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Comparison of different data analyses for detecting changes in attachment level.

A D Haffajee, S S Socransky, J M Goodson

    Journal of Clinical Periodontology
    |May 1, 1983
    PubMed
    Summary
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    This study compared three methods for detecting periodontal disease activity. The tolerance and running median methods showed higher agreement in identifying active disease sites, particularly on molars and incisors.

    Area of Science:

    • Periodontology
    • Dental Research
    • Biostatistics

    Background:

    • Detecting active periodontal disease progression is crucial for effective treatment.
    • Accurate measurement of attachment level changes over time is key to monitoring disease activity.
    • Existing methods for analyzing attachment level data have varying sensitivities and specificities.

    Purpose of the Study:

    • To evaluate and compare three analytical procedures for detecting destructive periodontal disease activity.
    • To assess the reliability and agreement between regression analysis, running medians, and the tolerance method.
    • To identify the most effective method for detecting changes in attachment levels at individual tooth sites.

    Main Methods:

    • Attachment level measurements were taken at 6 sites per tooth in 22 patients with periodontal destruction.

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  • Measurements were repeated within 7 days and monitored at 2-month intervals for approximately 1 year (3414 sites total).
  • Three analytical procedures were employed: linear regression analysis, running medians (2 mm threshold), and the tolerance method.

    • Main Results:

    • The tolerance and running median methods demonstrated the highest specific agreement (Ps = 0.63) for identifying breakdown sites.
    • Regression analysis identified more sites with significant attachment loss (175) and improvement (79) compared to running medians (90/50) and tolerance (94/40).
    • Running medians detected abrupt changes, regression analysis detected gradual slope changes, and the tolerance method was suited for short-term changes.

    Conclusions:

    • The tolerance and running median methods are effective in detecting active periodontal disease, especially on molars, lower incisors, and interproximal surfaces.
    • Each method possesses unique strengths: regression for gradual changes, running medians for abrupt shifts, and tolerance for short-term fluctuations.
    • The choice of method depends on the specific clinical scenario and the type of periodontal change being investigated.