2017
A pooled analysis of dietary sugar/carbohydrate intake and esophageal and gastric cardia adenocarcinoma incidence and survival in the USA
Li N, Petrick JL, Steck SE, Bradshaw PT, McClain KM, Niehoff NM, Engel LS, Shaheen NJ, Risch HA, Vaughan TL, Wu AH, Gammon MD. A pooled analysis of dietary sugar/carbohydrate intake and esophageal and gastric cardia adenocarcinoma incidence and survival in the USA. International Journal Of Epidemiology 2017, 46: 1836-1846. PMID: 29040685, PMCID: PMC5837717, DOI: 10.1093/ije/dyx203.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinomaAgedBlood GlucoseBody Mass IndexCase-Control StudiesDietary CarbohydratesDietary SucroseEsophageal NeoplasmsFemaleGastroesophageal RefluxHumansIncidenceLogistic ModelsMaleMiddle AgedMultivariate AnalysisNutrition AssessmentProportional Hazards ModelsRisk FactorsStomach NeoplasmsUnited StatesConceptsGastro-esophageal reflux diseaseBody mass indexCarbohydrate intakeAdenocarcinoma incidenceGCA incidenceOdds ratioUS population-based case-control studyStudy-specific food-frequency questionnairesPopulation-based case-control studyCox proportional hazards regressionGlycaemic indexDietary glycaemic indexFood frequency questionnaireProportional hazards regressionCase-control studyIntake of sucroseHigh glycaemic indexCarbohydrate measuresFrequency questionnaireHazard ratioReflux diseaseMass indexHazards regressionVital statusPooled analysis
2015
Dietary intake of flavonoids and oesophageal and gastric cancer: incidence and survival in the United States of America (USA)
Petrick JL, Steck SE, Bradshaw PT, Trivers KF, Abrahamson PE, Engel LS, He K, Chow WH, Mayne ST, Risch HA, Vaughan TL, Gammon MD. Dietary intake of flavonoids and oesophageal and gastric cancer: incidence and survival in the United States of America (USA). British Journal Of Cancer 2015, 112: 1291-1300. PMID: 25668011, PMCID: PMC4385952, DOI: 10.1038/bjc.2015.25.Peer-Reviewed Original ResearchConceptsOdds ratioHazard ratioFlavonoid intakeGastric cancerFood frequency questionnaire responsesMulticentre population-based studyIntake of anthocyanidinsLowest intake quartilesTotal flavonoid intakeFrequency-matched controlsPopulation-based studyProportional hazards regressionRisk of mortalityUSDA flavonoid databasesCase participantsAnthocyanidin intakeIntake quartilesHazards regressionVital statusDietary intakeChemopreventive effectsEpidemiologic studiesTumor typesFlavonoid databaseCancer
2014
Telomere Length and Mortality Following a Diagnosis of Ovarian Cancer
Kotsopoulos J, Prescott J, De Vivo I, Fan I, Mclaughlin J, Rosen B, Risch H, Sun P, Narod SA. Telomere Length and Mortality Following a Diagnosis of Ovarian Cancer. Cancer Epidemiology Biomarkers & Prevention 2014, 23: 2603-2606. PMID: 25159293, PMCID: PMC4221534, DOI: 10.1158/1055-9965.epi-14-0885.Peer-Reviewed Original ResearchConceptsLength z-scoreOvarian cancerZ-scoreTelomere lengthOvarian cancer-specific mortalityLarge population-based studyCancer-specific mortalityIncident ovarian cancerPopulation-based studyConfidence intervalsProportional hazards modelComputerized record linkagePeripheral blood leukocytesRelative telomere lengthNonserous tumorsChart reviewPrognostic roleVital statusPrognostic significanceLowest quartileBlood leukocytesHazards modelCancerCancer developmentQuartile
2012
Height, weight, BMI and ovarian cancer survival
Kotsopoulos J, Moody JR, Fan I, Rosen B, Risch HA, McLaughlin JR, Sun P, Narod SA. Height, weight, BMI and ovarian cancer survival. Gynecologic Oncology 2012, 127: 83-87. PMID: 22713293, DOI: 10.1016/j.ygyno.2012.05.038.Peer-Reviewed Original ResearchConceptsBody mass indexOvarian cancer survivalOvarian cancer-specific mortalityCancer-specific mortalityHazard ratioCancer survivalOvarian cancerLarge population-based studyBMI 5 yearsFatal gynecologic malignancyPopulation-based studyEpithelial ovarian cancerConfidence intervalsOvarian cancer prognosisProportional hazards modelChart reviewGynecologic malignanciesClinicopathologic featuresHistologic subtypeMass indexVital statusModifiable factorsRisk factorsHazards modelCancer prognosis