2021
Change in Alcohol Use Based on Self-Report and a Quantitative Biomarker, Phosphatidylethanol, in People With HIV
McGinnis KA, Tate JP, Bryant KJ, Justice AC, O’Connor P, Rodriguez-Barradas MC, Crystal S, Cutter CJ, Hansen NB, Maisto SA, Marconi VC, Williams EC, Cook RL, Gordon AJ, Gordon KS, Eyawo O, Edelman EJ, Fiellin DA. Change in Alcohol Use Based on Self-Report and a Quantitative Biomarker, Phosphatidylethanol, in People With HIV. AIDS And Behavior 2021, 26: 786-794. PMID: 34542779, DOI: 10.1007/s10461-021-03438-y.Peer-Reviewed Original ResearchMeSH KeywordsAlcohol DrinkingBiomarkersGlycerophospholipidsHIV InfectionsHumansMaleMiddle AgedSelf Report
2020
Validating Self‐Reported Unhealthy Alcohol Use With Phosphatidylethanol (PEth) Among Patients With HIV
Eyawo O, Deng Y, Dziura J, Justice AC, McGinnis K, Tate JP, Rodriguez‐Barradas M, Hansen NB, Maisto SA, Marconi VC, O’Connor P, Bryant K, Fiellin DA, Edelman EJ. Validating Self‐Reported Unhealthy Alcohol Use With Phosphatidylethanol (PEth) Among Patients With HIV. Alcohol Clinical And Experimental Research 2020, 44: 2053-2063. PMID: 33460225, PMCID: PMC8856627, DOI: 10.1111/acer.14435.Peer-Reviewed Original ResearchConceptsUnhealthy alcohol useSignificant alcohol useHeavy drinking daysAlcohol use disorderTimeline FollowbackAlcohol useSelf-reported alcohol useNumber of drinksClinical trialsRisk drinkingUse disordersDrinking daysBiomarker-based evidenceSample of PWHDrinks/dayMean numberSelf-reported alcohol consumptionMagnitude of associationBlood spot samplesLiver diseasePEth levelsTLFB interviewAlcohol consumptionLogistic regressionPatientsDNA methylation signature on phosphatidylethanol, not on self-reported alcohol consumption, predicts hazardous alcohol consumption in two distinct populations
Liang X, Justice AC, So-Armah K, Krystal JH, Sinha R, Xu K. DNA methylation signature on phosphatidylethanol, not on self-reported alcohol consumption, predicts hazardous alcohol consumption in two distinct populations. Molecular Psychiatry 2020, 26: 2238-2253. PMID: 32034291, PMCID: PMC8440221, DOI: 10.1038/s41380-020-0668-x.Peer-Reviewed Original ResearchConceptsHazardous alcohol drinkingSelf-reported alcohol consumptionAlcohol consumptionCohort 2Cohort 1Epigenome-wide association studiesSelf-reported dataHazardous alcohol consumptionAlcohol use disorderDNAm signaturesObjective measuresAlcohol drinkingClinical assessmentUse disordersRobust biomarkersDNA methylation signaturesValidation setDistinct populationsCharacteristic curvePEthEpigenetic biomarkersMethylation signatures
2019
Differentiating Types of Self-Reported Alcohol Abstinence
Gordon KS, McGinnis K, Dao C, Rentsch CT, Small A, Smith RV, Kember RL, Gelernter J, Kranzler HR, Bryant KJ, Tate JP, Justice AC. Differentiating Types of Self-Reported Alcohol Abstinence. AIDS And Behavior 2019, 24: 655-665. PMID: 31435887, PMCID: PMC6994373, DOI: 10.1007/s10461-019-02638-x.Peer-Reviewed Original ResearchConceptsLifetime abstainersSelf-reported alcohol abstinenceAlcohol biomarkersGenetic polymorphismsLogistic regression modelsHepatitis CAlcohol abstinenceUninfected individualsCharacteristics of peopleAlcohol useAbstinenceHealth effectsSmokingAbstainersBiomarkersRegression modelsOddsAssociationPLWHPolymorphismHIVCocaineMeasuring Exposure to Incarceration Using the Electronic Health Record
Wang EA, Long JB, McGinnis KA, Wang KH, Wildeman CJ, Kim C, Bucklen KB, Fiellin DA, Bates J, Brandt C, Justice AC. Measuring Exposure to Incarceration Using the Electronic Health Record. Medical Care 2019, 57: s157-s163. PMID: 31095055, PMCID: PMC8352066, DOI: 10.1097/mlr.0000000000001049.Peer-Reviewed Original ResearchMeSH KeywordsAdministrative Claims, HealthcareAdultCohort StudiesElectronic Health RecordsEthnicityFemaleHumansInformation Storage and RetrievalMaleMedicareMiddle AgedNatural Language ProcessingPrisonersSelf ReportSensitivity and SpecificityUnited StatesUnited States Department of Veterans AffairsVeteransConceptsVeterans Aging Cohort StudyElectronic health recordsHuman immunodeficiency virus-infected patientsVHA electronic health recordsNational observational cohortVirus-infected patientsHealth recordsAging Cohort StudyEHR dataHealth care disparitiesAdministrative dataRace/ethnicityIncarceration exposureObservational cohortUninfected patientsCohort studySpecificity 99.3DATA SOURCESCare disparitiesSpecificity 100Specificity 98.9Social determinantsMedicaid ServicesSpecificity 95.9Health information
2018
Using DNA methylation to validate an electronic medical record phenotype for smoking
