Literature DB >> 29796623

The Screening Illustrator: separating the effects of lead-time and overdiagnosis in mammography screening.

Mette L Lousdal1, Mette H Møller1, Ivar S Kristiansen2, Mette Kalager2,3, Torbjørn Wisløff2,4, Henrik Støvring1.   

Abstract

Background: Mammography screening increases incidence because cancers are detected earlier in time and because of overdiagnosis. We developed an Excel-based model to visualize the expected increase from lead-time amplified by increasing background incidence. Subsequently, we added overdiagnosis to the model.
Methods: We constructed two hypothetical populations of women aged 50-79 in 5-year age and calendar groups: one with screening for women aged 50-69 and one without. The user enters information on population at risk, number of breast cancers, trends in background incidence, average length of lead-time and, optionally, overdiagnosis. The model computes incidence rate ratios (IRRs) comparing incidence changes with screening to changes without in open and closed cohorts.
Results: We entered information from Norway from 1990 to 1994, the period preceding the gradual introduction of a national mammography screening programme. As expected, the Screening Illustrator showed prevalence peaks and compensatory drops. Only the closed cohort approach remained unaffected by increasing background incidence. The model showed a 20% sustained increase in incidence (IRR: 1.20) from lead-time and increasing background incidence in the open cohort approach for women aged 50-69. However, real life Norwegian data show a corresponding 38% increase. For the model to achieve the observed incidence, 10-14% overdiagnosis had to be added.
Conclusion: The observed breast cancer incidence increase in Norway after screening implementation could not be obtained from an average lead-time of 2.5 years and empirical background incidence trends, but had to incorporate overdiagnosis.

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Year:  2018        PMID: 29796623     DOI: 10.1093/eurpub/cky085

Source DB:  PubMed          Journal:  Eur J Public Health        ISSN: 1101-1262            Impact factor:   3.367


  2 in total

1.  Temporal trends and regional disparities in cancer screening utilization: an observational Swiss claims-based study.

Authors:  Caroline Bähler; Beat Brüngger; Agne Ulyte; Matthias Schwenkglenks; Viktor von Wyl; Holger Dressel; Oliver Gruebner; Wenjia Wei; Eva Blozik
Journal:  BMC Public Health       Date:  2021-01-05       Impact factor: 3.295

2.  The respective parts of incidence and lethality in socioeconomic differences in cancer mortality. An analysis of the French network Cancer registries (FRANCIM) data.

Authors:  Joséphine Bryere; Laure Tron; Gwenn Menvielle; Guy Launoy
Journal:  Int J Equity Health       Date:  2019-12-03
  2 in total

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