2024
Phylogeographic Analysis of Mycobacterium kansasii Isolates from Patients with M. kansasii Lung Disease in Industrialized City, Taiwan - Volume 30, Number 8—August 2024 - Emerging Infectious Diseases journal - CDC
Cudahy P, Liu P, Warren J, Sobkowiak B, Yang C, Ioerger T, Wu C, Lu P, Wang J, Chang H, Huang H, Cohen T, Lin H. Phylogeographic Analysis of Mycobacterium kansasii Isolates from Patients with M. kansasii Lung Disease in Industrialized City, Taiwan - Volume 30, Number 8—August 2024 - Emerging Infectious Diseases journal - CDC. Emerging Infectious Diseases 2024, 30: 1562-1570. PMID: 39043390, PMCID: PMC11286038, DOI: 10.3201/eid3008.240021.Peer-Reviewed Original ResearchConceptsM. kansasii lung diseaseM. kansasii pulmonary diseasePulmonary diseaseM. kansasii isolatesSputum mycobacterial cultureWhole-genome sequencingEvaluate risk factorsPhylogeographic analysisAge of participantsGenetic relatednessEnvironmental acquisitionLung diseaseMycobacterial cultureOdds ratioRisk factorsM. kansasiiPatientsDiseasePlantsEnvironmental transmissionIsolatesPark plantingsCDCRisk
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
Investigating spillover of multidrug-resistant tuberculosis from a prison: a spatial and molecular epidemiological analysis
Warren JL, Grandjean L, Moore DAJ, Lithgow A, Coronel J, Sheen P, Zelner JL, Andrews JR, Cohen T. Investigating spillover of multidrug-resistant tuberculosis from a prison: a spatial and molecular epidemiological analysis. BMC Medicine 2018, 16: 122. PMID: 30071850, PMCID: PMC6091024, DOI: 10.1186/s12916-018-1111-x.Peer-Reviewed Original Research
2017
Polyclonal Pulmonary Tuberculosis Infections and Risk for Multidrug Resistance, Lima, Peru - Volume 23, Number 11—November 2017 - Emerging Infectious Diseases journal - CDC
Nathavitharana RR, Shi CX, Chindelevitch L, Calderon R, Zhang Z, Galea JT, Contreras C, Yataco R, Lecca L, Becerra MC, Murray MB, Cohen T. Polyclonal Pulmonary Tuberculosis Infections and Risk for Multidrug Resistance, Lima, Peru - Volume 23, Number 11—November 2017 - Emerging Infectious Diseases journal - CDC. Emerging Infectious Diseases 2017, 23: 1887-1890. PMID: 29048297, PMCID: PMC5652442, DOI: 10.3201/eid2311.170077.Peer-Reviewed Original ResearchConceptsTreatment of tuberculosisHost Mycobacterium tuberculosis diversityMultidrug-resistant TBInfectious Diseases journal - CDCPulmonary TB patientsPulmonary tuberculosis infectionTB patientsTuberculosis infectionPolyclonal infectionsSimple infectionMultidrug resistanceInfectionPatientsTuberculosisPrevalenceDiagnosisCatastrophic costs potentially averted by tuberculosis control in India and South Africa: a modelling study
Verguet S, Riumallo-Herl C, Gomez GB, Menzies NA, Houben RMGJ, Sumner T, Lalli M, White RG, Salomon JA, Cohen T, Foster N, Chatterjee S, Sweeney S, Baena IG, Lönnroth K, Weil DE, Vassall A. Catastrophic costs potentially averted by tuberculosis control in India and South Africa: a modelling study. The Lancet Global Health 2017, 5: e1123-e1132. PMID: 29025634, PMCID: PMC5640802, DOI: 10.1016/s2214-109x(17)30341-8.Peer-Reviewed Original ResearchConceptsMultidrug-resistant tuberculosisEnd TB StrategyTuberculosis servicesCatastrophic costsTB StrategyDrug-sensitive tuberculosisCatastrophic financial burdenAnnual household incomeTuberculosis careTuberculosis controlEconomic burdenTuberculosisIntervention effectsMelinda Gates FoundationHousehold incomeIndirect costsFinancial burdenExpansion of accessPatientsTotal annual household incomeTreatmentCareGates FoundationBurdenIntervention scenariosPopulation implications of the use of bedaquiline in people with extensively drug-resistant tuberculosis: are fears of resistance justified?
