2023
Machine learning-based cluster analysis of immune cell subtypes and breast cancer survival
Wang Z, Katsaros D, Wang J, Biglio N, Hernandez B, Fei P, Lu L, Risch H, Yu H. Machine learning-based cluster analysis of immune cell subtypes and breast cancer survival. Scientific Reports 2023, 13: 18962. PMID: 37923775, PMCID: PMC10624674, DOI: 10.1038/s41598-023-45932-4.Peer-Reviewed Original ResearchMeSH KeywordsBreast NeoplasmsCluster AnalysisFemaleHumansMachine LearningNeoplasm Recurrence, LocalSurvival AnalysisConceptsImmune cell clustersT cellsHost immunityImmune cellsUnsupervised hierarchical clusteringImmune responseCD8-positive T cellsMemory CD4 T cellsCox regression survival analysisRegulatory T cellsPositive T cellsCD4 T cellsDifferent immune cellsDistinct immune responsesBreast cancer survivalImmune cell subtypesMemory B cellsImmune cell typesRegression survival analysisCell clustersBreast cancer progressionT cell receptor signalingCytokine stormOverall survivalFavorable survival
2018
Disparities by race, age, and sex in the improvement of survival for lymphoma: Findings from a population-based study
Mukhtar F, Boffetta P, Dabo B, Park JY, Tran CTD, Tran TV, Tran HT, Whitney M, Risch HA, Le LC, Zheng W, Shu XO, Luu HN. Disparities by race, age, and sex in the improvement of survival for lymphoma: Findings from a population-based study. PLOS ONE 2018, 13: e0199745. PMID: 29995909, PMCID: PMC6040734, DOI: 10.1371/journal.pone.0199745.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsFemaleHodgkin DiseaseHumansMaleMiddle AgedPopulation GroupsSex FactorsSurvival AnalysisConceptsLymphoma patientsHodgkin's lymphomaAge groupsHazard ratioDisease-specific mortalityFive-year survivalHodgkin's lymphoma patientsImprovement of survivalPopulation-based studyProportional hazards regressionConfidence intervalsCause-specific mortalityIncident lymphoma casesSEER cancer registryYears of ageOlder age groupsPatients 20Surveillance EpidemiologyCancer RegistrySurvival improvementHazards regressionLymphoma casesNHL survivalPatientsLymphoma
2017
History of Comorbidities and Survival of Ovarian Cancer Patients, Results from the Ovarian Cancer Association Consortium
Minlikeeva AN, Consortium JL, Freudenheim KH, Eng RA, Cannioto G, Friel JB, Szender B, Segal K, Odunsi P, Mayor B, Diergaarde E, Zsiros LE, Kelemen M, Köbel H, Steed A, deFazio SJ, Group PA, Jordan MW, Fasching HA, Beckmann MA, Risch JA, Rossing J, Doherty MT, Chang-Claude T, Goodman R, Dörk F, Edwards RB, Modugno K, Ness M, Matsuo BY, Mizuno EL, Karlan SK, Goode E, Kjær JM, Høgdall KL, Schildkraut DW, Terry EV, Cramer LE, Bandera LA, Paddock LFAG, Kiemeney R, Massuger H, Sutphen A, Anton-Culver U, Ziogas SA, Menon SJ, Gayther A, Ramus CL, Gentry-Maharaj AH, Pearce J, Wu A, Kupryjanczyk PM, Jensen KB, Webb P, Moysich K. History of Comorbidities and Survival of Ovarian Cancer Patients, Results from the Ovarian Cancer Association Consortium. Cancer Epidemiology Biomarkers & Prevention 2017, 26: 1470-1473. PMID: 28864456, PMCID: PMC5649363, DOI: 10.1158/1055-9965.epi-17-0367.Peer-Reviewed Original ResearchConceptsProgression-free survivalHistory of endometriosisStage of diseaseOvarian cancer patientsOvarian cancer outcomeCancer outcomesCancer patientsCox proportional hazards regression modelProportional hazards regression modelsHazards regression modelsInvasive ovarian carcinomasOvarian cancer prognosisOvarian Cancer Association ConsortiumPooled HRsConcurrent comorbiditiesHistologic subtypeOvarian carcinomaChronic diseasesOvarian cancerWeight statusNeurologic diseaseCancer prognosisComorbiditiesTreatment efficacyNeurological diseases
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
2013
Type I and II Endometrial Cancers: Have They Different Risk Factors?
