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
Accounting for urinary dilution in peri-implantation samples: implications for creatinine adjustment and specimen pooling
Rosen Vollmar AK, Johnson CH, Weinberg CR, Deziel NC, Baird DD, Wilcox AJ, Jukic AMZ. Accounting for urinary dilution in peri-implantation samples: implications for creatinine adjustment and specimen pooling. Journal Of Exposure Science & Environmental Epidemiology 2020, 31: 356-365. PMID: 32424331, PMCID: PMC7671945, DOI: 10.1038/s41370-020-0227-1.Peer-Reviewed Original ResearchConceptsCreatinine adjustmentCreatinine concentrationUrinary dilutionUrinary estrogen metabolitesEffect of pregnancyUrinary creatinine concentrationCreatinine levelsWeeks' gestationEarly pregnancyCreatinine excretionEstrogen metabolitesCreatinine measuresUrine specimensPooled measureBiomarker measurementsPooled specimensEnvironmental exposuresExposure measuresLinear mixed modelsBiomonitoring resultsPregnancyT-testKappa coefficientMixed modelsPerson sample