Kunkel A, Furin J, Cohen T. Population implications of the use of bedaquiline in people with extensively drug-resistant tuberculosis: are fears of resistance justified? The Lancet Infectious Diseases 2017, 17: e429-e433. PMID: 28533094, DOI: 10.1016/s1473-3099(17)30299-2.Peer-Reviewed Original ResearchConceptsUse of bedaquilineDrug-resistant tuberculosisXDR tuberculosisBedaquiline resistanceCohort study resultsMultidrug-resistant tuberculosisNew combination regimensHigh mortality rateFears of resistanceInfected contactsCombination regimensDrug combinationsPatientsEquivalent outcomesMortality rateAntituberculosis drugsBedaquilineTuberculosisNovel drugsDrug bedaquilineDrugsDiseasePopulation implicationsResistance concernsGreat need
2016
Second line drug susceptibility testing to inform the treatment of rifampin-resistant tuberculosis: a quantitative perspective
Kendall EA, Cohen T, Mitnick CD, Dowdy DW. Second line drug susceptibility testing to inform the treatment of rifampin-resistant tuberculosis: a quantitative perspective. International Journal Of Infectious Diseases 2016, 56: 185-189. PMID: 28007660, PMCID: PMC5576040, DOI: 10.1016/j.ijid.2016.12.010.Peer-Reviewed Original ResearchConceptsSecond-line drug susceptibility testingRifampin-resistant tuberculosisDrug susceptibility testingSecond-line drug resistanceDrug resistanceSusceptibility testingHigh-burden settingsSecond-line drugsDrug-resistant tuberculosisEffective regimensTreatment failureTreatment outcomesSmall incremental costEpidemiologic benefitsResistance amplificationPatientsTuberculosisIncremental costMost settingsWidespread implementationSettingRegimensPrevalenceUse 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 settingsLevelsAssessing the utility of Xpert® MTB/RIF as a screening tool for patients admitted to medical wards in South Africa
Heidebrecht CL, Podewils LJ, Pym AS, Cohen T, Mthiyane T, Wilson D. Assessing the utility of Xpert® MTB/RIF as a screening tool for patients admitted to medical wards in South Africa. Scientific Reports 2016, 6: 19391. PMID: 26786396, PMCID: PMC4726405, DOI: 10.1038/srep19391.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overCoinfectionDrug Resistance, BacterialFemaleHIV InfectionsHumansMaleMass ScreeningMicrobial Sensitivity TestsMiddle AgedMycobacterium tuberculosisNucleic Acid Amplification TechniquesReproducibility of ResultsRifampinSouth AfricaTuberculosis, Multidrug-ResistantYoung AdultConceptsChest X-rayMTB/RIFMedical wardsScreening toolAdditional TB casesInfection control actionsUtility of GeneXpertTB/HIVConsecutive adult patientsProportion of patientsRifampicin-resistant tuberculosisDrug-resistant tuberculosisLarge public hospitalTB diseaseAdult patientsStandard careTB casesTB screeningMedical admissionsMedical chartsHospital inpatientsSputum specimensGeneXpertPatientsRifampicin resistanceWithin-Host Heterogeneity of Mycobacterium tuberculosis Infection Is Associated With Poor Early Treatment Response: A Prospective Cohort Study
Cohen T, Chindelevitch L, Misra R, Kempner ME, Galea J, Moodley P, Wilson D. Within-Host Heterogeneity of Mycobacterium tuberculosis Infection Is Associated With Poor Early Treatment Response: A Prospective Cohort Study. The Journal Of Infectious Diseases 2016, 213: 1796-1799. PMID: 26768249, PMCID: PMC4857469, DOI: 10.1093/infdis/jiw014.Peer-Reviewed Original ResearchConceptsMonths of treatmentMycobacterium tuberculosis infectionTuberculosis infectionTreatment responsePoor early treatment responseProspective cohort studyInitiation of treatmentM. tuberculosis infectionRepetitive units-variable numberEarly treatment responsePersistent culture positivityCohort studyClinical managementCulture positivityHigher oddsInfectionTuberculosisPrevalenceTreatmentMonthsResponsePatientsKwaZulu-NatalHost heterogeneityPositivity
2014
Magnitude and sources of bias in the detection of mixed strain M. tuberculosis infection
