Comparison of surveillance-based metrics for the assessment and monitoring of disease detection: simulation study about type 2 diabetes
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Comparison of surveillance-based metrics for the assessment and monitoring of disease detection: simulation study about type 2 diabetes

Filetype[PDF-1.28 MB]


  • English
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    Details:

    • Alternative Title:
      BMC Med Res Methodol
    • Personal Author:
    • Description:
      Background

      Screening and detection of cases are a common public health priority for treatable chronic conditions with long subclinical periods. However, the validity of commonly-used metrics from surveillance systems for rates of detection (or case-finding) have not been evaluated.

      Methods

      Using data from a Danish diabetes register and a recently developed illness-death model of chronic diseases with subclinical conditions, we simulate two scenarios of different performance of case-finding. We report different epidemiological indices to assess case-finding in both scenarios and compare the validity of the results.

      Results

      The commonly used ratio of detected cases over total cases may lead to misleading conclusions. Instead, the ratio of undetected cases over persons without a diagnosis is a more valid index to distinguish the quality of case-finding. However, incidence-based measures are preferable to prevalence based indicators.

      Conclusion

      Prevalence-based indices for assessing case-finding should be interpreted with caution. If possible, incidence-based indices should be preferred.

      Electronic supplementary material

      The online version of this article (doi:10.1186/s12874-017-0328-2) contains supplementary material, which is available to authorized users.

    • Subjects:
    • Source:
      BMC Med Res Methodol. 17.
    • Pubmed ID:
      28399821
    • Pubmed Central ID:
      PMC5387346
    • Document Type:
      Journal Article
    • Place as Subject:
      Denmark
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    • Main Document Checksum:
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    • File Type:

    Supporting Files

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    Datasets

      • Additional file 1 of Comparison of surveillance-based metrics for the assessment and monitoring of disease detection: simulation study about type 2 diabetes
        Dataset Icon
        Cite
        Filetype[HTM]
        Personal Author:
        Brinks, Ralph ;
        Gregg, Edward W.
        ...
        2017
        04/12/2017
        Description:
        Scripts for the statistical software R. The zip-file contains the analysis for the simulation. For detailed instructions unzip the file and refer to t...
        File Type:
        Filetype[HTM]
        File Type:
        Filetype[HTM]

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