2021
Phenotypic Differences in Juvenile Polyposis Syndrome With or Without a Disease-causing SMAD4/BMPR1A Variant
MacFarland SP, Ebrahimzadeh JE, Zelley K, Begum L, Bass LM, Brand RE, Dudley B, Fishman DS, Ganzak A, Karloski E, Latham A, Llor X, Plon S, Riordan MK, Scollon SR, Stadler ZK, Syngal S, Ukaegbu C, Weiss JM, Yurgelun MB, Brodeur GM, Mamula P, Katona BW. Phenotypic Differences in Juvenile Polyposis Syndrome With or Without a Disease-causing SMAD4/BMPR1A Variant. Cancer Prevention Research 2021, 14: 215-222. PMID: 33097490, PMCID: PMC8557953, DOI: 10.1158/1940-6207.capr-20-0348.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAge FactorsAgedBone Morphogenetic Protein Receptors, Type IChildChild, PreschoolColectomyColonoscopyFemaleFollow-Up StudiesGerm-Line MutationHumansIntestinal PolyposisMaleMedical History TakingMiddle AgedNeoplastic Syndromes, HereditaryPractice Guidelines as TopicPrecision MedicineSmad4 ProteinWatchful WaitingYoung AdultConceptsJuvenile polyposis syndromePolyposis syndromeFamily historyDisease-causing variantsCancer riskGermline disease-causing variantsGastrointestinal cancer predisposition syndromesUpper gastrointestinal polypsHamartomatous polyposis syndromesCancer predisposition syndromeLifelong surveillanceAdult centersDuodenal polypsGastrointestinal cancerCancer historySubgroup analysisIndividualized managementLower riskGastrointestinal polypsPredisposition syndromeSyndromeYounger ageDistinct phenotypic differencesLower likelihoodGastrectomy
2019
Scoring colorectal cancer risk with an artificial neural network based on self-reportable personal health data
Nartowt BJ, Hart GR, Roffman DA, Llor X, Ali I, Muhammad W, Liang Y, Deng J. Scoring colorectal cancer risk with an artificial neural network based on self-reportable personal health data. PLOS ONE 2019, 14: e0221421. PMID: 31437221, PMCID: PMC6705772, DOI: 10.1371/journal.pone.0221421.Peer-Reviewed Original ResearchConceptsNational Health Interview SurveyUnited States Preventative Services Task ForceColorectal cancerPredictive valueDiagnosis of CRCColorectal cancer riskHealth Interview SurveyHigh-risk categoryNegative predictive valuePositive predictive valueMultivariable prediction modelHealth dataUSPSTF guidelinesRisk score methodCRC riskFamily historyCancer riskHigh riskAge 50Individual prognosisLower riskPersonal health dataClinical applicabilityInterview SurveyCancer