command time bias

A distortion overestimating the evident time making it through with a an illness caused by happen forward the moment of that diagnosis


Background

The premise of screening is that it enables earlier detection and treatment that a disease or wellness condition, causing a greater chance of healing or at the very least longer survival. A an illness or problem is clinically diagnosed ~ an separation, personal, instance display’s certain signs and symptoms. People with disease detected through population screening receive a diagnosis earlier before signs and symptoms appear. Together a consequence, estimates of distinctions in survival time between people diagnosed native screening and those whose an illness is detected ~ symptoms build can be biased, as survival time will appear to be longer in screen-detected world if beforehand detection has no impact on the food of an illness (figure 1) or if survival time is prolonged (figure 2). Command time predisposition is not the exception however the dominance that comes with any successful initiative to detect an illness early.

You are watching: Lead time bias is best described as:

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Figure 1. lead time prejudice where health and wellness outcome is the same in someone whose condition is detected by screening contrasted with someone whose condition is detected indigenous symptoms, but survival time from the moment of diagnosis is longer in the screened patient.

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Figure 2. command time predisposition where the screened patience lives much longer than the unscreened patient, but as whole survival time is still exaggerated by the lead time from earlier diagnosis.

Example

Badgwell and also colleagues compared survival in women with breast cancer, aged 80 year or enlarge that had actually accessed mammography screening regularly, irregularly or not at every in the 5 years before their diagnosis. Using a Medicare linked database, castle reported that statistically far-reaching improvements in overall and breast cancer-specific survive were connected with increasing use the mammography screening. Chest cancer–specific 5-year survival was 82% among women no screened, 88% amongst women v irregular and 94% among regular individuals of screening. In response, Berry et al provided that although the authors had recognised the their examine was subject to healthy and balanced person prejudice (where healthy and balanced patients tend to access screening), they had failed come take into account lead time bias. As lead time predisposition adds to the survival time that all women whose tumours to be detected through screening, boost in survival in the screened cohort compared to unscreened group is expected, and without appropriate adjustment, the it was observed difference can not be concluded together a survival benefit from screening. Media coverage that the mammography study conveyed stronger conclusions than probably the writer intended detailed Berry et al, aided by a “misleading” push release native the American society of Clinical Oncology which additionally failed come account because that lead time bias.

Impact

The benefits of early detection room often communicated to doctors and patients in the kind of expanded survival times. Expanded survival may occur since early detection is effective however some the the observed benefit will be because of lead time bias. Therefore, without correcting because that lead time, longer survival is no necessarily evidence of the advantage of early detection. This does no seem extensively understood, even among health professionals and educators. In a inspection of 297 primary care doctors presented with outcomes from two hypothetical screening tests, 76% considered much better survival as evidence that screening works. One observational study assessing statistical literacy in medical education and learning settings found 50% that the 16 college professors and an elderly medical educators had failed to recognize lead-time bias when presented.

Preventive steps

In randomised control trials examining screening, lead time predisposition can it is in countered by taking the time beginning as the suggest of randomisation, not the point of diagnosis, or by to compare the variety of deaths emerging in a given duration of time rather or and the number of people surviving. In observation settings, an alternate time origin to the of diagnosis may not be possible and comparisons of survival need adjustment because that lead time bias. One such an approach is offered by Duffy and colleagues. This an approach attempts to calculation the lead time predisposition for every patient and also subtract this native the observed survival or censoring time to develop a bias-adjusted as whole survival time (figure 3). The authors applied their method to data from the sweden Two-County study of breast cancer screening. After correction for lead time bias, the survival curve is lower than the uncorrected curve, suggesting that the positive effect of screening would otherwise have actually been overestimated.

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Figure 3. Hypothetical instance showing survival with unscreened (symptomatic) and screen-detected cases before and also after correction because that lead time.


Cite as

Catalogue of prejudice Collaboration. Oke J, Fanshawe T, Nunan D. Lead time bias. In Catalogue that Bias. 2021. Https://wgc2010.org/biases/lead-time-bias/

Related biases


Cite as

Catalogue of prejudice Collaboration. Oke J, Fanshawe T, Nunan D. Lead time bias. In Catalogue that Bias. 2021. Https://wgc2010.org/biases/lead-time-bias/


Sources

Morrison AS. The results of early on treatment, command time and also length prejudice on the mortality competent by situations detected by screening. Int J Epidemiol. 1982;11(3):261-7.

Welch HG, Woloshin S, Schwartz LM, Gordis L, Gotzsche PC, Harris R, et al. Overstating the evidence for lung cancer screening: the International beforehand Lung Cancer action Program (I-ELCAP) study. Arch Intern Med. 2007;167(21):2289-95.

Badgwell BD, Giordano SH, Duan ZZ, Fang S, Bedrosian I, Kuerer HM, et al. Mammography before Diagnosis among Women period 80 Years and also Older with Breast Cancer. Journal of Clinical Oncology. 2008;26(15):2482-8.

Berry DA, Baines CJ, Baum M, Dickersin K, Fletcher SW, Gøtzsche PC, et al. Flawed Inferences about Screening Mammography’s Benefit based upon Observational Data. Journal of Clinical Oncology. 2009;27(4):639-40.

Wegwarth O, Schwartz LM, Woloshin S, Gaissmaier W, Gigerenzer G. Do Physicians know Cancer Screening Statistics? A nationwide Survey that Primary treatment Physicians in the joined States. Ann Intern Med. 2012;156(5):340-U152.

Jenny MA, Keller N, Gigerenzer G. Assessing minimal clinical statistical literacy using the fast Risk Test: a prospective observational examine in Germany. BMJ open up 2018;8:e020847.

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Duffy SW, Nagtegaal ID, Wallis M, Cafferty FH, Houssami N, Warwick J, et al. Correcting for lead time and length prejudice in estimating the effect of display detection on cancer survival. Am J Epidemiol. 2008;168(1):98-104.