Search results for "risk prediction"

showing 8 items of 18 documents

Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts

2018

Source at https://doi.org/10.1186/s13058-018-1073-0. Licensed CC BY-NC-ND 4.0. Background: Few published breast cancer (BC) risk prediction models consider the heterogeneity of predictor variables between estrogen-receptor positive (ER+) and negative (ER-) tumors. Using data from two large cohorts, we examined whether modeling this heterogeneity could improve prediction. Methods: We built two models, for ER+ (ModelER+) and ER- tumors (ModelER-) , respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks)…

OncologyHORMONE-REPLACEMENT THERAPYmedicine.medical_treatmentWHI0302 clinical medicineBreast cancerRisk FactorsEstrogen receptor030212 general & internal medicineProspective StudiesProspective cohort study2. Zero hungerIncidenceHormone replacement therapy (menopause)Middle Agedlcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogensPrognosisRisk prediction3. Good healthEuropean Prospective Investigation into Cancer and NutritionMenopausePOSTMENOPAUSAL WOMENReceptors EstrogenPLUS PROGESTIN030220 oncology & carcinogenesisCohortFemaleRisk assessmentResearch Articlemedicine.medical_specialtyMODELSAntineoplastic AgentsBreast NeoplasmsEstrògenslcsh:RC254-282Models BiologicalRisk AssessmentVALIDATIONCàncer de mamaMAMMOGRAPHY03 medical and health sciencesBreast cancerInternal medicinemedicineHumansOncology & CarcinogenesisCancer och onkologiVDP::Medical disciplines: 700::Clinical medical disciplines: 750::Oncology: 762business.industryMORTALITYKirurgiProspective cohortmedicine.diseaseEstrogenVDP::Medisinske Fag: 700::Klinisk medisinske fag: 750::Onkologi: 762Cancer and OncologySurgerybusinessEPIC1112 Oncology And CarcinogenesisBody mass indexFollow-Up StudiesBreast Cancer Research : BCR
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Comparison of genetic risk prediction models to improve prediction of coronary heart disease in two large cohorts of the MONICA/KORA study

2021

Abstract It is still unclear how genetic information, provided as single‐nucleotide polymorphisms (SNPs), can be most effectively integrated into risk prediction models for coronary heart disease (CHD) to add significant predictive value beyond clinical risk models. For the present study, a population‐based case‐cohort was used as a trainingset (451 incident cases, 1488 noncases) and an independent cohort as testset (160 incident cases, 2749 noncases). The following strategies to quantify genetic information were compared: A weighted genetic risk score including Metabochip SNPs associated with CHD in the literature (GRSMetabo); selection of the most predictive SNPs among these literature‐co…

Oncologymedicine.medical_specialtyEpidemiologyFramingham Risk Score ; Metabochip ; Coronary Heart Disease ; Genomic Risk Prediction ; Priority-lassoPopulationCoronary DiseaseSingle-nucleotide polymorphismKoronare HerzkrankheitPolymorphism Single NucleotideRisk AssessmentCohort Studies03 medical and health sciencesRisk FactorsInternal medicinemedicineHumansgenomic risk predictionddc:610coronary heart diseaseMetabochipGenetikeducationGenotypingGenetics (clinical)030304 developmental biologypriority‐Lasso0303 health scienceseducation.field_of_studyFramingham Risk ScoreModels GeneticProportional hazards modelbusiness.industry030305 genetics & heredityGenomicsConfidence intervalddc:Coronary disease; GeneticsRisk factorsCohortFramingham risk scorebusinessDDC 610 / Medicine & healthPredictive modelling
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Les pourritures racinaires du pois potager, caractérisation et biocontrôle du complexe parasitaire d’origine tellurique incluant Aphanomyces euteiches

2021

Pea root rots are a major concern for pea growing regions around the world. The disease is caused by a parasitic complex composed of many species of fungi and oomycetes of soil origin. In France, the main pathogen is the oomycete Aphanomyces euteiches. The identity of the other components of the parasitic complex and their respective contributions to the disease have never been investigated. No means of control is currently available to effectively control the disease except for a predictive bioassay that is questioned by some users. However, this test allows the avoidance of infested plots, which limits the multiplication of the major pathogen A. euteiches in the soil. In this context, the…

[SDV] Life Sciences [q-bio]risk predictionpourritures racinairesAphanomyces euteichesFusarium[SDV]Life Sciences [q-bio]root rotbiocontrôlebiocontrolprédiction du risquePisum sativum
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Sauna bathing is associated with reduced cardiovascular mortality and improves risk prediction in men and women: a prospective cohort study.

