2024
Impact and cost-effectiveness of the 6-month BPaLM regimen for rifampicin-resistant tuberculosis in Moldova: A mathematical modeling analysis.
James L, Klaassen F, Sweeney S, Furin J, Franke M, Yaesoubi R, Chesov D, Ciobanu N, Codreanu A, Crudu V, Cohen T, Menzies N. Impact and cost-effectiveness of the 6-month BPaLM regimen for rifampicin-resistant tuberculosis in Moldova: A mathematical modeling analysis. PLOS Medicine 2024, 21: e1004401. PMID: 38701084, PMCID: PMC11101189, DOI: 10.1371/journal.pmed.1004401.Peer-Reviewed Original ResearchQuality-adjusted life yearsStandard of careDrug susceptibility testingRifampicin-resistant tuberculosisRR-TBEnd-of-treatmentLonger regimensTreatment strategiesTreatment outcomesBurden of drug-resistant TBCost-effective treatment strategyResistance to amikacinDrug-resistant TBSevere adverse eventsHistory of TBResistance to delamanidTB drug resistanceAnti-TB drugsLifetime costsAssociated treatment outcomesFQ-R.Average timeNatural history of TBFluoroquinolone resistanceFQ-R
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 trendDrivers and Trajectories of Resistance to New First-Line Drug Regimens for Tuberculosis
Shrestha S, Knight GM, Fofana M, Cohen T, White RG, Cobelens F, Dowdy DW. Drivers and Trajectories of Resistance to New First-Line Drug Regimens for Tuberculosis. Open Forum Infectious Diseases 2014, 1: ofu073. PMID: 25734143, PMCID: PMC4281792, DOI: 10.1093/ofid/ofu073.Peer-Reviewed Original ResearchDrug-resistant TBTreatment of tuberculosisNew drug regimenTransmission fitnessDrug regimensDrug regimenTreatment successDrug-susceptible TBAppropriate second-line therapyDR-TB prevalenceSecond-line therapyDrug resistance trendsTreatment success rateHigher treatment successNovel drug regimensEmergence of resistancePopulation-level dataTB regimensShort-term surveillanceDS-TBNew regimenClinical trialsEarly diagnosisRegimensDrug resistance
2013
Community-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 suppressionIntervention
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 epidemicLinking Surveillance with Action against Drug-Resistant Tuberculosis
Cohen T, Manjourides J, Hedt-Gauthier B. Linking Surveillance with Action against Drug-Resistant Tuberculosis. American Journal Of Respiratory And Critical Care Medicine 2012, 186: 399-401. PMID: 22592806, PMCID: PMC3443807, DOI: 10.1164/rccm.201203-0394pp.Peer-Reviewed Original ResearchConceptsMultidrug-resistant tuberculosisForms of TBDrug-resistant TBManagement of patientsDrug-resistant tuberculosisSecond-line drugsEffective public health responseDrug susceptibility testingPublic health responseQuality-assured treatmentMDRTB treatmentIncident casesHigh burdenProgrammatic dataHealth responseDrug resistanceSusceptibility testingImproved surveillance methodsPopulation subgroupsSurveillance methodsSurveillance activitiesTuberculosisClear roleTreatmentRecent global estimates
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
2010
Estimating the magnitude and direction of bias in tuberculosis drug resistance surveys conducted only in the public sector: a simulation study
Cohen T, Hedt BL, Pagano M. Estimating the magnitude and direction of bias in tuberculosis drug resistance surveys conducted only in the public sector: a simulation study. BMC Public Health 2010, 10: 355. PMID: 20565947, PMCID: PMC2898828, DOI: 10.1186/1471-2458-10-355.Peer-Reviewed Original Research
2009
Mathematical models of the epidemiology and control of drug-resistant TB
Cohen T, Dye C, Colijn C, Williams B, Murray M. Mathematical models of the epidemiology and control of drug-resistant TB. Expert Review Of Respiratory Medicine 2009, 3: 67-79. PMID: 20477283, DOI: 10.1586/17476348.3.1.67.Peer-Reviewed Original ResearchDrug-resistant TBDrug resistanceMultiple drug-resistant Mycobacterium tuberculosisDrug-resistant Mycobacterium tuberculosisDrug-resistant M. tuberculosisCombination chemotherapyTB controlM. tuberculosisMycobacterium tuberculosisAntibiotic resistanceRecent reportsTuberculosisEpidemiologyTBExtrinsic determinantsInterventionCost effectivenessReproductive capacityChemotherapyControlPrevalence
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
2006
Beneficial and perverse effects of isoniazid preventive therapy for latent tuberculosis infection in HIV–tuberculosis coinfected populations
Cohen T, Lipsitch M, Walensky RP, Murray M. Beneficial and perverse effects of isoniazid preventive therapy for latent tuberculosis infection in HIV–tuberculosis coinfected populations. Proceedings Of The National Academy Of Sciences Of The United States Of America 2006, 103: 7042-7047. PMID: 16632605, PMCID: PMC1459015, DOI: 10.1073/pnas.0600349103.Peer-Reviewed Original ResearchConceptsIsoniazid preventive therapyDrug-resistant TBCommunity-wide isoniazid preventive therapyPreventive therapyTuberculosis infectionTB controlLatent Mycobacterium tuberculosis infectionLatent tuberculosis infectionProportion of patientsMycobacterium tuberculosis infectionIncidence of TBTuberculosis case notificationCommunity-wide implementationEmergence of HIVCommunity-wide strategiesHIV-tuberculosisTB-HIVCoinfected individualsTB epidemicCase notificationTreatment policyHIVTherapyInfectionTB