2019
Effect estimates in randomized trials and observational studies: comparing apples with apples
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, 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. American Journal Of Epidemiology 2019, 188: 1569-1577. PMID: 31063192, PMCID: PMC6670045, DOI: 10.1093/aje/kwz100.Peer-Reviewed Original ResearchMeSH KeywordsAdultAnti-Retroviral AgentsEpidemiologic MethodsFemaleHIV InfectionsHumansMaleMiddle AgedObservational Studies as TopicRandomized Controlled Trials as TopicResearch Design
2015
Using observational data to emulate a randomized trial of dynamic treatment-switching strategies: an application to antiretroviral therapy
Cain LE, Saag MS, Petersen M, May MT, Ingle SM, Logan R, Robins JM, Abgrall S, Shepherd BE, Deeks SG, Gill M, Touloumi G, Vourli G, Dabis F, Vandenhende MA, Reiss P, van Sighem A, Samji H, Hogg RS, Rybniker J, Sabin CA, Jose S, del Amo J, Moreno S, Rodríguez B, Cozzi-Lepri A, Boswell SL, Stephan C, Pérez-Hoyos S, Jarrin I, Guest JL, Monforte A, Antinori A, Moore R, Campbell CN, Casabona J, Meyer L, Seng R, Phillips AN, Bucher HC, Egger M, Mugavero MJ, Haubrich R, Geng EH, Olson A, Eron JJ, Napravnik S, Kitahata MM, Van Rompaey SE, Teira R, Justice AC, Tate JP, Costagliola D, Sterne JA, Hernán MA, Systems A. Using observational data to emulate a randomized trial of dynamic treatment-switching strategies: an application to antiretroviral therapy. International Journal Of Epidemiology 2015, 45: 2038-2049. PMID: 26721599, PMCID: PMC5841611, DOI: 10.1093/ije/dyv295.Peer-Reviewed Original ResearchMeSH KeywordsAdultAnti-HIV AgentsCD4 Lymphocyte CountFemaleHIV InfectionsHIV-1HumansMaleMiddle AgedObservational Studies as TopicRandomized Controlled Trials as TopicSurvival AnalysisUnited KingdomViral LoadConceptsAntiretroviral therapyCopies/Antiretroviral Therapy Cohort CollaborationTime-varying covariatesTight control groupAdjusted hazard ratioAntiretroviral therapy regimenAIDS Research NetworkIntegrated Clinical SystemsHIV-CAUSAL CollaborationDeath eventsCohort CollaborationHazard ratioTherapy regimenRandomized trialsInverse probability weightingInclusion criteriaMortality analysisClinical treatmentAIDSTherapyDeath analysisDeathTrialsComparative effects
2013
Validation of an algorithm to identify antiretroviral‐naïve status at time of entry into a large, observational cohort of HIV‐infected patients
Gandhi NR, Tate JP, Rodriguez‐Barradas M, Rimland D, Goetz MB, Gibert C, Brown ST, Mattocks K, Justice AC. Validation of an algorithm to identify antiretroviral‐naïve status at time of entry into a large, observational cohort of HIV‐infected patients. Pharmacoepidemiology And Drug Safety 2013, 22: 1019-1025. PMID: 23836591, PMCID: PMC3831617, DOI: 10.1002/pds.3476.Peer-Reviewed Original ResearchConceptsART-naïve patientsViral load thresholdMedical record reviewAntiretroviral treatmentMedical recordsHIV cohortObservational cohortRecord reviewVeterans Aging Cohort Study Virtual CohortVirtual cohortPrevious antiretroviral treatmentLaboratory dataPatients' medical recordsPositive predictive value 87Cohort entryAdverse eventsHIV outcomesRandomized trialsRetrospective studyAdverse reactionsTime of entryCopies/ART treatmentTreatment statusTreatment history