2025
National Trends in Suicidal Thoughts and Suicide Attempts Among High School Students in the United States
Bommersbach T, Olfson M, Rhee T. National Trends in Suicidal Thoughts and Suicide Attempts Among High School Students in the United States. American Journal Of Psychiatry 2025, 182: 639-659. PMID: 40432341, DOI: 10.1176/appi.ajp.20240706.Peer-Reviewed Original ResearchConceptsPast-year suicidal thoughtsSuicidal thoughtsHigh school studentsHealth risk behaviorsSuicidal symptomsSuicide attemptsNon-Hispanic whitesSchool studentsBehavioral risksBlack studentsNational trendsHigh school seniorsU.S. high school studentsDepressive symptomsAttempted suicideRisk categoriesEstimate national trendsBiennial cross-sectional surveysMultivariate logistic regressionSuicideYouth Risk Behavior SurveySchool seniorsElevated ratesHealth risk categoriesRisk Behavior SurveyTrends in depressive symptoms among high school students with and without health-risk behaviors in the United States: A population-based study
Bommersbach T, Olfson M, Rhee T. Trends in depressive symptoms among high school students with and without health-risk behaviors in the United States: A population-based study. The Lancet Regional Health - Americas 2025, 42: 101000. PMID: 39906085, PMCID: PMC11790505, DOI: 10.1016/j.lana.2025.101000.Peer-Reviewed Original ResearchHealth risk behaviorsDepressive symptomsYouth Risk Behavior SurveyNational trendsMultiple behavioral risk factorsMultivariable-adjusted logistic regressionUniversal depression screeningAssociated with depressive symptomsBiennial cross-sectional surveysBehavioral risk factorsShort sleeping hoursAt-risk groupsNon-Hispanic white studentsRisk categoriesDepression screeningUS high school studentsScreen timeHigh school studentsWeight perceptionRisk Behavior SurveyRisk behaviorsTargeted screeningLogistic regressionSleep hoursDecreased engagement
2024
Mechanical clot disruption during pulmonary thromboembolectomy is safe: A propensity score-matched analysis
Thomas S, Deshmukh A, Mojibian H, Marino A, Lozada J, Cornman-Homonoff J. Mechanical clot disruption during pulmonary thromboembolectomy is safe: A propensity score-matched analysis. Clinical Imaging 2024, 118: 110381. PMID: 39637758, DOI: 10.1016/j.clinimag.2024.110381.Peer-Reviewed Original ResearchPulmonary thromboembolectomyPulmonary emboliPulmonary arteryRight pulmonary arteryLeft pulmonary arteryPulmonary artery pressureAdministration of anticoagulantsDuration of hospitalizationMechanical clot disruptionPropensity-score matchingSPESI scorePulmonary vasculatureArterial pressureClinical effectsOrganized thrombusThromboembolectomyPropensity-scoreClot disruptionInclusion criteriaPatientsMortality rateRisk categoriesCompare groupsStudy periodArteryUsing Data-To-Care Strategies to Optimize the HIV Care Continuum in Connecticut: Results From a Randomized Controlled Trial
