2024
Association between psoriasis and obsessive-compulsive disorder: a case-control study in the All of Us research program
Craver A, Chen G, Fan R, Levey D, Cohen J. Association between psoriasis and obsessive-compulsive disorder: a case-control study in the All of Us research program. Archives Of Dermatological Research 2024, 316: 280. PMID: 38796663, DOI: 10.1007/s00403-024-03112-y.Peer-Reviewed Original Research
2023
Psoriasis associated with asthma and allergic rhinitis: a US-based cross-sectional study using the All of US Research Program
Joel M, Fan R, Damsky W, Cohen J. Psoriasis associated with asthma and allergic rhinitis: a US-based cross-sectional study using the All of US Research Program. Archives Of Dermatological Research 2023, 315: 1823-1826. PMID: 36707438, DOI: 10.1007/s00403-023-02539-z.Peer-Reviewed Original ResearchConceptsAllergic rhinitisUS adultsUs Research ProgramCommon chronic inflammatory diseaseMultivariable logistic regression modelNationwide longitudinal cohortImmunopathogenesis of psoriasisBody mass indexChronic inflammatory diseaseCases of asthmaCross-sectional studyLogistic regression modelsMultivariable analysisSmoking statusMass indexInflammatory pathwaysSubgroup analysisInflammatory diseasesLongitudinal cohortHigh prevalenceAsthmaPsoriasisPotential associationDiverse cohortSociodemographic variables
2022
Lichen planus is associated with depression and anxiety: a cross-sectional study in the All of Us research program
Hong S, Fan R, Cohen J. Lichen planus is associated with depression and anxiety: a cross-sectional study in the All of Us research program. Archives Of Dermatological Research 2022, 315: 1417-1419. PMID: 36401617, DOI: 10.1007/s00403-022-02459-4.Peer-Reviewed Original ResearchConceptsLichen planusCross-sectional studyAssociation of LPCross-sectional population studyType II diabetes mellitusHepatitis C infectionMultivariable logistic regressionPrevalence of depressionElectronic health record dataHealth record dataNeeds of patientsMental health outcomesC infectionDiabetes mellitusFemale predominanceMultivariable analysisHealth cohortPsychiatric comorbidityAutoimmune diseasesCardiovascular diseaseInternational ClassificationAverage ageResearch DatabaseHealth outcomesUs Research ProgramThe Genomic and Phenotypic Landscape of Ichthyosis
Sun Q, Burgren NM, Cheraghlou S, Paller AS, Larralde M, Bercovitch L, Levinsohn J, Ren I, Hu RH, Zhou J, Zaki T, Fan R, Tian C, Saraceni C, Nelson-Williams CJ, Loring E, Craiglow BG, Milstone LM, Lifton RP, Boyden LM, Choate KA. The Genomic and Phenotypic Landscape of Ichthyosis. JAMA Dermatology 2022, 158: 16-25. PMID: 34851365, PMCID: PMC8637393, DOI: 10.1001/jamadermatol.2021.4242.Peer-Reviewed Original ResearchConceptsClinical manifestationsPathogenic variantsCohort studySkin painEye problemsPhenotypic spectrumGenotype-phenotype associationsSkin odorClear genotype-phenotype associationsFisher's exact testGenetic diagnosisPatient advocacy groupsNovel disease-associated variantsReferral centerDisease-associated variantsClinical assessmentSkin infectionsClinical photographsMAIN OUTCOMEExact testHearing problemsHeterogeneous disorderScaly skinBlood DNACommon genotype
2019
Clinical Implications of Plasma-Based Genotyping With the Delivery of Personalized Therapy in Metastatic Non–Small Cell Lung Cancer
