2022
Predicting counterfactual risks under hypothetical treatment strategies: an application to HIV
Dickerman BA, Dahabreh IJ, Cantos KV, Logan RW, Lodi S, Rentsch CT, Justice AC, Hernán MA. Predicting counterfactual risks under hypothetical treatment strategies: an application to HIV. European Journal Of Epidemiology 2022, 37: 367-376. PMID: 35190946, PMCID: PMC9189026, DOI: 10.1007/s10654-022-00855-8.Peer-Reviewed Original Research
2019
Emulating a trial of joint dynamic strategies: An application to monitoring and treatment of HIV‐positive individuals
Caniglia EC, Robins JM, Cain LE, Sabin C, Logan R, Abgrall S, Mugavero MJ, Hernández‐Díaz S, Meyer L, Seng R, Drozd DR, Seage G, Bonnet F, Le Marec F, Moore RD, Reiss P, Sighem A, Mathews WC, Jarrín I, Alejos B, Deeks SG, Muga R, Boswell SL, Ferrer E, Eron JJ, Gill J, Pacheco A, Grinsztejn B, Napravnik S, Jose S, Phillips A, Justice A, Tate J, Bucher HC, Egger M, Furrer H, Miro JM, Casabona J, Porter K, Touloumi G, Crane H, Costagliola D, Saag M, Hernán MA. Emulating a trial of joint dynamic strategies: An application to monitoring and treatment of HIV‐positive individuals. Statistics In Medicine 2019, 38: 2428-2446. PMID: 30883859, PMCID: PMC6499640, DOI: 10.1002/sim.8120.Peer-Reviewed Original ResearchConceptsHIV-positive individualsCopies/First-line treatment regimenAIDS Research NetworkAIDS-free survivalCells/Integrated Clinical SystemsHIV-CAUSAL CollaborationOutcomes of interestRisk difference estimatesDirect effectAntiretroviral therapyHIV RNACD4 thresholdTreatment regimenNew regimenTreatment strategiesHIV researchTarget trialsRegimenTherapyResearch NetworkTrialsSurvivalClinical systems
2016
What are the Patterns Between Depression, Smoking, Unhealthy Alcohol Use, and Other Substance Use Among Individuals Receiving Medical Care? A Longitudinal Study of 5479 Participants
Ruggles KV, Fang Y, Tate J, Mentor SM, Bryant KJ, Fiellin DA, Justice AC, Braithwaite RS. What are the Patterns Between Depression, Smoking, Unhealthy Alcohol Use, and Other Substance Use Among Individuals Receiving Medical Care? A Longitudinal Study of 5479 Participants. AIDS And Behavior 2016, 21: 2014-2022. PMID: 27475945, PMCID: PMC5542002, DOI: 10.1007/s10461-016-1492-9.Peer-Reviewed Original ResearchConceptsUnhealthy alcohol useVeterans Aging Cohort StudyAlcohol useSubstance useTreatment strategiesIntegrated screeningCurrent depressionMedical careHIV-negative subgroupsAging Cohort StudyPatterns of depressionCohort studyCurrent smokingOpioid useNegative subgroupSmokingDepressionLongitudinal studyHIVMarijuana useSubgroupsCareCurrent useScreeningStatus
2004
Predictors of trend in CD4-positive T-cell count and mortality among HIV-1-infected individuals with virological failure to all three antiretroviral-drug classes
Ledergerber B, Lundgren JD, Walker AS, Sabin C, Justice A, Reiss P, Mussini C, Wit F, d'Arminio Monforte A, Weber R, Fusco G, Staszewski S, Law M, Hogg R, Lampe F, Gill MJ, Castelli F, Phillips AN. Predictors of trend in CD4-positive T-cell count and mortality among HIV-1-infected individuals with virological failure to all three antiretroviral-drug classes. The Lancet 2004, 364: 51-62. PMID: 15234856, DOI: 10.1016/s0140-6736(04)16589-6.Peer-Reviewed Original ResearchConceptsProportional hazards modelVirological failureCD4 cell count slopesHIV-1 RNA concentrationsCox proportional hazards modelCD4 cell countPredictors of deathAntiretroviral therapyHIV cohortDual therapyClinical outcomesViral loadHIV replicationDrug classesTreatment strategiesTreatment informationPatientsDemographic characteristicsRNA concentrationRegression analysisTherapyFailureCohort