Machavariani E, Miceli J, Altice F, Fanfair R, Speers S, Nichols L, Jenkins H, Villanueva M. Using Data-To-Care Strategies to Optimize the HIV Care Continuum in Connecticut: Results From a Randomized Controlled Trial. JAIDS Journal Of Acquired Immune Deficiency Syndromes 2024, 96: 40-50. PMID: 38324241, PMCID: PMC11009056, DOI: 10.1097/qai.0000000000003391.Peer-Reviewed Original ResearchDisease intervention specialistsCare continuum outcomesHIV care continuum outcomesHIV care continuumRandomized controlled trialsHIV risk categoryCare continuumStandard-of-careData-to-CareViral suppressionRe-engagementPredictor of re-engagementRisk categoriesHIV careRe-engage peopleMultivariate regression modelHIV clinicPredictors of retentionDetectable HIV-1 RNAIntervention specialistsControlled trialsPre-randomizationPredictors of VSCareHIV-1 RNAPolygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction
Yiangou K, Mavaddat N, Dennis J, Zanti M, Wang Q, Bolla M, Abubakar M, Ahearn T, Andrulis I, Anton-Culver H, Antonenkova N, Arndt V, Aronson K, Augustinsson A, Baten A, Behrens S, Bermisheva M, de Gonzalez A, Białkowska K, Boddicker N, Bodelon C, Bogdanova N, Bojesen S, Brantley K, Brauch H, Brenner H, Camp N, Canzian F, Castelao J, Cessna M, Chang-Claude J, Chenevix-Trench G, Chung W, Colonna S, Couch F, Cox A, Cross S, Czene K, Daly M, Devilee P, Dörk T, Dunning A, Eccles D, Eliassen A, Engel C, Eriksson M, Evans D, Fasching P, Fletcher O, Flyger H, Fritschi L, Gago-Dominguez M, Gentry-Maharaj A, González-Neira A, Guénel P, Hahnen E, Haiman C, Hamann U, Hartikainen J, Ho V, Hodge J, Hollestelle A, Honisch E, Hooning M, Hoppe R, Hopper J, Howell S, Howell A, Jakovchevska S, Jakubowska A, Jernström H, Johnson N, Kaaks R, Khusnutdinova E, Kitahara C, Koutros S, Kristensen V, Lacey J, Lambrechts D, Lejbkowicz F, Lindblom A, Lush M, Mannermaa A, Mavroudis D, Menon U, Murphy R, Nevanlinna H, Obi N, Offit K, Park-Simon T, Patel A, Peng C, Peterlongo P, Pita G, Plaseska-Karanfilska D, Pylkäs K, Radice P, Rashid M, Rennert G, Roberts E, Rodriguez J, Romero A, Rosenberg E, Saloustros E, Sandler D, Sawyer E, Schmutzler R, Scott C, Shu X, Southey M, Stone J, Taylor J, Teras L, van de Beek I, Willett W, Winqvist R, Zheng W, Vachon C, Schmidt M, Hall P, MacInnis R, Milne R, Pharoah P, Simard J, Antoniou A, Easton D, Michailidou K. Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction. Breast Cancer Research 2024, 26: 189. PMID: 39734228, PMCID: PMC11682615, DOI: 10.1186/s13058-024-01947-x.Peer-Reviewed Original ResearchConceptsBreast Cancer Association ConsortiumBreast cancer risk predictionCancer risk predictionBreast cancer diagnosisEuropean ancestry populationsUK BiobankAncestry populationsBreast cancer risk estimationCancer diagnosisRisk predictionRisk estimatesPrincipal component adjustmentPolygenic risk scoresCancer risk estimatesCountry of birthInfluence risk estimatesRisk categoriesEuropean populationsOverestimation of riskEuropean ancestryUnderestimation of riskRisk scorePredicted riskEuropean countriesGenotype data
2023
Efficacy of Imetelstat in Achieving Red Blood Cell Transfusion Independence (RBC-TI) across Different Risk Subgroups in Patients with Lower-Risk Myelodysplastic Syndromes (LR-MDS) Relapsed/Refractory (R/R) to Erythropoiesis-Stimulating Agents (ESAs) in IMerge Phase 3 Study
