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Brinks R, Bardenheier BH, Hoyer A, et al. Development and demonstration of a state model for the estimation of incidence of partly undetected chronic diseases. BMC Med Res Methodol. 2015;15:98doi: 10.1186/s12874-015-0094-y.
Brinks, R., Bardenheier, B. H., Hoyer, A., Lin, J., Landwehr, S., & Gregg, E. W. (2015). Development and demonstration of a state model for the estimation of incidence of partly undetected chronic diseases. BMC medical research methodology, 1598. https://doi.org/10.1186/s12874-015-0094-y
Brinks, Ralph, et al. "Development and demonstration of a state model for the estimation of incidence of partly undetected chronic diseases." BMC medical research methodology vol. 15 (2015): 98. doi: https://doi.org/10.1186/s12874-015-0094-y
Brinks R, Bardenheier BH, Hoyer A, Lin J, Landwehr S, Gregg EW. Development and demonstration of a state model for the estimation of incidence of partly undetected chronic diseases. BMC Med Res Methodol. 2015 Nov 11;15:98. doi: 10.1186/s12874-015-0094-y. PMID: 26560517; PMCID: PMC4642685.
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BMC Med Res Methodol. 2015 Nov 11;15:98. doi: 10.1186/s12874-015-0094-y.

Development and demonstration of a state model for the estimation of incidence of partly undetected chronic diseases.

BMC medical research methodology

Ralph Brinks, Barbara H Bardenheier, Annika Hoyer, Ji Lin, Sandra Landwehr, Edward W Gregg

Affiliations

  1. German Diabetes Center, Institute for Biometry and Epidemiology, Auf'm Hennekamp 65, Düsseldorf, 40225, Germany. [email protected].
  2. Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, Georgia, United States of America. [email protected].
  3. German Diabetes Center, Institute for Biometry and Epidemiology, Auf'm Hennekamp 65, Düsseldorf, 40225, Germany. [email protected].
  4. Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, Georgia, United States of America. [email protected].
  5. University Hospital, Department for Statistics in Medicine, Düsseldorf, Germany. [email protected].
  6. Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, Georgia, United States of America. [email protected].

PMID: 26560517 PMCID: PMC4642685 DOI: 10.1186/s12874-015-0094-y

Abstract

BACKGROUND: Estimation of incidence of the state of undiagnosed chronic disease provides a crucial missing link for the monitoring of chronic disease epidemics and determining the degree to which changes in prevalence are affected or biased by detection.

METHODS: We developed a four-part compartment model for undiagnosed cases of irreversible chronic diseases with a preclinical state that precedes the diagnosis. Applicability of the model is tested in a simulation study of a hypothetical chronic disease and using diabetes data from the Health and Retirement Study (HRS).

RESULTS: A two dimensional system of partial differential equations forms the basis for estimating incidence of the undiagnosed and diagnosed disease states from the prevalence of the associated states. In the simulation study we reach very good agreement between the estimates and the true values. Application to the HRS data demonstrates practical relevance of the methods.

DISCUSSION: We have demonstrated the applicability of the modeling framework in a simulation study and in the analysis of the Health and Retirement Study. The model provides insight into the epidemiology of undiagnosed chronic diseases.

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