Overview of HIV Infection
Mark J. Rosen, James M. Beck in Human Immunodeficiency Virus and the Lung, 1998
Lead time bias occurs when a disease is diagnosed earlier in an asymptomatic person than if there were no evaluation, but the patient dies on the same date as he or she would have without screening. Survival from the time of diagnosis to the time of death is increased, but the outcome is identical. Length bias occurs when diseases that are detected by screening identifies persons with a better or more prolonged natural history than those diagnosed following symptoms. Overdiagnosis occurs when screening detects a disease that may never have been discovered during life, because subjects will die of other causes. Selection bias in screening is present when those who choose to be screened are at different risk than a general population in whom the screening test may be implemented (2).
Screening in Urology
Anthony R. Mundy, John M. Fitzpatrick, David E. Neal, Nicholas J. R. George in The Scientific Basis of Urology, 2010
The detection of disease during the DPCP by the screening test itself results in difficulties when attempts are made to judge the effectiveness of any single program. The time between the positive result of the screening test and the time at which clinical symptoms would have appeared is defined as the lead-time bias. It will be evident that if treatment for the disease is ineffective, the patient will die at the same point as if it had originally been detected because of clinical symptoms. Survival, however, will apparently have been increased by the amount of time between the positive screening test and the clinical presentation; hence, it is necessary to account for lead-time bias when assessing the efficacy of screening for any particular disease (10). For severe chronic disease such as cancer, the elimination of leadtime bias is best achieved by randomized controlled trials of the screening program, as described below.
Introduction to the management station
Sukhpreet Singh Dubb in Core Surgical Training Interviews, 2020
Even after a suitable screening tool is made available, there are a number of important factors that still must be considered: Feasibility: This describes the ease with which a population can be screened using the test, its acceptability and whether resources are available to follow-up the results of the screening (e.g., investigations).Effectiveness: This is measured by the outcomes of a screening programme once it is executed, and is difficult to assess due to various types of bias; among others, these include: Selection bias: Participants of screening programmes are generally different from those that do not volunteerLead time bias: Here, a screening programme correctly identifies a disease and gives the impression that survival has been extended due to early recognition. However, such patients would have been identified later due to various reasons (manifestation of disease, symptoms, signs, etc.). The screening programme therefore does not actually improve survival or prognosis, but simply identifies the disease earlier.
Changes in mortality associated with cancer drug approvals in the United States from 2000 to 2016
Published in Journal of Medical Economics, 2020
Joanna P. MacEwan, Syvart Dennen, Rebecca Kee, Farzad Ali, Jason Shafrin, Katharine Batt
Using cancer mortality, rather than survival, as the primary endpoint of interest has several advantages. Unlike survival rates, cancer mortality rates are not affected by lead-time bias, overdiagnosis, and stage migration, providing a clearer measure of cancer outcomes27,44,45. Lead-time bias refers to an inflation of survival rates when improvements in screening appear to increase survival time by detecting malignancies earlier, without actually prolonging survival beyond the usual course of disease. Stage migration occurs when improvements in diagnostic techniques result in variations in tumor staging, thus affecting stage-specific survival45. However, cancer mortality rates may be influenced by other general population health trends, such as smoking rates, age distribution of the population, and cancer screening practices (although screening has shown negligible mortality impact for some cancer types, e.g. prostate cancer46,47) To control for these factors and differentiate them from the impact of drug approvals, we controlled for tumor-specific cancer incidence, which is driven by these underlying population-level trends.
Prostate cancer specific mortality after 5α-reductase inhibitors medication in benign prostatic hyperplasia patients: systematic review and meta-analysis
Published in The Aging Male, 2021
Jae Joon Park, Hyun Young Lee, Sung Ryul Shim, Sang Wook Lee, Kwang Taek Kim, Jae Heon Kim
Among the studies included in our meta-analysis, Sarker et al.'s 2019 study [26] had exceptionally high rates of death from cancer and from all causes. Conceivable causes of such high death rates include lead-time bias and misclassification. First, lead-time bias means that ifthe diagnosis is delayed, the time to death is short;so the deathrate for the disease may beoverestimated. We set the PSA of 4 ng/ml or more as the standard for elevated PSA to measure the time until prostate biopsy was done. This standard PSA value is higher than that of other included studies. So, in this study, the death rate may have been overestimatedbecause of lead-time bias. On the other hand, in this paper, we calculated the death rate from specific causesusing the National Death Index, but as mentioned, the cause of death may have been misclassified; so there may be differences from the actual rate of death from cancer. Considering these points, lower OR values may have been reported than we found in this meta-analysis; so5-ARI administration and deaths fromprostatecancer may have a lower association.
The role of transvaginal ultrasound in screening for ovarian cancer
Published in Climacteric, 2018
S. Campbell, A. Gentry-Maharaj
Demonstrating a stage shift towards detection of iEOC at stage I/II is not sufficient to imply an improvement in rates of mortality from this condition. Lead- and length-time biases can give a false impression that screening is working. Early detection through screening (with either the multimodal or ultrasound strategy) may not necessarily translate into a mortality benefit, as this lead-time bias is impacted by many factors, including treatment delivered. If the cancers detected at an earlier stage have surgery with a curative intent, then the opportunity to impact on mortality is much greater. Therefore, to prove a mortality benefit in terms of 5-year survival that is attributable to screening, an unscreened control group is required and numbers have to be sufficiently large to show an effect. This review will focus on such studies.
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