Literature DB >> 29186461

Advancing the evaluation of cervical cancer screening: development and application of a longitudinal adherence metric.

Kine Pedersen1, Emily A Burger1,2, Suzanne Campbell3, Mari Nygård3, Eline Aas1, Stefan Lönnberg3.   

Abstract

Background: Attendance to routine cancer screening at repeated intervals is essential for reducing morbidity and mortality of targeted cancers, yet currently defined quality-assurance metrics evaluate coverage within a defined period of time (e.g. 3.5 years).
Methods: We developed a longitudinal adherence metric that captures attendance to cancer screening at repeated intervals, and applied the metric to population-based data from the Cancer Registry of Norway that captures two decades of organised cervical cancer screening, including all screening tests and cervical cancer diagnoses for women living in Norway at any time during years 1992-2013 and eligible for at least two screening rounds (1 round = 3.5 years, N = 1 391 812). For each woman, we calculated the proportion of eligible screening rounds with at least one registered cytology test, and categorised women into one of five longitudinal adherence categories: never-screeners, severe under-screeners, moderate under-screeners, guidelines-based screeners and over-screeners. For each category, we evaluated cancer outcomes such as cancer stage at diagnosis.
Results: Only 46% of screen-eligible women were consistently screened at least once every 3.5 years, and the majority of these were over-screened. In contrast, 29% were moderately under-screened, 17% were severely under-screened and 8% had never attended screening. Screening behaviour was associated with cancer outcomes; e.g., the proportion of cancers diagnosed at Stage I increased from 21% among never-screeners to 70% among over-screeners.
Conclusion: The longitudinal adherence metric evaluates screening performance as a succession of screening episodes, reflecting both guidelines and the fundamental principles of screening, and may be a valuable addition to existing performance indicators.
© The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

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Year:  2017        PMID: 29186461     DOI: 10.1093/eurpub/ckx073

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


  1 in total

1.  Towards a data-driven system for personalized cervical cancer risk stratification.

Authors:  Geir Severin R E Langberg; Jan F Nygård; Vinay Chakravarthi Gogineni; Mari Nygård; Markus Grasmair; Valeriya Naumova
Journal:  Sci Rep       Date:  2022-07-15       Impact factor: 4.996

  1 in total

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