2020
DOI: 10.1183/13993003.00138-2020
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Avoiding immortal time bias in observational studies

Abstract: The study used population-based administrative data from the province of Quebec, Canada, to evaluate the association between inhaled corticosteroid (ICS) exposure and lung cancer risk in patients with COPD. The results of the study indicated that ICS use was not associated with lung cancer risk in this patient population.

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Cited by 5 publications
(3 citation statements)
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“…To avoid immortal time bias, 16 participants were transferred from the risk set who had not received a bivalent booster vaccination to the risk set who had received a bivalent booster vaccination at 7 days after receiving the vaccination, modifying their vaccination status from non-recipient to recipient. Consequently, the follow-up of participants who received a bivalent booster vaccination started at the end of the immortal period and lasted for a minimum of 14 days to allow sufficient time for hospitalisation events.…”
Section: Methodsmentioning
confidence: 99%
“…To avoid immortal time bias, 16 participants were transferred from the risk set who had not received a bivalent booster vaccination to the risk set who had received a bivalent booster vaccination at 7 days after receiving the vaccination, modifying their vaccination status from non-recipient to recipient. Consequently, the follow-up of participants who received a bivalent booster vaccination started at the end of the immortal period and lasted for a minimum of 14 days to allow sufficient time for hospitalisation events.…”
Section: Methodsmentioning
confidence: 99%
“…The initial visit for new patients and first prescription could help us to confirm if the patients are alive or not. These strict policies help us to eliminate the immortal time bias in this study ( Suissa and Ernst, 2020 ).…”
Section: Resultsmentioning
confidence: 99%
“…This additional eligibility restriction was necessary in order to avoid immortal time-bias as well as to reduce confounding by disease severity by only comparing these characteristics among opioid users. 41,42 To maintain an appropriate temporal sequence that properly places the exposure relative to when the outcome occurs, only patients who lled their rst post-discharge opioid prescription before they had their rst post-discharge ED encounter were included in the model. 43 Cohort entry for this model was time of rst dispensation to further reduce the opportunity for immortal time bias.…”
Section: Statistical Analysesmentioning
confidence: 99%