Setiawan VW, Yang HP, Pike MC, McCann SE, Yu H, Xiang YB, Wolk A, Wentzensen N, Weiss NS, Webb PM, van den Brandt PA, van de Vijver K, Thompson PJ, Group T, Strom BL, Spurdle AB, Soslow RA, Shu XO, Schairer C, Sacerdote C, Rohan TE, Robien K, Risch HA, Ricceri F, Rebbeck TR, Rastogi R, Prescott J, Polidoro S, Park Y, Olson SH, Moysich KB, Miller AB, McCullough ML, Matsuno RK, Magliocco AM, Lurie G, Lu L, Lissowska J, Liang X, Lacey JV, Kolonel LN, Henderson BE, Hankinson SE, Håkansson N, Goodman MT, Gaudet MM, Garcia-Closas M, Friedenreich CM, Freudenheim JL, Doherty J, De Vivo I, Courneya KS, Cook LS, Chen C, Cerhan JR, Cai H, Brinton LA, Bernstein L, Anderson KE, Anton-Culver H, Schouten LJ, Horn-Ross PL. Type I and II Endometrial Cancers: Have They Different Risk Factors? Journal Of Clinical Oncology 2013, 31: 2607-2618. PMID: 23733771, PMCID: PMC3699726, DOI: 10.1200/jco.2012.48.2596.Peer-Reviewed Original ResearchMeSH KeywordsAdenocarcinomaAdultAge FactorsAgedBiopsy, NeedleCarcinoma, EndometrioidCase-Control StudiesCohort StudiesConfidence IntervalsContraceptives, OralDatabases, FactualDiabetes MellitusDisease-Free SurvivalEndometrial NeoplasmsFemaleHumansImmunohistochemistryMiddle AgedNeoplasm InvasivenessNeoplasm StagingObesityOdds RatioRisk FactorsSensitivity and SpecificitySmokingSurvival AnalysisConceptsType II tumorsII tumorsRisk factorsEndometrial cancerOdds ratioHigh-grade endometrioid tumorsEndometrial cancer risk factorsType IEndometrial Cancer ConsortiumEndometrial cancer typesType I tumorsEndometrial cancer casesOral contraceptive useRisk factor patternsBody mass indexCancer risk factorsCommon etiologic factorCase-control studyDifferent risk factorsEndometrioid tumorsI tumorsMass indexCigarette smokingPooled analysisEtiologic factors
2011
Clinical impact of unclassified variants of the BRCA1 and BRCA2 genes
Akbari MR, Zhang S, Fan I, Royer R, Li S, Risch H, McLaughlin J, Rosen B, Sun P, Narod SA. Clinical impact of unclassified variants of the BRCA1 and BRCA2 genes. Journal Of Medical Genetics 2011, 48: 783. PMID: 21965345, DOI: 10.1136/jmedgenet-2011-100305.Peer-Reviewed Original ResearchConceptsFirst-degree relativesFemale first-degree relativesRelatives of patientsOvarian cancerCumulative riskPathogenic mutationsUnclassified variantsRisk of cancerHistorical cohortBRCA2 mutationsClinical impactHigh riskBRCA2 genesCancerUnknown significancePatientsMissense variantsFunctional effectsWomenRiskBRCA1PenetranceMutationsRelativesCohortGenetic Effects and Modifiers of Radiotherapy and Chemotherapy on Survival in Pancreatic Cancer
Zeng H, Yu H, Lu L, Jain D, Kidd MS, Saif MW, Chanock SJ, Hartge P, Risch H. Genetic Effects and Modifiers of Radiotherapy and Chemotherapy on Survival in Pancreatic Cancer. Pancreas 2011, 40: 657-663. PMID: 21487324, PMCID: PMC3116071, DOI: 10.1097/mpa.0b013e31821268d1.