Literature DB >> 9542700

Determinants of cancer screening frequency: the example of screening for cervical cancer.

P S Frame1, J S Frame.   

Abstract

BACKGROUND: Cancer screening frequency should be based on the rate of progression of the disease and the sensitivity of the screening test. A common misconception is that a person's risk of getting the disease determines how often they should be screened.
METHODS: We describe algebraically the theoretical interaction of disease progression rate and screening test sensitivity determining the portion of invasive cancers prevented by screening. After discussing the assumptions and limitations of the model, we apply this model to the example of screening for cervical cancer. Actual data from large screening programs assembled by the International Agency for Research on Cancer (IARC) are used to test the assumptions of the model.
RESULTS: A simple formula can express the relation between disease progression rate, sensitivity of the screening test, screening frequency, and screening error. Disease prevalence does not figure in this equation. The IARC data suggest that, at least for cervical cancer, as screening frequency increases, incremental sensitivity of the test decreases or remaining undetected cases progress more rapidly so that anticipated benefits from more frequent screening are not realized.
CONCLUSIONS: Rate of disease progression and sensitivity of the screening test are the proper determinants of cancer screening frequency. Because these factors can vary depending on screening frequency, however, the optimal screening interval for a particular cancer must be determined by clinical trials.

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Mesh:

Year:  1998        PMID: 9542700     DOI: 10.3122/15572625-11-2-87

Source DB:  PubMed          Journal:  J Am Board Fam Pract        ISSN: 0893-8652


  3 in total

Review 1.  How can we develop a cost-effective quality cervical screening programme?

Authors:  Sue Wilson; Helen Lester
Journal:  Br J Gen Pract       Date:  2002-06       Impact factor: 5.386

2.  A progressive three-state model to estimate time to cancer: a likelihood-based approach.

Authors:  Eddymurphy U Akwiwu; Thomas Klausch; Henriette C Jodal; Beatriz Carvalho; Magnus Løberg; Mette Kalager; Johannes Berkhof; Veerle M H Coupé
Journal:  BMC Med Res Methodol       Date:  2022-06-27       Impact factor: 4.612

3.  The frequency of Pap smear screening in the United States.

Authors:  Brenda E Sirovich; H Gilbert Welch
Journal:  J Gen Intern Med       Date:  2004-03       Impact factor: 5.128

  3 in total

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