McGinnis KA, Justice AC, Tate JP, Kranzler HR, Tindle HA, Becker WC, Concato J, Gelernter J, Li B, Zhang X, Zhao H, Crothers K, Xu K, Group F. Using DNA methylation to validate an electronic medical record phenotype for smoking. Addiction Biology 2018, 24: 1056-1065. PMID: 30284751, PMCID: PMC6541538, DOI: 10.1111/adb.12670.Peer-Reviewed Original ResearchConceptsVeterans Aging Cohort StudyAging Cohort StudyStrong associationDNA methylation sitesSmoking metricsCohort studyCurrent smokingSmoking statusSpearman correlation coefficientBiomarker cohortBlood samplesSmoking behaviorCriterion standardLogistic regressionSmokingSmoking phenotypesCurve analysisGroup assignmentText notesAssociationDescriptive statisticsPhenotypeCorrelation coefficientGenetic discoveriesPercentAlcohol and Mortality
Eyawo O, McGinnis KA, Justice AC, Fiellin DA, Hahn JA, Williams EC, Gordon AJ, Marshall BDL, Kraemer KL, Crystal S, Gaither JR, Edelman EJ, Bryant KJ, Tate JP. Alcohol and Mortality. JAIDS Journal Of Acquired Immune Deficiency Syndromes 2018, 77: 135-143. PMID: 29112041, PMCID: PMC5762259, DOI: 10.1097/qai.0000000000001588.Peer-Reviewed Original ResearchConceptsHepatitis C virusAlcohol exposureAlcohol useDirect biomarkerVeterans Aging Cohort Study Biomarker CohortBlood collection dateRecent alcohol exposureHIV viral suppressionUnhealthy alcohol useRelationship of alcoholAUDIT-C scoresViral suppressionC virusHigh riskRisk of harmHIVClinical settingMortalityPEthExposureBiomarkersRiskImproved detectionAuditIndividuals
2013
Agreement Between Electronic Medical Record-based and Self-administered Pain Numeric Rating Scale
Goulet JL, Brandt C, Crystal S, Fiellin DA, Gibert C, Gordon AJ, Kerns RD, Maisto S, Justice AC. Agreement Between Electronic Medical Record-based and Self-administered Pain Numeric Rating Scale. Medical Care 2013, 51: 245-250. PMID: 23222528, PMCID: PMC3572341, DOI: 10.1097/mlr.0b013e318277f1ad.Peer-Reviewed Original ResearchConceptsNumeric rating scaleElectronic medical recordsPain screeningMedical recordsPain numeric rating scaleRating ScaleModerate-severe painVeterans Affairs medical facilitiesPatients' electronic medical recordsMajor depressive disorderEMR dataQuality of careUnderestimation of painSample of veteransPosttraumatic stress disorderHealth care systemClinical characteristicsPatient characteristicsNRS scoresPain careDepressive disorderSurvey scoresPainLevel of agreementStress disorder
2011
Validating Smoking Data From the Veteran’s Affairs Health Factors Dataset, an Electronic Data Source
McGinnis KA, Brandt CA, Skanderson M, Justice AC, Shahrir S, Butt AA, Brown ST, Freiberg MS, Gibert CL, Goetz MB, Kim JW, Pisani MA, Rimland D, Rodriguez-Barradas MC, Sico JJ, Tindle HA, Crothers K. Validating Smoking Data From the Veteran’s Affairs Health Factors Dataset, an Electronic Data Source. Nicotine & Tobacco Research 2011, 13: 1233-1239. PMID: 21911825, PMCID: PMC3223583, DOI: 10.1093/ntr/ntr206.Peer-Reviewed Original ResearchConceptsSmoking statusHealth factorsSmoking dataKappa statisticsSmoking variablesVeterans Aging Cohort StudyAging Cohort StudySelf-reported smoking dataCohort studyCurrent smokersSmoking interventionsVirtual cohortElectronic data sourcesEMR dataFuture studiesStatusParticipantsFactorsHIVSmokersSmokingStudy surveyCohortNonmedical use of prescription opioids and pain in veterans with and without HIV
Barry DT, Goulet JL, Kerns RK, Becker WC, Gordon AJ, Justice AC, Fiellin DA. Nonmedical use of prescription opioids and pain in veterans with and without HIV. Pain 2011, 152: 1133-1138. PMID: 21354703, PMCID: PMC3086805, DOI: 10.1016/j.pain.2011.01.038.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAnalgesics, OpioidChi-Square DistributionCohort StudiesFemaleHealth SurveysHIV InfectionsHumansLogistic ModelsMaleMental DisordersMiddle AgedOdds RatioOpioid-Related DisordersPainPain MeasurementPrescriptionsPsychiatric Status Rating ScalesRetrospective StudiesSelf ReportSurveys and QuestionnairesVeterans HealthYoung AdultConceptsHuman immunodeficiency virusPrescription opioidsComponent summaryHIV statusPain interferenceUse disordersForm Health Survey Mental Component SummarySF-12 Physical Component SummaryVeterans Aging Cohort StudyNonmedical usePharmacy record dataAlcohol Use Disorders Identification Test (AUDIT) scoresAging Cohort StudyPhysical component summaryMental component summaryOpioid use disorderMedian participant ageDrug use disordersLegitimate medical reasonsPast-month cigarette useChi-squared testU.S. military veteransHepatitis COpioid prescriptionsCohort study