Literature DB >> 7129740

The effects of early treatment, lead time and length bias on the mortality experienced by cases detected by screening.

A S Morrison.   

Abstract

This paper describes a means of analysing the effects that the benefit of early treatment, lead time and length-biased sampling (and other forms of prognostic selection bias) have on the mortality rate of cases detected in screening programmes. Both benefit and lead time reduce the mortality rate of screen-detected cases. A beneficial effect of early treatment will lead to a decrease in the number of deaths, the numerator of the rate. The amount of person-time among screen-detected cases, the denominator, is increased by early diagnosis as a result of screening (lead-time) as well as by prolongation of life due to early treatment. The numbers of cases experiencing benefit and lead time can be estimated by comparisons of the numbers of deaths and numbers of diagnosed cases between the entire screened population, from which the series of screen-detected cases is drawn, and an otherwise comparable unscreened population. Benefit and lead time, as reflected in these numbers, can be removed from the mortality rate of cases detected by screening. The effects of benefit or lead time on prognosis then can be assessed by comparing the observed mortality rate of screen-detected cases to the rates with benefit or lead time removed. Prognostic selection bias (a tendency of screen-detected cases to be relatively benign or relatively malignant) can be evaluated by comparing the case-mortality rate, with both benefit and lead time removed, to the mortality rate of cases in an unscreened population. The relationships described are illustrated with data from a breast cancer screening programme.

Entities:  

Mesh:

Year:  1982        PMID: 7129740     DOI: 10.1093/ije/11.3.261

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN: 0300-5771            Impact factor:   7.196


  14 in total

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Journal:  Circ Heart Fail       Date:  2012-01-23       Impact factor: 8.790

2.  Time for evidence-based screening?

Authors:  L Smeeth
Journal:  J R Soc Med       Date:  1998-07       Impact factor: 5.344

3.  Harms and Benefits of Cancer Screening.

Authors:  Bernt-Peter Robra
Journal:  Recent Results Cancer Res       Date:  2021

4.  Proportional incidence and radiological review of large (T2+) breast cancers as surrogate indicators of screening programme performance.

Authors:  S Ciatto; D Bernardi; M Pellegrini; G Borsato; P Peterlongo; M A Gentilini; F Caumo; A Frigerio; N Houssami
Journal:  Eur Radiol       Date:  2011-12-27       Impact factor: 5.315

5.  Method of detection and breast cancer survival disparities in Hispanic women.

Authors:  Deirdre A Hill; Andrea Nibbe; Melanie E Royce; Anne Marie Wallace; Huining Kang; Charles L Wiggins; Robert D Rosenberg
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2010-09-14       Impact factor: 4.254

6.  Lead-time bias in esophageal cancer screening in high-risk areas in China.

Authors:  Zhao Yang; Irene Ol Wong; Wei Deng; Ru Chen; Jiachen Zhou; Wenqiang Wei
Journal:  Chin J Cancer Res       Date:  2020-08       Impact factor: 4.026

7.  Moving beyond the national lung screening trial: discussing strategies for implementation of lung cancer screening programs.

Authors:  Bernardo H L Goulart; Scott D Ramsey
Journal:  Oncologist       Date:  2013-07-19

8.  Prognostic role of detection method and its relationship with tumor biomarkers in breast cancer: the university of Texas M.D. Anderson Cancer Center experience.

Authors:  Wenli Dong; Donald A Berry; Therese B Bevers; Shu-Wan Kau; Limin Hsu; Richard L Theriault; Yu Shen
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2008-05       Impact factor: 4.254

9.  Baseline and annual repeat rounds of screening: implications for optimal regimens of screening.

Authors:  Claudia I Henschke; Mary Salvatore; Matthew Cham; Charles A Powell; Larry DiFabrizio; Raja Flores; Andrew Kaufman; Corey Eber; Rowena Yip; David F Yankelevitz
Journal:  Eur Radiol       Date:  2017-10-05       Impact factor: 5.315

10.  Cost of a 5-year lung cancer survivor: symptomatic tumour identification vs proactive computed tomography screening.

Authors:  A W Castleberry; D Smith; C Anderson; A J Rotter; F W Grannis
Journal:  Br J Cancer       Date:  2009-08-18       Impact factor: 7.640

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