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Calculation of reference values for lung function tests.

A Dirksen, S Groth

    Bulletin Europeen De Physiopathologie Respiratoire
    |May 1, 1986
    PubMed
    Summary
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    Simple regression models with logarithmic transformation effectively calculate lung function reference values. This method ensures data normality and accurately describes sex-based differences, offering a reliable standard for clinical use.

    Area of Science:

    • Pulmonary Medicine
    • Biostatistics

    Background:

    • