2024
Using a Bayesian analytic approach to identify county-level ecological factors associated with survival among individuals with early-onset colorectal cancer
Siddique S, Baum L, Deziel N, Kelly J, Warren J, Ma X. Using a Bayesian analytic approach to identify county-level ecological factors associated with survival among individuals with early-onset colorectal cancer. PLOS ONE 2024, 19: e0311540. PMID: 39471191, PMCID: PMC11521299, DOI: 10.1371/journal.pone.0311540.Peer-Reviewed Original ResearchConceptsAge-of-onset colorectal cancerEarly-onset colorectal cancerEnd Results program dataCenters for Disease Control and Prevention dataCounty-level factorsColorectal cancerHealth risk behaviorsIdentified principal componentsOdds of survivalPreventive servicesSurvival disparitiesLinear mixed modelsEOCRCChronic diseasesPreventive factorsUS countiesSalt Lake CountyCA residentsRisk behaviorsUnited StatesProgram dataCounty-levelOlder ageBayesian analytical approachYounger age
2020
Epidemiology of the classical myeloproliferative neoplasms: The four corners of an expansive and complex map
Shallis RM, Wang R, Davidoff A, Ma X, Podoltsev NA, Zeidan AM. Epidemiology of the classical myeloproliferative neoplasms: The four corners of an expansive and complex map. Blood Reviews 2020, 42: 100706. PMID: 32517877, DOI: 10.1016/j.blre.2020.100706.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsChronic myeloid leukemiaPolycythemia veraEssential thrombocythemiaMyeloproliferative neoplasmsClassical myeloproliferative neoplasmsPrimary myelofibrosisIncidence of CMLEnd Results program dataTyrosine kinase inhibitor therapyCML patient outcomesClonal myeloid disordersKinase inhibitor therapyPotential etiological roleInhibitor therapyMale genderRisk factorsPatient outcomesMyeloid leukemiaPMF patientsBetter survivalGeneral populationEtiological roleMyeloid disordersMolecular abnormalitiesEpidemiological literature
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