2024
The recent rapid expansion of multidrug resistant Ural lineage Mycobacterium tuberculosis in Moldova
Chitwood M, Colijn C, Yang C, Crudu V, Ciobanu N, Codreanu A, Kim J, Rancu I, Rhee K, Cohen T, Sobkowiak B. The recent rapid expansion of multidrug resistant Ural lineage Mycobacterium tuberculosis in Moldova. Nature Communications 2024, 15: 2962. PMID: 38580642, PMCID: PMC10997638, DOI: 10.1038/s41467-024-47282-9.Peer-Reviewed Original ResearchConceptsMDR M. tuberculosisGenome sequenceResistance-conferring mutationsBeijing sublineageMDR strainsReproductive fitnessBeijing strainsCulture-positive casesLineagesMtb strainsMultidrug-resistant tuberculosisMDRMtbStrainMDR-TBMutationsResistant tuberculosisMDR-MTBSubstantial riskSublineagesTuberculosisSequenceIdentifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model
Lan Y, Crudu V, Ciobanu N, Codreanu A, Chitwood M, Sobkowiak B, Warren J, Cohen T. Identifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model. EBioMedicine 2024, 102: 105085. PMID: 38531172, PMCID: PMC10987885, DOI: 10.1016/j.ebiom.2024.105085.Peer-Reviewed Original ResearchConceptsPatterns of spatial aggregationMtb strainsMDR-TBLogistic regression modelsGenome Epidemiology StudySpecific strainsMultidrug-resistant tuberculosisTreated TB casesNational Institute of AllergyMDR phenotypeRegression modelsM. tuberculosisInstitute of AllergyMultinomial logistic regression modelUS National Institutes of HealthNational Institutes of HealthMDR diseasePublic health concernAssociated with local transmissionIncident TBInstitutes of HealthMtbResistant tuberculosisStrainDiagnosing TB
2022
Predicting resistance to fluoroquinolones among patients with rifampicin-resistant tuberculosis using machine learning methods
You S, Chitwood MH, Gunasekera KS, Crudu V, Codreanu A, Ciobanu N, Furin J, Cohen T, Warren JL, Yaesoubi R. Predicting resistance to fluoroquinolones among patients with rifampicin-resistant tuberculosis using machine learning methods. PLOS Digital Health 2022, 1: e0000059. PMID: 36177394, PMCID: PMC9518704, DOI: 10.1371/journal.pdig.0000059.Peer-Reviewed Original ResearchDrug susceptibility testXpert MTB/RIFMachine learning-based modelsLearning-based modelsMachine learning methodsRifampicin-resistant tuberculosisTime of diagnosisRifampin-resistant tuberculosisMTB/RIFNeural network modelLearning methodsNetwork modelMulti-drug resistant tuberculosisNational TB surveillanceDrug-resistant tuberculosisOptimism-corrected areaSelection of antibioticsAnti-TB agentsDistrict-level prevalenceLow-resource settingsPatient characteristicsResistant tuberculosisTB surveillanceAppropriate treatmentDST results
2019
Transmissibility and potential for disease progression of drug resistant Mycobacterium tuberculosis: prospective cohort study
Becerra MC, Huang CC, Lecca L, Bayona J, Contreras C, Calderon R, Yataco R, Galea J, Zhang Z, Atwood S, Cohen T, Mitnick CD, Farmer P, Murray M. Transmissibility and potential for disease progression of drug resistant Mycobacterium tuberculosis: prospective cohort study. The BMJ 2019, 367: l5894. PMID: 31649017, PMCID: PMC6812583, DOI: 10.1136/bmj.l5894.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAntitubercular AgentsChildChild, PreschoolContact TracingDisease ProgressionFemaleFollow-Up StudiesHumansIncidenceInfantInfant, NewbornIsoniazidKaplan-Meier EstimateMaleMicrobial Sensitivity TestsMiddle AgedMycobacterium tuberculosisPeruProspective StudiesRifampinSputumTuberculin TestTuberculosis, Multidrug-ResistantTuberculosis, PulmonaryYoung AdultConceptsDrug-sensitive tuberculosisMultidrug-resistant tuberculosisHousehold contactsProspective cohort studySensitive tuberculosisTuberculosis infectionResistant tuberculosisCohort studyTuberculosis diseaseHigh riskDrug-resistant Mycobacterium tuberculosisIncident tuberculosis diseasePhenotypic drug resistanceDistrict Health CenterResistant Mycobacterium tuberculosisDrug-susceptible strainsDrug resistance profilesActive diseasePulmonary tuberculosisDisease progressionGuideline producersHealth centersIndex patientsEffective treatmentPatients
2018
Trends in C-Reactive Protein, D-Dimer, and Fibrinogen during Therapy for HIV-Associated Multidrug-Resistant Tuberculosis.