Komrokji R, Santini V, Fenaux P, Savona M, Madanat Y, Berry T, Sherman L, Navada S, Feller F, Sun L, Xia Q, Wan Y, Huang F, Zeidan A, Platzbecker U. Efficacy of Imetelstat in Achieving Red Blood Cell Transfusion Independence (RBC-TI) across Different Risk Subgroups in Patients with Lower-Risk Myelodysplastic Syndromes (LR-MDS) Relapsed/Refractory (R/R) to Erythropoiesis-Stimulating Agents (ESAs) in IMerge Phase 3 Study. Blood 2023, 142: 194. DOI: 10.1182/blood-2023-181237.Peer-Reviewed Original ResearchInternational Prognostic Scoring SystemLower-risk myelodysplastic syndromesDifferent risk subgroupsErythropoiesis stimulating agentsLow-risk subgroupsRisk groupsRisk subgroupsResponse rateTI ratesRBC-TIClinical efficacyRisk categoriesHigh riskLower riskRed blood cell transfusion independenceIPSS risk groupPhase 3 portionIntermediate-risk groupCytogenetic risk groupHigh-risk patientsPhase 3 studyPrognostic scoring systemIntermediate-risk subgroupsHigh-risk subgroupsHigh-risk groupRisk Assessment of Kidney Disease Progression and Efficacy of SGLT2 Inhibition in Patients With Type 2 Diabetes
Moura F, Berg D, Bellavia A, Dwyer J, Mosenzon O, Scirica B, Wiviott S, Bhatt D, Raz I, Feinberg M, Braunwald E, Morrow D, Sabatine M. Risk Assessment of Kidney Disease Progression and Efficacy of SGLT2 Inhibition in Patients With Type 2 Diabetes. Diabetes Care 2023, 46: 1807-1815. PMID: 37556796, PMCID: PMC10516252, DOI: 10.2337/dc23-0492.Peer-Reviewed Original ResearchConceptsSodium-glucose cotransporter 2Kidney disease progressionPredictors of kidney disease progressionAbsolute risk reductionDisease progressionValidation cohortType 2 diabetesSodium-glucose cotransporter 2 inhibitionUrine albumin-to-creatinine ratioAlbumin-to-creatinine ratioEfficacy of dapagliflozinMedian follow-upRisk categoriesMultivariate Cox regressionRelative risk reductionHigh-risk groupAtherosclerotic cardiovascular diseaseSystolic blood pressureRisk reductionMagnitude of benefitDapagliflozin EffectT2D durationCotransporter 2SGLT2 inhibitionStratify riskCommunity distress and risk of adverse outcomes after peripheral vascular intervention
Schenck C, Strand E, Smolderen K, Romain G, Nagpal S, Cleman J, Blume P, Mena-Hurtado C. Community distress and risk of adverse outcomes after peripheral vascular intervention. Journal Of Vascular Surgery 2023, 78: 166-174.e3. PMID: 36944389, PMCID: PMC11146282, DOI: 10.1016/j.jvs.2023.03.027.Peer-Reviewed Original ResearchConceptsPeripheral vascular interventionsDistressed Communities IndexMajor amputationRisk of mortalityAdverse outcomesVascular interventionsVascular Quality Initiative databaseDCI scoresCommunity distressCox regression modelTime-dependent receiverCharacteristic curve analysisClinical characteristicsFinal cohortPrimary outcomeClinical outcomesCardiovascular diseasePatientsAmputationZip code dataMortalityRisk categoriesCurve analysisInitiative databaseOutcomesAdjuvant immunotherapy in renal cell carcinoma: A living systematic review and network meta-analysis (NMA).
