%0 Journal Article %1 Wolkewitz2012 %A Wolkewitz, Martin %A Allignol, Arthur %A Harbarth, Stephan %A de Angelis, Giulia %A Schumacher, Martin %A Beyersmann, Jan %D 2012 %J Journal of clinical epidemiology %K Abortion AlzheimerDisease AlzheimerDisease:mortality CohortStudies CoronaryDisease CoronaryDisease:epidemiology CrossInfection CrossInfection:epidemiology DataInterpretation DiabetesMellitus DiabetesMellitus:epidemiology Female HeartTransplantation HeartTransplantation:mortality Humans LengthofStay LengthofStay:statistics&numericaldata LiverCirrhosis LiverCirrhosis:mortality Pregnancy ProportionalHazardsModels SelectionBias Spontaneous Spontaneous:epidemiology Statistical SurvivalAnalysis TimeFactors %N 11 %P 1171-80 %R 10.1016/j.jclinepi.2012.04.008 %T Time-dependent study entries and exposures in cohort studies can easily be sources of different and avoidable types of bias. %U http://www.sciencedirect.com/science/article/pii/S0895435612001175 http://www.ncbi.nlm.nih.gov/pubmed/23017635 %V 65 %X OBJECTIVES: To display and discuss the reasons and consequences of length and time-dependent bias. They might occur in presence of a time-dependent study entry or a time-dependent exposure which might change from unexposed to exposed. STUDY DESIGN AND SETTING: Recalling the popular study of Oscar nominees and using a real-data example from hospital epidemiology, we give innovative and easy-to-understand graphical presentations of how these biases corrupt the analyses via distorted time-at-risk. Cumulative hazard plots and Cox proportional hazards models were used. We are building bridges to medical disciplines such as critical care medicine, hepatology, pharmaco-epidemiology, transplantation medicine, neurology, gynecology and cardiology. RESULTS: In presence of time-dependent bias, the hazard ratio (comparing exposed with unexposed) is artificially underestimated. The length bias leads to an artificial underestimation of the overall hazard. When both biases coexist it can lead to different directions of biased hazard ratios. CONCLUSION: Since length and time-dependent bias might occur in several medical disciplines, we conclude that understanding and awareness are the best prevention of survival bias. %@ 0895-4356

@article{Wolkewitz2012, abstract = {OBJECTIVES: To display and discuss the reasons and consequences of length and time-dependent bias. They might occur in presence of a time-dependent study entry or a time-dependent exposure which might change from unexposed to exposed. STUDY DESIGN AND SETTING: Recalling the popular study of Oscar nominees and using a real-data example from hospital epidemiology, we give innovative and easy-to-understand graphical presentations of how these biases corrupt the analyses via distorted time-at-risk. Cumulative hazard plots and Cox proportional hazards models were used. We are building bridges to medical disciplines such as critical care medicine, hepatology, pharmaco-epidemiology, transplantation medicine, neurology, gynecology and cardiology. RESULTS: In presence of time-dependent bias, the hazard ratio (comparing exposed with unexposed) is artificially underestimated. The length bias leads to an artificial underestimation of the overall hazard. When both biases coexist it can lead to different directions of biased hazard ratios. CONCLUSION: Since length and time-dependent bias might occur in several medical disciplines, we conclude that understanding and awareness are the best prevention of survival bias.}, added-at = {2023-02-03T11:44:35.000+0100}, author = {Wolkewitz, Martin and Allignol, Arthur and Harbarth, Stephan and de Angelis, Giulia and Schumacher, Martin and Beyersmann, Jan}, biburl = {https://www.bibsonomy.org/bibtex/27ec85b5ae01b6917c9f11229390570a7/jepcastel}, doi = {10.1016/j.jclinepi.2012.04.008}, interhash = {65c9f06878cba5ef7a1415b9118aea4e}, intrahash = {7ec85b5ae01b6917c9f11229390570a7}, isbn = {0895-4356}, issn = {1878-5921}, journal = {Journal of clinical epidemiology}, keywords = {Abortion AlzheimerDisease AlzheimerDisease:mortality CohortStudies CoronaryDisease CoronaryDisease:epidemiology CrossInfection CrossInfection:epidemiology DataInterpretation DiabetesMellitus DiabetesMellitus:epidemiology Female HeartTransplantation HeartTransplantation:mortality Humans LengthofStay LengthofStay:statistics&numericaldata LiverCirrhosis LiverCirrhosis:mortality Pregnancy ProportionalHazardsModels SelectionBias Spontaneous Spontaneous:epidemiology Statistical SurvivalAnalysis TimeFactors}, month = {11}, note = {6935<m:linebreak></m:linebreak>Anàlisi de supervivència; Bias; Immortal time bias; Introductori}, number = 11, pages = {1171-80}, pmid = {23017635}, timestamp = {2023-02-03T11:44:35.000+0100}, title = {Time-dependent study entries and exposures in cohort studies can easily be sources of different and avoidable types of bias.}, url = {http://www.sciencedirect.com/science/article/pii/S0895435612001175 http://www.ncbi.nlm.nih.gov/pubmed/23017635}, volume = 65, year = 2012 }