Cudahy PGT, Warren JL, Cohen T, Wilson D. Trends in C-Reactive Protein, D-Dimer, and Fibrinogen during Therapy for HIV-Associated Multidrug-Resistant Tuberculosis. American Journal Of Tropical Medicine And Hygiene 2018, 99: 1336-1341. PMID: 30226135, PMCID: PMC6221241, DOI: 10.4269/ajtmh.18-0322.Peer-Reviewed Original ResearchConceptsC-reactive proteinMulti-drug resistant tuberculosisD-dimerMedian C-reactive proteinSerum C-reactive proteinHigher baseline fibrinogenMDR-TB therapyHIV-positive adultsDrug-resistant tuberculosisHIV-positive participantsHigher CRP concentrationsEarly treatment modificationBaseline fibrinogenTreatment initiationResistant tuberculosisCRP concentrationsTreatment modificationTreatment outcomesTreatment responseHigh riskHigh mortalityNormal levelsOlder ageEarly responseFibrinogen
2016
Use of Lot Quality Assurance Sampling to Ascertain Levels of Drug Resistant Tuberculosis in Western Kenya
Jezmir J, Cohen T, Zignol M, Nyakan E, Hedt-Gauthier BL, Gardner A, Kamle L, Injera W, Carter EJ. Use of Lot Quality Assurance Sampling to Ascertain Levels of Drug Resistant Tuberculosis in Western Kenya. PLOS ONE 2016, 11: e0154142. PMID: 27167381, PMCID: PMC4864281, DOI: 10.1371/journal.pone.0154142.Peer-Reviewed Original ResearchConceptsMDR-TBDrug resistanceResistant tuberculosisLot Quality Assurance Sampling methodologyMulti-drug resistant tuberculosisPositive TB patientsDrug resistance surveillanceDrug-resistant tuberculosisTB drug resistanceRural settingsPoly-resistant strainsTB patientsWestern KenyaLot Quality AssuranceLow prevalencePatientsResistance surveillancePrevalenceTuberculosisLQASSettingLow levelsDifferent geographic settingsUrban settingsLevels
2014
On the spread and control of MDR-TB epidemics: An examination of trends in anti-tuberculosis drug resistance surveillance data
Cohen T, Jenkins HE, Lu C, McLaughlin M, Floyd K, Zignol M. On the spread and control of MDR-TB epidemics: An examination of trends in anti-tuberculosis drug resistance surveillance data. Drug Resistance Updates 2014, 17: 105-123. PMID: 25458783, PMCID: PMC4358299, DOI: 10.1016/j.drup.2014.10.001.Peer-Reviewed Original ResearchConceptsMDR-TBTB casesResistant tuberculosisAbsolute burdenSurveillance dataMDR-TB epidemicDrug-resistant TBMultidrug-resistant tuberculosisDrug-resistant tuberculosisNotified TB casesResistance surveillance dataSufficient surveillance dataWorld Health OrganizationBurden settingsTuberculosis controlUnadjusted analysesSignificant linear trendSurveillance indicatorsRobust surveillance systemHealth OrganizationTuberculosisBurdenSurveillance systemSettingLinear trend
2013
Treatment outcome of multi-drug resistant tuberculosis in the United Kingdom: retrospective-prospective cohort study from 2004 to 2007.
