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Related Concept Videos

Assessment of the Mouth01:26

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Differential Misclassification of Disease under Partial-Mouth Sampling.

J S Preisser1, A E Sanders2, R H Lyles3

  • 11 Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.

JDR Clinical and Translational Research
|April 2, 2019
PubMed
Summary

Partial-mouth sampling can misclassify disease presence, leading to biased estimates of disease-exposure associations. This occurs because sensitivity varies by exposure status, potentially over or underestimating risks in periodontal research.

Keywords:
attachment losschronic periodontitisepidemiologyoral diagnosisprevalencesensitivity

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Area of Science:

  • Biostatistics
  • Epidemiology
  • Dental Public Health

Background:

  • Partial-cluster sampling, common in periodontal research, involves examining a subset of observations (e.g., tooth sites) within a cluster (e.g., full mouth).
  • Accurate disease classification is crucial for valid epidemiological studies, especially when assessing associations with exposures.
  • Previous studies have not fully addressed the impact of partial-mouth sampling on disease misclassification and subsequent exposure association bias.

Purpose of the Study:

  • To investigate the effect of cluster-level disease misclassification, arising from partial-cluster sampling, on the association with a cluster-level dichotomous exposure.
  • To analyze how partial-mouth sampling influences disease misclassification probabilities, including sensitivity and negative predictive values.
  • To evaluate the potential for bias in disease-exposure associations estimated using partial-recording protocols compared to full-cluster sampling.

Main Methods:

  • Utilized conditional probability arguments to model disease misclassification under partial-cluster sampling.
  • Investigated the impact of misclassification on the estimated association between a cluster-level dichotomous outcome (disease) and a dichotomous exposure.
  • Employed a numeric example to demonstrate bias in odds ratios under partial-cluster random sampling versus full-cluster sampling.

Main Results:

  • Disease misclassification at the cluster level is generally differential under partial-cluster sampling when disease probability varies by exposure status.
  • The degree of misclassification depends on the sampling protocol, joint probability structure of the condition within clusters, and the disease criterion.
  • Disease-exposure odds ratios can be biased in either direction (toward or away from the null) compared to gold-standard estimates from full-cluster sampling.

Conclusions:

  • Partial-mouth sampling leads to differential misclassification of disease, where sensitivity and negative predictive values are exposure-dependent.
  • This differential misclassification results in biased inference for disease-exposure associations.
  • Standard analysis procedures may under- or overestimate associations in periodontal data; methods addressing bias in partial-recording protocols are necessary.