Aggarwal C, Thompson J, Black T, Katz S, Fan R, Yee S, Chien A, Evans T, Bauml J, Alley E, Ciunci C, Berman A, Cohen R, Lieberman D, Majmundar K, Savitch S, Morrissette J, Hwang W, Elenitoba-Johnson K, Langer C, Carpenter E. Clinical Implications of Plasma-Based Genotyping With the Delivery of Personalized Therapy in Metastatic Non–Small Cell Lung Cancer. JAMA Oncology 2019, 5: 173-180. PMID: 30325992, PMCID: PMC6396811, DOI: 10.1001/jamaoncol.2018.4305.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiomarkers, TumorCarcinoma, Non-Small-Cell LungClinical Decision-MakingDNA Mutational AnalysisFemaleGenetic Predisposition to DiseaseHumansLung NeoplasmsMaleMiddle AgedMutationPatient SelectionPhenotypePrecision MedicinePredictive Value of TestsPrognosisProspective StudiesConceptsNon-small cell lung cancerTissue next-generation sequencingMetastatic non-small cell lung cancerCell lung cancerTargetable mutationsNext-generation sequencingLung cancerPlasma testingStage IV non-small cell lung cancerAllele fractionNGS testingClinical implicationsPlasma next-generation sequencingPersonalized therapyReal-world clinical settingProspective cohort studyResponse Evaluation CriteriaRoutine clinical managementNumber of patientsSolid Tumors responseDNA next-generation sequencingStable diseaseMutation allele fractionCohort studyPartial response
2018
Measurement and immunophenotyping of pleural fluid EpCAM-positive cells and clusters for the management of non-small cell lung cancer patients
Thompson J, Fan R, Black T, Yu G, Savitch S, Chien A, Yee S, Sen M, Hwang W, Katz S, Feldman M, Vachani A, Carpenter E. Measurement and immunophenotyping of pleural fluid EpCAM-positive cells and clusters for the management of non-small cell lung cancer patients. Lung Cancer 2018, 127: 25-33. PMID: 30642547, PMCID: PMC6657687, DOI: 10.1016/j.lungcan.2018.11.020.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerMalignant pleural effusionPleural fluid samplesEpCAM-positive cellsPD-L1 expressionNSCLC patientsOverall survivalPrognostic informationNon-small cell lung cancer patientsFluid samplesCell lung cancer patientsCox proportional hazards modelInferior overall survivalKaplan-Meier methodNon-malignant groupCell lung cancerLung cancer patientsProportional hazards modelPleural fluid specimensCommon complicationPD-L1Pleural effusionCurrent gold standardCancer patientsLung cancer
2017
Feasibility of monitoring advanced melanoma patients using cell‐free DNA from plasma
Gangadhar T, Savitch S, Yee S, Xu W, Huang A, Harmon S, Lieberman D, Soucier D, Fan R, Black T, Morrissette J, Salathia N, Waters J, Zhang S, Toung J, van Hummelen P, Fan J, Xu X, Amaravadi R, Schuchter L, Karakousis G, Hwang W, Carpenter E. Feasibility of monitoring advanced melanoma patients using cell‐free DNA from plasma. Pigment Cell & Melanoma Research 2017, 31: 73-81. PMID: 28786531, PMCID: PMC5742050, DOI: 10.1111/pcmr.12623.Peer-Reviewed Original ResearchConceptsCell-free DNAStage III/IV patientsTissue next-generation sequencingAdvanced melanoma patientsMonitoring of patientsPrevious therapyIV patientsAdvanced melanomaMelanoma patientsTumor burdenBlood drawUltra-deep sequencingPatientsPlasma mutationsLiquid biopsyNext-generation sequencingFrequent mutationsAllele fractionTherapyMore mutationsMutationsBiopsyMelanomaBRAF
2016
Detection of Therapeutically Targetable Driver and Resistance Mutations in Lung Cancer Patients by Next-Generation Sequencing of Cell-Free Circulating Tumor DNA
Thompson J, Yee S, Troxel A, Savitch S, Fan R, Balli D, Lieberman D, Morrissette J, Evans T, Bauml J, Aggarwal C, Kosteva J, Alley E, Ciunci C, Cohen R, Bagley S, Stonehouse-Lee S, Sherry V, Gilbert E, Langer C, Vachani A, Carpenter E. Detection of Therapeutically Targetable Driver and Resistance Mutations in Lung Cancer Patients by Next-Generation Sequencing of Cell-Free Circulating Tumor DNA. Clinical Cancer Research 2016, 22: 5772-5782. PMID: 27601595, PMCID: PMC5448134, DOI: 10.1158/1078-0432.ccr-16-1231.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerCtDNA next-generation sequencingResistance mutationsNext-generation sequencingTissue sequencingAdvanced non-small cell lung cancerActionable EGFR mutationsCell lung cancerProgressive diseaseConsecutive patientsCtDNA sequencingTargetable driversLung cancerClinical trialsDisease progressionEGFR mutationsUltra-deep sequencingPatient managementExperimental therapiesTumor genotypingCtDNA samplesTissue biopsiesPatientsAccurate diagnosisBlood collection