Anderson LF, Tamne S, Watson JP, Cohen T, Mitnick C, Brown T, Drobniewski F, Abubakar I. Treatment outcome of multi-drug resistant tuberculosis in the United Kingdom: retrospective-prospective cohort study from 2004 to 2007. Eurosurveillance 2013, 18 PMID: 24128699, DOI: 10.2807/1560-7917.es2013.18.40.20601.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAntibiotics, AntitubercularAntitubercular AgentsChildChild, PreschoolDrug Resistance, Multiple, BacterialFemaleFluoroquinolonesHumansInfantInfant, NewbornMaleMicrobial Sensitivity TestsMiddle AgedMycobacterium tuberculosisPatient ComplianceProspective StudiesRetrospective StudiesSurveys and QuestionnairesTreatment OutcomeTuberculosis, Multidrug-ResistantUnited KingdomYoung AdultConceptsMultidrug-resistant tuberculosisTreatment outcomesRetrospective-prospective cohort studyWorld Health Organization targetMulti-drug resistant tuberculosisMDR-TB patientsMDR-TB treatmentMDR-TB casesFurther drug resistanceTreatment completion ratesSuccessful treatment outcomeUnited Kingdom guidelinesIndividualised regimensCohort studyMonths treatmentResistant tuberculosisTreatment completionInfectious casesDrug resistanceDrug sensitivitySuccessful outcomeOrganization targetBacteriostatic drugsOutcomesTreatmentResponse to Comment on “Community-Wide Isoniazid Preventive Therapy Drives Drug-Resistant Tuberculosis: A Model-Based Analysis”
Mills HL, Cohen T, Colijn C. Response to Comment on “Community-Wide Isoniazid Preventive Therapy Drives Drug-Resistant Tuberculosis: A Model-Based Analysis”. Science Translational Medicine 2013, 5: 204lr4. PMID: 24068734, DOI: 10.1126/scitranslmed.3007442.Peer-Reviewed Original ResearchCommunity-Wide Isoniazid Preventive Therapy Drives Drug-Resistant Tuberculosis: A Model-Based Analysis
Mills HL, Cohen T, Colijn C. Community-Wide Isoniazid Preventive Therapy Drives Drug-Resistant Tuberculosis: A Model-Based Analysis. Science Translational Medicine 2013, 5: 180ra49. PMID: 23576815, PMCID: PMC3714172, DOI: 10.1126/scitranslmed.3005260.Peer-Reviewed Original ResearchConceptsDrug-resistant TBIPT interventionDrug-sensitive infectionsIsoniazid-resistant TBHIV/TBRisk of progressionHigh HIV prevalenceDrug-resistant diseaseIsoniazid-resistant Mycobacterium tuberculosisSymptom-free individualsSignificant elevated riskDrug-resistant strainsWorld Health OrganizationActive TBTB controlResistant tuberculosisHIV prevalenceTuberculosis controlIPT programElevated riskHost immunityMycobacterium tuberculosisHealth OrganizationSelective suppressionInterventionRisk factors and timing of default from treatment for non-multidrug-resistant tuberculosis in Moldova
Jenkins HE, Ciobanu A, Plesca V, Crudu V, Galusca I, Soltan V, Cohen T. Risk factors and timing of default from treatment for non-multidrug-resistant tuberculosis in Moldova. The International Journal Of Tuberculosis And Lung Disease 2013, 17: 373-380. PMID: 23407226, PMCID: PMC3710709, DOI: 10.5588/ijtld.12.0464.Peer-Reviewed Original ResearchMeSH KeywordsAdultAntitubercular AgentsContinuity of Patient CareFemaleHumansInstitutionalizationLeast-Squares AnalysisLinear ModelsMaleMedication AdherenceMoldovaMultivariate AnalysisPatient DischargePrisonersProportional