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- In randomised control trials evaluating screening, lead time bias can be countered by taking the time origin as the point of randomisation, not the point of diagnosis, or by comparing the number of deaths occurring in a given period of time instead or as well as the number of people surviving.
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In randomised control trials evaluating screening, lead time bias can be countered by taking the time origin as the point of randomisation, not the point of diagnosis, or by comparing the number of deaths occurring in a given period of time instead or as well as the number of people surviving.
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Is comparing survival time between screened and unscreened a lead time bias?
Mar 27, 2020 · Lead‐time bias causes problems when the survival of patients with a particular disease is being compared between regions with and without screening programmes. In nephrology, it has become widely known as a problem of cohort studies comparing policies of early and late start of dialysis.
- Kitty J. Jager, Giovanni Tripepi, Nicholas C. Chesnaye, Friedo W. Dekker, Carmine Zoccali, Vianda S....
- 10.1111/nep.13706
- 2020
- 2020/06
Lead-time bias can be reduced by comparing actual mortality rates in screened and unscreened populations [64]. Survival should not be used as a measure of screening effectiveness. Detecting disease earlier in life without any benefit in prognosis may have a negative impact on quality of life.
Lead time bias occurs if testing increases the perceived survival time without affecting the course of the disease. Lead time bias happens when survival time appears longer because diagnosis was done earlier (for instance, by screening), irrespective of whether the patient lived longer.
How to avoid lead time bias. We can correct for lead time bias in 2 ways: Solution #1: Get an estimate of the lead time. If we can estimate the lead time, then instead of comparing survival between screened and unscreened, we can compare: (Survival in the screened group) versus (Survival in the unscreened group + our estimate of the lead time).
Dec 25, 2023 · The authors use a method to correct for lead-time bias described by Duffy et al. and a conservative mean tumor sojourn time of 4.3 years for the preclinical screen-detectable period in the Dutch population, resulting in maximum adjusted lead times of 2.0 to 6.1 years for their study cohort.
Lead-time and length-time bias are critical in analysing clinical trials involving time-to-event analysis. This article aims to simplify the concepts of lead-time and length-time bias and some solutions for controlling them.
