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Table 5 Solutions proposed by Hernan et al. to address the risk of bias when time points of eligibility, treatment assignment, and the start of follow-up are not aligned

From: Risk of bias in observational studies using routinely collected data of comparative effectiveness research: a meta-research study

Situations Possible solutions
a. Follow-up starts after eligibility criteria completion and treatment assignment which leads to prevalent user bias.
Select new users [12].
b. Follow-up starts at eligibility but after treatment assignment which leads to prevalent user bias and selection bias due to post-treatment eligibility.
Select new users and ensure that individuals are not selected by an event that happens after the follow-up starts [12].
c. Follow-up starts before treatment assignment and eligibility which leads to immortal time bias and selection bias due to post-treatment eligibility.
Keep all individuals who start the treatment since the start of follow-up, create an exact copy of the population, assign them to one of the intervention groups from the start of the follow-up, and censor when they start to deviate from assigned treatment [39].
One strategy which is often used to account for immortal time bias in literature is to consider exposure as a time-dependent variable. However, this strategy is not adequate to address the risk of selection bias due to post-treatment eligibility, as an uncensored group might not be exchangeable with the censored group [3].
d. Follow-up starts at eligibility, but treatment is assigned later which leads to immortal time bias and misclassification of treatment.
1) Randomly assign individuals to one of the treatment strategies [12].
2) Create an exact copy of the population, assign them to one of the intervention groups from the start of the follow-up, and censor when they start to deviate from assigned treatment [39].
One strategy which is often used to account for immortal time bias is to consider exposure as a time-dependent variable. However, this strategy is inadequate to address the risk of misclassification, because if individuals have outcomes during the grace period, we are uncertain which intervention group they should be classified into.