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overATP Binding Cassette Transporter, Subfamily G, Member 2ATP-Binding Cassette TransportersCase-Control StudiesConnecticutDihydrouracil Dehydrogenase (NADP)FemaleGenetic MarkersGenetic VariationGenome-Wide Association StudyHumansMaleMiddle AgedNeoplasm ProteinsPancreatic NeoplasmsPolymorphism, Single NucleotidePrognosisProportional Hazards ModelsSerpinsSurvival AnalysisTreatment OutcomeConceptsPancreatic cancerOverall survivalCancer survivalProportional hazards regression modelsSurvival of patientsPopulation-based studyPancreatic cancer survivalHazards regression modelsGerm-line genetic variationEvidence of associationClinical outcomesCancer patientsTreatment outcomesTreatment responseSignificant associationPatientsCancerPrevious genome-wide association study dataRadiotherapyPutative markerGenetic polymorphismsSurvivalDPYD geneChemotherapyEvidence of interaction
2006
The relationship of insulin-like growth factor-II, insulin-like growth factor binding protein-3, and estrogen receptor-alpha expression to disease progression in epithelial ovarian cancer.
Lu L, Katsaros D, Wiley A, de la Longrais I, Risch HA, Puopolo M, Yu H. The relationship of insulin-like growth factor-II, insulin-like growth factor binding protein-3, and estrogen receptor-alpha expression to disease progression in epithelial ovarian cancer. Clinical Cancer Research 2006, 12: 1208-1214. PMID: 16489075, DOI: 10.1158/1078-0432.ccr-05-1801.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBiomarkers, TumorDisease ProgressionEpithelial CellsEstrogen Receptor alphaFemaleGene Expression Regulation, NeoplasticHumansInsulin-Like Growth Factor Binding Protein 3Insulin-Like Growth Factor IIMiddle AgedNeoplasm StagingOvarian NeoplasmsReverse Transcriptase Polymerase Chain ReactionRNA, NeoplasmSurvival AnalysisConceptsIGF-II expressionEstrogen receptor alpha expressionReceptor alpha expressionEpithelial ovarian cancerIGF-IIDisease progressionOvarian cancerInsulin-like growth factor (IGF) systemPrimary epithelial ovarian cancerProtein 3Insulin-like growth factorIGF signalingHigh IGF-IILarge residual lesionExpression of estrogenInsulin-like growth factor IIIGFBP-3 expressionEffects of IGFOvarian cancer treatmentGrowth factor systemFresh tumor specimensGrowth factor IIQuantitative reverse transcription PCRIGFBP-3Serous histology
2005
Demographic and lifestyle predictors of survival in patients with esophageal or gastric cancers
Trivers KF, de Roos AJ, Gammon MD, Vaughan TL, Risch HA, Olshan AF, Schoenberg JB, Mayne ST, Dubrow R, Stanford JL, Abrahamson P, Rotterdam H, West AB, Fraumeni JF, Chow WH. Demographic and lifestyle predictors of survival in patients with esophageal or gastric cancers. Clinical Gastroenterology And Hepatology 2005, 3: 225-230. PMID: 15765441, DOI: 10.1016/s1542-3565(04)00613-5.Peer-Reviewed Original ResearchConceptsBody mass indexEsophageal squamous cell carcinomaGastric cancerHazard ratioLonger survivalNonsteroidal anti-inflammatory drug usePopulation-based case-control studyAnti-inflammatory drug usePrediagnosis body mass indexAdjusted hazard ratioGastroesophageal reflux diseaseSquamous cell carcinomaConfidence intervalsGastric cancer survivalCase-control studyEsophageal adenocarcinoma patientsLocalized diseaseReflux diseaseMass indexAlcohol intakeCigarette smokingDecreased riskIncident casesAdenocarcinoma patientsCell carcinoma