0000000000195213

AUTHOR

Meinhard Kieser

showing 2 related works from this author

Opportunities and challenges of combined effect measures based on prioritized outcomes

2013

Many authors have proposed different approaches to combine multiple endpoints in a univariate outcome measure in the literature. In case of binary or time-to-event variables, composite endpoints, which combine several event types within a single event or time-to-first-event analysis are often used to assess the overall treatment effect. A main drawback of this approach is that the interpretation of the composite effect can be difficult as a negative effect in one component can be masked by a positive effect in another. Recently, some authors proposed more general approaches based on a priority ranking of outcomes, which moreover allow to combine outcome variables of different scale levels. …

Statistics and ProbabilityClinical Trials as TopicEpidemiologyUnivariatecomputer.software_genreOutcome (game theory)Treatment OutcomeRankingScale (social sciences)Component (UML)Outcome Assessment Health CareMultiple comparisons problemHumansComputer SimulationData miningcomputerProportional Hazards ModelsMathematicsStatistical hypothesis testingEvent (probability theory)Statistics in Medicine
researchProduct

A weighted combined effect measure for the analysis of a composite time-to-first-event endpoint with components of different clinical relevance

2018

Composite endpoints combine several events within a single variable, which increases the number of expected events and is thereby meant to increase the power. However, the interpretation of results can be difficult as the observed effect for the composite does not necessarily reflect the effects for the components, which may be of different magnitude or even point in adverse directions. Moreover, in clinical applications, the event types are often of different clinical relevance, which also complicates the interpretation of the composite effect. The common effect measure for composite endpoints is the all-cause hazard ratio, which gives equal weight to all events irrespective of their type …

Statistics and ProbabilityHazard (logic)EpidemiologyEndpoint Determination01 natural sciencesMeasure (mathematics)WIN RATIO010104 statistics & probability03 medical and health sciences0302 clinical medicineResamplingStatisticstime-to-eventHumansComputer Simulation030212 general & internal medicinerelevance weighting0101 mathematicsParametric statisticsEvent (probability theory)MathematicsProportional Hazards Modelsclinical trialsHazard ratiocomposite endpointWeightingPRIORITIZED OUTCOMESTRIALSData Interpretation StatisticalMULTISTATE MODELSINFERENCENull hypothesisMonte Carlo MethodStatistics in Medicine
researchProduct