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
2021
Analysis of Survival Among Adults With Early-Onset Colorectal Cancer in the National Cancer Database
Cheng E, Blackburn HN, Ng K, Spiegelman D, Irwin ML, Ma X, Gross CP, Tabung FK, Giovannucci EL, Kunz PL, Llor X, Billingsley K, Meyerhardt JA, Ahuja N, Fuchs CS. Analysis of Survival Among Adults With Early-Onset Colorectal Cancer in the National Cancer Database. JAMA Network Open 2021, 4: e2112539. PMID: 34132794, PMCID: PMC8209612, DOI: 10.1001/jamanetworkopen.2021.12539.Peer-Reviewed Original ResearchConceptsEarly-onset colorectal cancerOnset colorectal cancerNational Cancer DatabaseColorectal cancerAge 51Overall survivalCancer DatabaseIncidence of CRCCox proportional hazards regressionPrimary colorectal cancerKaplan-Meier analysisProportional hazards regressionAge 50 yearsAge 25 yearsAnalysis of survivalCohort studySurvival benefitHazards regressionUnadjusted analysesCancer incidenceMAIN OUTCOMEAge 35Survival advantageLower riskStage I