This major difference in study design and immortal time bias might explain the discrepant results between the REVEAL Registry and the COMPERA-derived analyses in IPAH patients.
In this review, we present an example of four potentially important biases (lead time bias, survivor bias, immortal time bias, and index event bias) that can result in inaccurate estimates of association between risk factors or treatments and outcomes.
We call that lead time bias or stage migration.
Positive values of reaction time bias scores signified attentional bias toward food, negative values a bias away from food.
Time-related biases include immortal time bias, a bias introduced with time-fixed cohort analyses that misclassify unexposed time as exposed; time-window bias, a bias introduced because of differential exposure opportunity time windows between subjects; and time-lag bias, a bias introduced by comparing treatments given at different stages of the disease (1, 2).
We also adjusted for lead time bias.
This could help adjust for lead-time bias, comparison between centers and management policies.
Finally, gastric cancer screening efficacy cannot be directly estimated by cancer stage, as there might be a gap related to lead-time bias and length bias between cancer stage and mortality.
This is compounded by different healthcare settings, different methods of measuring delays, the potential confounding effect of lead-time bias, and variations between cancers; and is reflected in the conflicting findings from this literature.
The relationship between lead-time bias vs a difference in the biology of screen-detected and interval CRCs and the outcome of patients remains unknown, therefore a further detailed analysis of the biology of screen and post FOBt interval cancers is planned.
