Literature DB >> 10529025

A novel form of ascertainment bias in case-control studies of cancer screening.

T R Church1.   

Abstract

In case-control studies of cancer screening, some have generally admonished investigators against case definitions based on diagnosis dates because of lead-time bias. However, perhaps partly due to vagueness, the admonitions have been frequently ignored. A recurrence-time model simulates case ascertainment when diagnosis must occur within a specific calendar period. The model depends on screening test sensitivity and rate, age-specific preclinical incidence rates, and preclinical duration time and survival time distributions. For one study of sigmoidoscopic screening for colorectal cancer, when the true odds ratio is 1, its estimate is 0.50 to 0.75 under plausible assumptions. This bias can affect any observational study wherein case definition depends on diagnosis times (e.g., health-plan enrollment data). To avoid bias in observational investigations of cancer screening wherein the case definition depends on the diagnosis date, one must ensure that both screening and preclinical incidence do not occur before the case definition period.

Entities:  

Mesh:

Year:  1999        PMID: 10529025     DOI: 10.1016/s0895-4356(99)00073-6

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  3 in total

1.  Observational methods to assess the effectiveness of screening colonoscopy in reducing right colon cancer mortality risk: SCOLAR.

Authors:  Michael Goodman; Robert H Fletcher; V Paul Doria-Rose; Christopher D Jensen; Alexis M Zebrowski; Tracy A Becerra; Virginia P Quinn; Ann G Zauber; Douglas A Corley; Chyke A Doubeni
Journal:  J Comp Eff Res       Date:  2015-07-23       Impact factor: 1.744

2.  Quantifying lead-time bias in risk factor studies of cancer through simulation.

Authors:  Rick J Jansen; Bruce H Alexander; Kristin E Anderson; Timothy R Church
Journal:  Ann Epidemiol       Date:  2013-08-27       Impact factor: 3.797

3.  A mathematical model of case-ascertainment bias: Applied to case-control studies nested within a randomized screening trial.

Authors:  Rick J Jansen; Bruce H Alexander; Richard B Hayes; Anthony B Miller; Sholom Wacholder; Timothy R Church
Journal:  PLoS One       Date:  2018-03-19       Impact factor: 3.240

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.