0000000000430171

AUTHOR

V. Jooste

showing 4 related works from this author

Differences in the management and survival of metastatic colorectal cancer in Europe. A population-based study

2020

The management regarding metastatic colorectal cancer throughout Europe is not well known.To draw a European comparison of the management and prognosis of metastatic colorectal cancers.Factors associated with chemotherapy administration were identified through logistic regressions. Net survival was estimated and crude probabilities of death related to cancer and other causes using a flexible cumulative hazard model.Among the 13 227 patients with colorectal cancer diagnosed between 2010 and 2013 in cancer registries from 10 European countries, 3140 were metastatic. 62% of metastatic patients received chemotherapy. Compared to Spain, the related adjusted odds ratios ranged from 0.7 to 4.0 (P0…

MaleOncologymedicine.medical_specialtySurvivalColorectal cancerPopulationAntineoplastic AgentsLogistic regressionMetastasisMetastasis03 medical and health sciences0302 clinical medicineInternal medicineHealth caremedicineHumansRegistriesNeoplasm MetastasisDisease management (health)educationAgedRetrospective StudiesAged 80 and overeducation.field_of_studyHepatologybusiness.industryGastroenterologyDisease ManagementCancerOdds ratioMiddle Agedmedicine.diseaseColorectal cancerEurope030220 oncology & carcinogenesisFemale030211 gastroenterology & hepatologyColorectal NeoplasmsbusinessDigestive and Liver Disease
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Guidelines for time-to-event end point definitions in sarcomas and gastrointestinal stromal tumors (GIST) trials: results of the DATECAN initiative (…

2015

ABSTRACT The DATECAN initiative (Definition for the Assessment of Time-to-event Endpoints in CANcer trials) aims to provide recommendations for definitions of time-to-event end points in cancer randomized controlled trials. We relied on a consensus method based on a multidisciplinary panel of experts to develop these guidelines for trials on sarcomas and gastrointestinal stromal tumors. Background The use of potential surrogate end points for overall survival, such as disease-free survival (DFS) or time-to-treatment failure (TTF) is increasingly common in randomized controlled trials (RCTs) in cancer. However, the definition of time-to-event (TTE) end points is rarely precise and lacks unif…

medicine.medical_specialtyConsensusTime FactorssarcomaDelphi TechniqueEndpoint Determination[SDV]Life Sciences [q-bio]Disease-Free Survivallaw.invention03 medical and health sciencesgastrointestinal stromal tumors0302 clinical medicineRandomized controlled trialSDG 3 - Good Health and Well-beinglawMultidisciplinary approachTerminology as TopicmedicineHumansMedical physicsTreatment Failureguidelinestime-to-event end pointComputingMilieux_MISCELLANEOUSRandomized Controlled Trials as Topic030304 developmental biologyEvent (probability theory)0303 health sciencesEnd pointGiSTSurrogate endpointbusiness.industryefficacy measureCancerHematologymedicine.disease3. Good healthOncologyResearch Design030220 oncology & carcinogenesisrandomized controlled trialDisease ProgressionRadiologySarcomabusiness
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Erratum to “Time trends and short term projections of cancer prevalence in France” [Cancer Epidemiol. 56 (2018) 97–105]

2018

IF 2.888 (2017); International audience

Cancer ResearchEpidemiologyTime trendsbusiness.industryPublished ErratumMEDLINECancerTime trends[SDV.CAN]Life Sciences [q-bio]/Cancermedicine.diseaseShort-term projectionsTerm (time)Projection scenariosOncologyPrevalenceMedicineFlexible modelsbusinessCancer prevalenceDemographyCancer Epidemiology
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Time trends and short term projections of cancer prevalence in France

2018

IF 2.888 (2017); International audience; BackgroundThis study analyzes time trends in cancer prevalence in France and provides short-term projections up to the year 2017. The 15-year prevalence for 24 cancers was estimated from the French cancer registries network (FRANCIM) incidence and survival data.MethodWe estimated prevalence using the P = I × S relationship, with flexible modeling of incidence and survival. Based on observations of the incidence and survival up to 2010, different scenarios for evolution up to 2017 were studied, combining stable and dynamic incidence and survival. The determinants of variations in prevalence (incidence, survival and demography) were quantified.ResultsA…

AdultMaleCancer ResearchTime FactorsAdolescentEpidemiologyPopulation[SDV.CAN]Life Sciences [q-bio]/Cancer030501 epidemiologyProjection scenariosYoung Adult03 medical and health sciences0302 clinical medicineSurvival dataNeoplasmsPrevalencemedicineHumansRegistrieseducationCancer prevalenceAgedAged 80 and overeducation.field_of_studybusiness.industryTime trendsIncidenceIncidence (epidemiology)CancerTime trendsMiddle AgedPrognosismedicine.diseaseShort-term projections3. Good healthSurvival RateOncologyDemographic change030220 oncology & carcinogenesisFemaleFranceFlexible models0305 other medical sciencebusinessDemographyCancer Epidemiology
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