.89 (1.22-6.88) and zidovudine/lamivudine 2.28 (1.01-5.14), whereas for the emergence of NRTI resistance abacavir/lamivudine had an HR of 1.17 (0.11-12.2), tenofovir/lamivudine 11.3 (2.34-55.3) and zidovudine/lamivudine 4.02 (0.78-20.7). Differences among regimens disappeared when models were additionally adjusted for pill burden. However, non-white patients compared with white patients and higher pill number per day were associated with increased risks of VF and emergence of NRTI resistance: HR of non-white ethnicity for VF was 2.85 (1.64-4.96) and for NRTI resistance 3.54 (1.20-10.4); HR of pill burden for VF was 1.41 (1.01-1.96) and for NRTI resistance 1.72 (0.97-3.02). CONCLUSIONS Although VF and emergence of resistance was very low in the population studied, tenofovir/emtricitabine appears to be superior to abacavir/lamivudine, tenofovir/lamivudine and zidovudine/lamivudine. However, it is unclear whether these differences are due to the substances as such or to an association of tenofovir/emtricitabine regimens with lower pill burden.
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Affiliation(s)
- Wan-Lin Yang
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Roger D Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Alexandra U Scherrer
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Jürg Böni
- Swiss National Center for Retroviruses, Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Cyril Shah
- Swiss National Center for Retroviruses, Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Sabine Yerly
- Laboratory of Virology, Division of Infectious Diseases, Geneva University Hospital, Geneva, Switzerland
| | - Thomas Klimkait
- Department of Biomedicine-Petersplatz, University of Basel, Basel, Switzerland
| | - Vincent Aubert
- Division of Immunology and Allergy, University Hospital Lausanne, Lausanne, Switzerland
| | - Cédric Hirzel
- Department of Infectious Diseases, Berne University Hospital and University of Berne, Berne, Switzerland
| | - Manuel Battegay
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, University Hospital Lausanne, Lausanne, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland
| | - Pietro Vernazza
- Division of Infectious Diseases, Cantonal Hospital St Gallen, St Gallen, Switzerland
| | - Leonhard Held
- Institute of Social and Preventive Medicine, University of Zurich, Zurich, Switzerland
| | - Bruno Ledergerber
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland Institute of Medical Virology, University of Zurich, Zurich, Switzerland
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