2019
DOI: 10.1007/s40471-019-0180-5
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Immortal Time Bias in Epidemiology

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Cited by 31 publications
(44 citation statements)
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“…When the outcome is a function of time at risk, and time-varying exposures are assessed as though they occurred at the start of follow up (or in this case, at conception), immortal time bias can result. 49 To address this, we analysed time to birth as a survival outcome, first conducting descriptive analyses using Kaplan-Meier survival plots and then estimating time-varying Cox proportional hazard models stratified by census tract. 50 This approach allows the person-time in exposed and unexposed states to be accurately represented in the estimation and permits each census tract to have its own baseline hazard, analogous to including a fixed effect on each census tract.…”
Section: Discussionmentioning
confidence: 99%
“…When the outcome is a function of time at risk, and time-varying exposures are assessed as though they occurred at the start of follow up (or in this case, at conception), immortal time bias can result. 49 To address this, we analysed time to birth as a survival outcome, first conducting descriptive analyses using Kaplan-Meier survival plots and then estimating time-varying Cox proportional hazard models stratified by census tract. 50 This approach allows the person-time in exposed and unexposed states to be accurately represented in the estimation and permits each census tract to have its own baseline hazard, analogous to including a fixed effect on each census tract.…”
Section: Discussionmentioning
confidence: 99%
“…To prevent immortaltime bias-namely, considering hazard periods during which the study outcome cannot occur, time at risk was defined as the number of days when the persons were not hospitalised. 25 Hospitalisations separated by 1 day or less were concatenated into a single episode in order to avoid counting transfers from one hospital unit to another as separate admissions. Incidence rates and their 95% CIs were calculated per 100 personyears or per 100 person-weeks, as appropriate.…”
Section: Outcomementioning
confidence: 99%
“…We found a reduced survival time after testing in MAP ELISA test positive dairy cows. In our model the time from ELISA testing to culling was analyzed instead of the age at culling to avoid immortal time bias (37). Controlling for immortal time bias was necessary, because cattle had to remain in the herd for a sufficiently long time period to be tested (they could not be culled earlier, e.g., as heifers prior to testing).…”
Section: Cullingmentioning
confidence: 99%