Plazzotta G, Cohen T, Colijn C. Magnitude and sources of bias in the detection of mixed strain M. tuberculosis infection. Journal Of Theoretical Biology 2014, 368: 67-73. PMID: 25553967, PMCID: PMC7011203, DOI: 10.1016/j.jtbi.2014.12.009.Peer-Reviewed Original ResearchConceptsMixed infectionsM. tuberculosis infectionIncidence of TBOutcome of treatmentPopulation-level interventionsFraction of casesTuberculosis infectionMinority strainsActual prevalenceInfected individualsInfectionStudy designMycobacterium tuberculosisPrevalenceSputumTuberculosisDistinct strainsDifferent strainsSources of biasPrevious studiesPatientsSpecific reasonsIncidenceIndividualsCigarette smoking among tuberculosis patients increases risk of transmission to child contacts
Huang CC, Tchetgen ET, Becerra MC, Cohen T, Galea J, Calderon R, Yataco R, Contreras C, Zhang ZB, Lecca L, Murray M. Cigarette smoking among tuberculosis patients increases risk of transmission to child contacts. The International Journal Of Tuberculosis And Lung Disease 2014, 18: 1285-1291. PMID: 25299859, DOI: 10.5588/ijtld.14.0309.Peer-Reviewed Original ResearchConceptsLatent tuberculous infectionTuberculin skin testTB patientsIndex caseChild household contactsDrug-susceptible TBIndex TB patientsObservational cohort studySecondhand smoke exposureRisk of transmissionPoisson regression modelsHousehold contactsCohort studyTST positivityTuberculosis patientsTuberculous infectionSmoke exposureSmoking statusTuberculosis casesCigarette smokingSkin testRisk factorsPatientsInfection statusTime points
2013
The Effect of HIV-Related Immunosuppression on the Risk of Tuberculosis Transmission to Household Contacts
Huang CC, Tchetgen ET, Becerra MC, Cohen T, Hughes KC, Zhang Z, Calderon R, Yataco R, Contreras C, Galea J, Lecca L, Murray M. The Effect of HIV-Related Immunosuppression on the Risk of Tuberculosis Transmission to Household Contacts. Clinical Infectious Diseases 2013, 58: 765-774. PMID: 24368620, PMCID: PMC3935504, DOI: 10.1093/cid/cit948.Peer-Reviewed Original ResearchConceptsHuman immunodeficiency virusHousehold contactsIndex patientsCD4 countTuberculosis patientsTuberculosis transmissionHIV-negative tuberculosis patientsHIV-negative patientsHIV-positive patientsDrug-sensitive tuberculosisTuberculin skin testingTuberculosis infection statusRisk of infectionCoinfected PatientsActive tuberculosisTuberculosis infectionHIV statusSkin testingImmunodeficiency virusRisk factorsRelative riskPatientsTuberculosisInfection statusInfectionBayesian Estimation of Mixture Models with Prespecified Elements to Compare Drug Resistance in Treatment-Naïve and Experienced Tuberculosis Cases
Izu A, Cohen T, DeGruttola V. Bayesian Estimation of Mixture Models with Prespecified Elements to Compare Drug Resistance in Treatment-Naïve and Experienced Tuberculosis Cases. PLOS Computational Biology 2013, 9: e1002973. PMID: 23555210, PMCID: PMC3605089, DOI: 10.1371/journal.pcbi.1002973.Peer-Reviewed Original ResearchConceptsTreatment-experienced patientsDrug-resistant strainsMultiple drug-resistant strainsTreatment-naïve patientsDrug-resistant tuberculosisMycobacterium tuberculosis isolatesWorld Health OrganizationDrug resistance pathwaysTreatment-naïveTuberculosis casesTuberculosis isolatesWorldwide surveillanceDrug resistancePatientsHealth OrganizationResistant strainsResistant pathogensResistance pathwaysLow transmissibilityPathwayTuberculosisRisk 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
Assessing spatial heterogeneity of multidrug-resistant tuberculosis in a high-burden country
