2018
Model-Based and Model-Free Techniques for Amyotrophic Lateral Sclerosis Diagnostic Prediction and Patient Clustering
Tang M, Gao C, Goutman S, Kalinin A, Mukherjee B, Guan Y, Dinov I. Model-Based and Model-Free Techniques for Amyotrophic Lateral Sclerosis Diagnostic Prediction and Patient Clustering. Neuroinformatics 2018, 17: 407-421. PMID: 30460455, PMCID: PMC6527505, DOI: 10.1007/s12021-018-9406-9.Peer-Reviewed Original ResearchConceptsAmyotrophic Lateral Sclerosis Functional Rating ScaleClusters of participantsModel-basedAmyotrophic lateral sclerosisRating ScaleComputable phenotypeFunctional Rating ScaleSets of featuresUnsupervised clusteringUnsupervised machine learning methodsClinical decision supportMachine learning methodsTemporal and geographic variation in the systemic treatment of advanced prostate cancer
Caram M, Estes J, Griggs J, Lin P, Mukherjee B. Temporal and geographic variation in the systemic treatment of advanced prostate cancer. BMC Cancer 2018, 18: 258. PMID: 29510667, PMCID: PMC5840834, DOI: 10.1186/s12885-018-4166-3.Peer-Reviewed Original ResearchConceptsMetastatic castration-resistant prostate cancerCastration-resistant prostate cancerFirst-line therapyProstate cancerSystemic treatmentFirst-lineSystemic treatment of advanced prostate cancerTreatment of metastatic castration-resistant prostate cancerTreatment of advanced prostate cancerResultsOur final analysisAdvanced prostate cancerFirst line therapyFood and Drug AdministrationNational insurance providerLine therapySequence of treatmentTreatment patternsDisease courseStudy cohortPrescription ratesPrescribed drugsDrug AdministrationIncreased survivalCancerTherapy
2016
Microsatellite Alterations With Allelic Loss at 9p24.2 Signify Less-Aggressive Colorectal Cancer Metastasis
Koi M, Garcia M, Choi C, Kim H, Koike J, Hemmi H, Nagasaka T, Okugawa Y, Toiyama Y, Kitajima T, Imaoka H, Kusunoki M, Chen Y, Mukherjee B, Boland C, Carethers J. Microsatellite Alterations With Allelic Loss at 9p24.2 Signify Less-Aggressive Colorectal Cancer Metastasis. Gastroenterology 2016, 150: 944-955. PMID: 26752111, PMCID: PMC4808397, DOI: 10.1053/j.gastro.2015.12.032.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkers, TumorChi-Square DistributionChromosome AberrationsChromosomes, Human, Pair 9Colorectal NeoplasmsDisease ProgressionDisease-Free SurvivalFemaleGenetic Predisposition to DiseaseHumansJapanKaplan-Meier EstimateLiver NeoplasmsLogistic ModelsLoss of HeterozygosityMaleMicrosatellite RepeatsMiddle AgedNeoplasm Recurrence, LocalNeoplasm StagingOdds RatioPhenotypeProportional Hazards ModelsProto-Oncogene Proteins B-rafProto-Oncogene Proteins p21(ras)Republic of KoreaRisk FactorsTime FactorsTreatment OutcomeConceptsPrimary colorectal tumorsLoss of heterozygosityLiver metastasesColorectal cancerColorectal tumorsElevated microsatellite alterationsMicrosatellite alterationsStage IICurative treatment of patientsStage III colorectal cancerOverall survival of patientsSurvival of patientsIII colorectal cancerTumor to liverColorectal cancer recurrenceTreatment of patientsMatched liver metastasesCancer cell nucleiMatched metastasesDisease recurrenceOverall survivalPrognostic factorsAllelic lossNo significant differenceCurative treatment
2013
Transcriptome Profiling Identifies HMGA2 as a Biomarker of Melanoma Progression and Prognosis
Raskin L, Fullen D, Giordano T, Thomas D, Frohm M, B. K, Ahn J, Mukherjee B, Johnson T, Gruber S. Transcriptome Profiling Identifies HMGA2 as a Biomarker of Melanoma Progression and Prognosis. Journal Of Investigative Dermatology 2013, 133: 2585-2592. PMID: 23633021, PMCID: PMC4267221, DOI: 10.1038/jid.2013.197.Peer-Reviewed Original ResearchConceptsAmerican Joint Committee on CancerOverall survivalTissue microarrayPrimary melanomaMelanoma pathogenesisMelanoma progressionAssociated with disease-free survivalAnalysis of tissue microarraysMetastases-free survivalDisease-free survivalHMGA2 overexpressionCox proportional hazards regression modelsLog-rank testPredictors of survivalProportional hazards regression modelsHazards regression modelsBRAF/NRAS mutationsPrimary tumorPrognostic featuresMelanoma metastasesClinicopathological characteristicsReal-time PCRGenetic alterationsAQUA analysisMelanoma development
2007
Analysis of matched case–control data with multiple ordered disease states: possible choices and comparisons
Mukherjee B, Liu I, Sinha S. Analysis of matched case–control data with multiple ordered disease states: possible choices and comparisons. Statistics In Medicine 2007, 26: 3240-3257. PMID: 17206600, DOI: 10.1002/sim.2790.Peer-Reviewed Original ResearchConceptsConditional logistic regressionStratum-specific nuisance parametersCase-control dataAdjacent-category logit modelCase-control studyOrdered categorical dataConditional-likelihood approachLikelihood-based approachNuisance parametersProportional-odds modelCumulative logitsSimulation studyAnalyse such dataMantel-Haenszel approachCumulative logit modelNatural orderPotential risk factorsStages of cancerReference categoryCategorical dataLogistic regressionOrdinal natureEffect of potential risk factorsLow birthweightRisk factors