Sipra Q, Bin Riaz I, Naqvi S, He H, Siddiqi R, Islam M, Asghar N, Ikram W, Xu W, Singh P, Ho T, Bilen M, Zakharia Y, Bryce A. Adjuvant immunotherapy in renal cell carcinoma: A living systematic review and network meta-analysis (NMA). Journal Of Clinical Oncology 2023, 41: 694-694. DOI: 10.1200/jco.2023.41.6_suppl.694.Peer-Reviewed Original ResearchRenal cell carcinomaDisease-free survivalAdjuvant immunotherapyBaseline riskCell carcinomaTreatment optionsImproved disease-free survivalLocalized Renal Cell CarcinomaRisk categoriesAdjuvant treatment optionsAbsolute risk differenceUnique treatment optionRisk stratification systemMixed treatment comparisonSignificant differencesRelative effect estimatesEvidence synthesis frameworkAdjuvant pembrolizumabNivolumab-ipilimumabOverall survivalTreatment landscapeAbsolute benefitPreferred treatmentRecent trialsDisease progressionRisk Stratification for Management of Solitary Fibrous Tumor/Hemangiopericytoma of the Central Nervous System
Kinslow C, Rae A, Kumar P, McKhann G, Sisti M, Bruce J, Yu J, Cheng S, Wang T. Risk Stratification for Management of Solitary Fibrous Tumor/Hemangiopericytoma of the Central Nervous System. Cancers 2023, 15: 876. PMID: 36765837, PMCID: PMC9913704, DOI: 10.3390/cancers15030876.Peer-Reviewed Original ResearchNational Cancer DatabaseCause-specific survivalIntermediate-risk groupCentral nervous systemSolitary fibrous tumor/hemangiopericytomaAssociation of radiotherapyHigh-risk groupOverall survivalRisk categoriesRisk stratificationAssociated with improved survivalPrognostic risk categoriesGross-total resectionKaplan-Meier methodNervous systemCox proportional hazards regressionLow-risk groupProportional hazards regressionEORTC Cooperative GroupRadiotherapy strategiesSEER databaseSurvival benefitProspective trialsCancer DatabaseMeningeal tumors
2022
OP0027 ASSOCIATION BETWEEN BASELINE CARDIOVASCULAR RISK AND INCIDENCE RATES OF MAJOR ADVERSE CARDIOVASCULAR EVENTS AND MALIGNANCIES IN PATIENTS WITH PSORIATIC ARTHRITIS AND PSORIASIS RECEIVING TOFACITINIB
Kristensen L, Strober B, Poddubnyy D, Leung Y, Jo H, Kwok K, Vranic I, Fleishaker D, Fallon L, Yndestad A, Gladman D. OP0027 ASSOCIATION BETWEEN BASELINE CARDIOVASCULAR RISK AND INCIDENCE RATES OF MAJOR ADVERSE CARDIOVASCULAR EVENTS AND MALIGNANCIES IN PATIENTS WITH PSORIATIC ARTHRITIS AND PSORIASIS RECEIVING TOFACITINIB. Annals Of The Rheumatic Diseases 2022, 81: 20. DOI: 10.1136/annrheumdis-2022-eular.1762.Peer-Reviewed Original ResearchMajor adverse CV eventsASCVD riskCV riskIncidence rateBristol-Myers SquibbGrant/research supportPfizer IncPsoriatic arthritisSpeakers bureauEli LillyMajor adverse cardiovascular eventsRisk categoriesGilead SciencesASCVD risk categoryBaseline cardiovascular riskBaseline CV riskTofacitinib-treated patientsTreatment of PsAAdverse cardiovascular eventsAdverse CV eventsCV disease riskCoronary artery diseaseHigh incidence rateDose of tofacitinibCV events
2021
319-OR: Effects of Empagliflozin on Markers of Liver Steatosis and Fibrosis and Their Relation to Cardiorenal Outcomes in the EMPA-REG OUTCOME Trial
KAHL S, OFSTAD A, ZINMAN B, WANNER C, SCHUELER E, INZUCCHI S, RODEN M. 319-OR: Effects of Empagliflozin on Markers of Liver Steatosis and Fibrosis and Their Relation to Cardiorenal Outcomes in the EMPA-REG OUTCOME Trial. Diabetes 2021, 70 DOI: 10.2337/db21-319-or.Peer-Reviewed Original ResearchNonalcoholic fatty liver diseaseNAFLD fibrosis scoreCardiorenal outcomesFibrosis riskEMPA-REG OUTCOMELiver fat contentRisk of steatosisEffect of empagliflozinFatty liver diseaseType 2 diabetesCause deathDaily empagliflozinSteatosis indexHeart failureFibrosis scoreLiver diseaseCox regressionCardiovascular diseaseHigh riskEmpagliflozinPlaceboSteatosisRisk categoriesBaselineMeasures analysisOutcomes of first-line (1L) ipilimumab and nivolumab (IPI-NIVO) and subsequent therapy in metastatic renal cell carcinoma (mRCC): Results from the International mRCC Database Consortium (IMDC).