Jenkins HE, Plesca V, Ciobanu A, Crudu V, Galusca I, Soltan V, Serbulenco A, Zignol M, Dadu A, Dara M, Cohen T. Assessing spatial heterogeneity of multidrug-resistant tuberculosis in a high-burden country. European Respiratory Journal 2012, 42: 1291-1301. PMID: 23100496, PMCID: PMC3800490, DOI: 10.1183/09031936.00111812.Peer-Reviewed Original ResearchConceptsMultidrug-resistant tuberculosisMDR-TB riskMDR-TB risk factorsNational TB surveillance dataMDR-TB incidenceTB surveillance dataMDR-TB casesHigh-burden countriesMDR-TB burdenDistribution of casesTB casesTuberculosis casesRisk of resistanceRisk factorsGreater riskSubstantial geographical variationSurveillance dataAppropriate targetingTesting coverageRiskTuberculosisBurdenHigh percentageLocal mechanismsPatientsMixed-Strain Mycobacterium tuberculosis Infections and the Implications for Tuberculosis Treatment and Control
Cohen T, van Helden PD, Wilson D, Colijn C, McLaughlin MM, Abubakar I, Warren RM. Mixed-Strain Mycobacterium tuberculosis Infections and the Implications for Tuberculosis Treatment and Control. Clinical Microbiology Reviews 2012, 25: 708-719. PMID: 23034327, PMCID: PMC3485752, DOI: 10.1128/cmr.00021-12.Peer-Reviewed Original ResearchConceptsMixed infectionsTuberculosis infectionM. tuberculosis infectionTuberculosis control strategiesMycobacterium tuberculosis infectionTreatment of patientsMultiple distinct strainsTuberculosis treatmentInfectionMycobacterium tuberculosisEpidemiological importanceDistinct strainsTreatmentNumerous studiesPatientsTuberculosisDiagnosisHighlight challengesIndividualsUse of Spatial Information to Predict Multidrug Resistance in Tuberculosis Patients, Peru - Volume 18, Number 5—May 2012 - Emerging Infectious Diseases journal - CDC
Lin HH, Shin SS, Contreras C, Asencios L, Paciorek CJ, Cohen T. Use of Spatial Information to Predict Multidrug Resistance in Tuberculosis Patients, Peru - Volume 18, Number 5—May 2012 - Emerging Infectious Diseases journal - CDC. Emerging Infectious Diseases 2012, 18: 811-813. PMID: 22516236, PMCID: PMC3358052, DOI: 10.3201/eid1805.111467.Peer-Reviewed Original ResearchOutcomes among tuberculosis patients with isoniazid resistance in Georgia, 2007-2009.
Gegia M, Cohen T, Kalandadze I, Vashakidze L, Furin J. Outcomes among tuberculosis patients with isoniazid resistance in Georgia, 2007-2009. The International Journal Of Tuberculosis And Lung Disease 2012, 16: 812-6. PMID: 22507372, PMCID: PMC3786434, DOI: 10.5588/ijtld.11.0637.Peer-Reviewed Original ResearchMeSH KeywordsAdultAntitubercular AgentsChi-Square DistributionDrug Resistance, BacterialDrug Therapy, CombinationEthambutolFemaleGeorgia (Republic)HumansIsoniazidLogistic ModelsMaleMicrobial Sensitivity TestsMiddle AgedMultivariate AnalysisMycobacterium tuberculosisPredictive Value of TestsPyrazinamideRetrospective StudiesRifampinRisk AssessmentRisk FactorsSputumTime FactorsTreatment OutcomeTuberculosisConceptsPulmonary tuberculosisPrevious treatmentOutcomes of patientsPulmonary TB patientsSubset of patientsRetrospective record reviewForms of tuberculosisFirst-line drugsHigh TB ratesDrug-resistant formsLower ratesLow tuberculosisTB patientsTuberculosis patientsOptimal management strategyTreatment regimenRecord reviewTB ratesTreatment successTreatment outcomesCountry of GeorgiaPatientsIsoniazid resistanceTuberculosisDrug resistance
2011
Bayesian methods for fitting mixture models that characterize branching tree processes: An application to development of resistant TB strains
Izu A, Cohen T, Mitnick C, Murray M, De Gruttola V. Bayesian methods for fitting mixture models that characterize branching tree processes: An application to development of resistant TB strains. Statistics In Medicine 2011, 30: 2708-2720. PMID: 21717491, PMCID: PMC3219798, DOI: 10.1002/sim.4287.Peer-Reviewed Original ResearchConceptsCharacterization of uncertaintyBayesian approachBayesian methodsBranching tree modelStatistical methodsMixture modelBranching treeNatural wayPrior informationDrug resistance-conferring mutationsSuch cross-sectional dataDrug-resistant TBResistant TB strainsCombination of antibioticsDrug resistance mutationsMeasurement errorResistance-conferring mutationsTB strainsSingle patientTreatment policyPatientsMultiple drugsDiagnostic specimensCross-sectional dataGenetic mutations