Hazards ModelsRetrospective StudiesRisk FactorsSocioeconomic FactorsTime FactorsTreatment OutcomeTuberculosisConceptsMultidrug-resistant tuberculosisMDR-TB patientsRisk factorsHighest MDR-TB ratesDrug resistanceGreater lung pathologyMDR-TB ratesAnti-tuberculosis treatmentIndependent risk factorHuman immunodeficiency virusTB drug resistanceContinuity of careRoutine surveillance dataTuberculosis patientsResistant tuberculosisImmunodeficiency virusLung pathologyTreatment adherenceRetrospective analysisHigh riskPatientsSociodemographic factorsCommunity careSurveillance dataStudy period
2012
Modeling the Dynamic Relationship Between HIV and the Risk of Drug-Resistant Tuberculosis
Sergeev R, Colijn C, Murray M, Cohen T. Modeling the Dynamic Relationship Between HIV and the Risk of Drug-Resistant Tuberculosis. Science Translational Medicine 2012, 4: 135ra67. PMID: 22623743, PMCID: PMC3387814, DOI: 10.1126/scitranslmed.3003815.Peer-Reviewed Original ResearchConceptsMultidrug-resistant TBDrug-resistant tuberculosisDrug-resistant TBHIV-seropositive individualsHIV statusTB patientsLatent Mycobacterium tuberculosis infectionIndividual HIV statusIncident HIV infectionMultidrug-resistant tuberculosisMycobacterium tuberculosis infectionEffects of HIVCross-sectional studyDrug-resistant formsRise of HIVIndividual-level associationsAcquisition of resistanceAverage CD4HIV infectionResistance-conferring mutationsTB controlTuberculosis infectionResistant tuberculosisTB drugsHIV epidemic
2011
Quantifying the Burden and Trends of Isoniazid Resistant Tuberculosis, 1994–2009
Jenkins HE, Zignol M, Cohen T. Quantifying the Burden and Trends of Isoniazid Resistant Tuberculosis, 1994–2009. PLOS ONE 2011, 6: e22927. PMID: 21829557, PMCID: PMC3146514, DOI: 10.1371/journal.pone.0022927.Peer-Reviewed Original ResearchConceptsIsoniazid preventive therapyIncident TB casesTB casesHIV prevalence countriesHigh HIV prevalence countriesPrevalence countriesHigh HIV prevalence areasRetreatment TB casesHIV prevalence areasIsoniazid-resistant tuberculosisControl of tuberculosisEffect of INHObserved time trendsWorld Health OrganizationPreventive therapyResistant tuberculosisIncident casesTreatment successPrevalence areasIsoniazid resistanceMultidrug resistanceHealth OrganizationTuberculosisINHNational data
2008
Are Survey-Based Estimates of the Burden of Drug Resistant TB Too Low? Insight from a Simulation Study
Cohen T, Colijn C, Finklea B, Wright A, Zignol M, Pym A, Murray M. Are Survey-Based Estimates of the Burden of Drug Resistant TB Too Low? Insight from a Simulation Study. PLOS ONE 2008, 3: e2363. PMID: 18523659, PMCID: PMC2408555, DOI: 10.1371/journal.pone.0002363.Peer-Reviewed Original ResearchConceptsResistant tuberculosisIncident casesTotal burdenDrug-resistant TBDrug-resistant tuberculosisSecond-line antibioticsDrug treatment regimensDrug sensitivity testingDrug-resistant strainsBurden of resistanceEmergence of tuberculosisResistant TBTreatment regimensPrevalent casesWorldwide burdenIntroduction of interventionsRoutine surveillanceSurveillance strategiesDrug resistanceTuberculosisLaboratory capacityMycobacterium tuberculosisSensitivity testingTuberculosis modelBurden