Gan C, Wells J, Schmidt A, Powles T, Tran B, Meza L, Labaki C, Lee J, Wood L, Shapiro J, Ernst D, Kapoor A, Canil C, Yuasa T, McKay R, Beuselinck B, Donskov F, Dudani S, Choueiri T, Heng D. Outcomes of first-line (1L) ipilimumab and nivolumab (IPI-NIVO) and subsequent therapy in metastatic renal cell carcinoma (mRCC): Results from the International mRCC Database Consortium (IMDC). Journal Of Clinical Oncology 2021, 39: 4554-4554. DOI: 10.1200/jco.2021.39.15_suppl.4554.Peer-Reviewed Original ResearchInternational mRCC Database ConsortiumMetastatic renal cell carcinomaIpi-nivoOverall survivalCell histologyInternational mRCC Database Consortium criteriaOutcomes of first-lineTreatment durationNon-clear cell histologyPoor-risk diseaseTyrosine kinase inhibitorsRenal cell carcinomaRisk categoriesMedian OSBrain metastasesBone metastasesLiver metastasesPoor riskRisk diseaseCell carcinomaFirst-lineMedian ageProgressive diseaseMedian TDNeutrophil count
2020
Defining High‐risk Emergency Chief Complaints: Data‐driven Triage for Low‐ and Middle‐income Countries
Rice B, Leanza J, Mowafi H, Kamara N, Mulogo EM, Bisanzo M, Nikam K, Kizza H, Newberry JA, Strehlow M, Group G, Kohn M. Defining High‐risk Emergency Chief Complaints: Data‐driven Triage for Low‐ and Middle‐income Countries. Academic Emergency Medicine 2020, 27: 1291-1301. PMID: 32416022, PMCID: PMC7818254, DOI: 10.1111/acem.14013.Peer-Reviewed Original ResearchConceptsHigh-risk chief complaintsChief complaintMiddle-income countriesPatient outcomesLMIC settingsVital signsMortality odds ratioLevel of consciousnessLogistic regression modelsLocal disease patternsHIV statusMortality oddsOdds ratioDerivation data setsEmergency unitMortality riskEmergency careEmergency training programsDerivation dataDisease patternsTriage systemRisk categoriesComplaintsPatient dataTriage data
2019
A Phase 1b Study of Glasdegib in Combination with Azacitidine in Patients with Untreated Higher-Risk Myelodysplastic Syndromes, Acute Myeloid Leukemia, and Chronic Myelomonocytic Leukemia
Sekeres M, Schuster M, Joris M, Krauter J, Maertens J, Gyan E, Kovacsovics T, Verma A, Vyas P, Wang E, Wendy W, Zeremski M, Kudla A, Chan G, Zeidan A. A Phase 1b Study of Glasdegib in Combination with Azacitidine in Patients with Untreated Higher-Risk Myelodysplastic Syndromes, Acute Myeloid Leukemia, and Chronic Myelomonocytic Leukemia. Blood 2019, 134: 177. DOI: 10.1182/blood-2019-124050.Peer-Reviewed Original ResearchHigh-risk myelodysplastic syndromeChronic myelomonocytic leukemiaAcute myeloid leukemiaLow-dose cytarabineMedian treatment durationComplete remissionPhase 1b trialIntensive chemotherapyOverall survivalMyelodysplastic syndromePersonal feesAdverse eventsMyelomonocytic leukemiaSpeakers bureauSerious TEAEsFebrile neutropeniaMedian ageMedian timeEuropean LeukemiaNetRisk categoriesMyeloid leukemiaMedian (95% CI) OSMortality rateTreatment durationCR/complete remissionStratifying Ovarian Cancer Risk Using Personal Health Data
Hart GR, Nartowt BJ, Muhammad W, Liang Y, Huang GS, Deng J. Stratifying Ovarian Cancer Risk Using Personal Health Data. Frontiers In Big Data 2019, 2: 24. PMID: 33693347, PMCID: PMC7931902, DOI: 10.3389/fdata.2019.00024.Peer-Reviewed Original ResearchOvarian cancer riskCancer riskOvarian Cancer Screening TrialNational Health Interview SurveyCancer Screening TrialHigh-risk populationHealth Interview SurveyHealth dataOvarian cancer detectionDifferent risk categoriesPublic health organizationsOvarian cancerScreening TrialGeneral populationLower riskPersonal health dataTargeted screeningGenetic testingRisk categoriesHealth OrganizationInterview SurveyCancerCharacteristic curveNon-invasive wayCancer detection705 Evaluating the cost of surveillance for non-muscle invasive bladder cancer: An economic analysis based on risk categories