2018

Background Previous evidence indicates that sauna bathing is related to a reduced risk of fatal cardiovascular disease (CVD) events in men. The aim of this study was to investigate the relationship between sauna habits and CVD mortality in men and women, and whether adding information on sauna habits to conventional cardiovascular risk factors is associated with improvement in prediction of CVD mortality risk. Methods Sauna bathing habits were assessed at baseline in a sample of 1688 participants (mean age 63; range 53–74 years), of whom 51.4% were women. Multivariable-adjusted hazard ratios (HRs) were calculated to investigate the relationships of frequency and duration of sauna use with C…

kuolleisuusMalesaunominenPreventionlcsh:Rehkäisylcsh:MedicineGenderMiddle AgedCardiovascular diseaseSauna bathingRisk predictionsukupuoliSteam BathCardiovascular DiseasesRisk Factorssydän- ja verisuonitauditHumansennaltaehkäisyFemaleProspective StudiesRisk Reduction BehaviorResearch ArticleAgedProportional Hazards Models
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Efficient design and modeling strategies for follow-up studies with time-varying covariates

2015

Epidemiological studies can often be designed in several ways, some of which may be more optimal than others. Possible designs may differ in the required resources or the ability to provide reliable answers to the questions under study. In addition, once the data are collected, the selected modeling approach may affect how efficiently the data are utilized. The purpose of this dissertation is to investigate efficient designs and analysis meth ods in follow-up studies with longitudinal measurements. A key question is how to select optimally a subcohort for a new longitudinal covariate measurement if we cannot afford to measure the entire cohort. Another key question we consider is how to determine …

kuolleisuustime-varying covariatesdata collectionkustannustehokkuusanalyysimenetelmätennusteetfollow-up studypitkittäistutkimusoptimaalisuusrisk predictiondataaikariippuvat kovariaatitSeurantatutkimustutkimusmenetelmätsydän- ja verisuonitauditcardiovascular disease mortalitylongitudinal measurementssimulointioptimal designepidemiologiakohorttitutkimustutkimusaineistoterveysriskit
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Is 're-calibration' of standard cardiovascular disease (CVD) risk algorithms the panacea to improved CVD risk prediction and prevention?

2018

This editorial refers to ‘Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies’, by L. Pennells et al., doi:10.1093/eurheartj/ehy653.

medicine.medical_specialtyCalibration (statistics)Cvd riskehkäisyMEDLINEDisease030204 cardiovascular system & hematologyPanacea (medicine)03 medical and health sciencesrisk prediction0302 clinical medicinepreventioncardiovascular diseasealgoritmitMedicinerisk algorithms030212 general & internal medicineIntensive care medicineta315riskitbusiness.industryta3141ta3121ennustettavuussydän- ja versisuonitauditCardiology and Cardiovascular MedicinebusinessRisk assessmentEuropean Heart Journal
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Head-to-head comparison of contemporary heart failure risk scores.

2021

Altres ajuts: acords transformatius de la UAB Aims: Several heart failure (HF) web-based risk scores are currently used in clinical practice. Currently, we lack head-to-head comparison of the accuracy of risk scores. This study aimed to assess correlation and mortality prediction performance of Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC-HF) risk score, which includes clinical variables + medications; Seattle Heart Failure Model (SHFM), which includes clinical variables + treatments + analytes; PARADIGM Risk of Events and Death in the Contemporary Treatment of Heart Failure (PREDICT-HF) and Barcelona Bio-Heart Failure (BCN-Bio-HF) risk calculator, which also include biomarke…

medicine.medical_specialtyCalibration (statistics)Head to headHeart failureSpearman's rank correlation coefficientRisk AssessmentCorrelationRisk FactorsInternal medicineNatriuretic Peptide BrainmedicineRisk modelsHumansOverall performanceMortalityNatriuretic PeptidesHeart FailureFramingham Risk Scorebusiness.industrymedicine.diseasePrognosisRisk predictionPeptide FragmentsClinical PracticeHeart failureCardiology and Cardiovascular MedicinebusinessBiomarkersEuropean journal of heart failureReferences
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How many longitudinal covariate measurements are needed for risk prediction?

2014

Abstract Objective In epidemiologic follow-up studies, many key covariates, such as smoking, use of medication, blood pressure, and cholesterol, are time varying. Because of practical and financial limitations, time-varying covariates cannot be measured continuously, but only at certain prespecified time points. We study how the number of these longitudinal measurements can be chosen cost-efficiently by evaluating the usefulness of the measurements for risk prediction. Study Design and Setting The usefulness is addressed by measuring the improvement in model discrimination between models using different amounts of longitudinal information. We use simulated follow-up data and the data from t…

ta112Models StatisticalEpidemiologyComputer scienceHazard ratiota3142Risk Assessment01 natural sciencesrisk prediction010104 statistics & probability03 medical and health sciencesstudy design0302 clinical medicineCovariateStatisticsEconometricsHumanslongitudinal measurementsLongitudinal Studies030212 general & internal medicine0101 mathematicsOlder peoplemodel discriminationForecastingJournal of Clinical Epidemiology
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