Mossanen M, Wang Y, Szymaniak J, Tan W, Huynh M, Preston M, Trinh Q, Sonpavde G, Schrag D, Kibel A, Chang S. 705 Evaluating the cost of surveillance for non-muscle invasive bladder cancer: An economic analysis based on risk categories. European Urology Open Science 2019, 18: e942. DOI: 10.1016/s1569-9056(19)30685-2.Peer-Reviewed Original ResearchPredicting the Risk of Huntington’s Disease with Multiple Longitudinal Biomarkers
Li F, Li K, Li C, Luo S, Group P. Predicting the Risk of Huntington’s Disease with Multiple Longitudinal Biomarkers. Journal Of Huntington's Disease 2019, 8: 323-332. PMID: 31256145, PMCID: PMC6718328, DOI: 10.3233/jhd-190345.Peer-Reviewed Original ResearchConceptsEnroll-HDRisk of Huntington's diseasePREDICT-HDRisk of HDMultiple longitudinal markersTime to diagnosisHuntington's diseasePatient's risk categoryPrognostic indexPrognostic scorePrognostic modelHD diagnosisRisk predictionPublic health threatCox modelRisk categoriesLongitudinal measurementsHealth threatRiskLongitudinal biomarkersScoresBiomarker measurementsPatient selectionClinical trialsClinical biomarkers
2018
Trends in volume and risk profiles of patients undergoing isolated surgical and transcatheter aortic valve replacement
Mori M, Bin Mahmood SU, Geirsson A, Yun JJ, Cleman MW, Forrest JK, Mangi AA. Trends in volume and risk profiles of patients undergoing isolated surgical and transcatheter aortic valve replacement. Catheterization And Cardiovascular Interventions 2018, 93: e337-e342. PMID: 30269424, DOI: 10.1002/ccd.27855.Peer-Reviewed Original ResearchMeSH KeywordsAcademic Medical CentersAgedAged, 80 and overAortic ValveFemaleHeart Valve Prosthesis ImplantationHospitals, High-VolumeHumansMalePatient Reported Outcome MeasuresPractice Patterns, Physicians'Retrospective StudiesRisk AssessmentRisk FactorsTime FactorsTranscatheter Aortic Valve ReplacementTreatment OutcomeConceptsSurgical aortic valve replacementAortic valve replacementSTS-PROMSAVR volumeSAVR cohortValve replacementCase volumeTranscatheter aortic valve replacementRisk profileTranscatheter aortic valve replacement (TAVR) programHigh-volume academic medical centerRisk categoriesStudy periodContemporary temporal trendsMedian STS PROMProportion of patientsRisk of mortalityLow-risk categoryAcademic medical centerPROM patientsTAVR cohortTAVR volumeTAVR patientsConsecutive patientsIntermediate riskDecreasing hospitalizations in patients on hemodialysis: Time for a paradigm shift
Golestaneh L. Decreasing hospitalizations in patients on hemodialysis: Time for a paradigm shift. Seminars In Dialysis 2018, 31: 278-288. PMID: 29409160, DOI: 10.1111/sdi.12675.Peer-Reviewed Original ResearchConceptsEngagement of patientsCost of careImprove hospital outcomesInpatient resource utilizationSelf-managementCare structuresSystem-level elementsPayment modelsPatient trajectoriesHospitalization riskHospital outcomesDecreased hospitalizationDialysis facilitiesCareEngaging stakeholdersAssociated with poor outcomesHospitalRisk categoriesStakeholder levelOutcomesRiskLong-term outcomesPoor outcomePatientsParadigm discussions
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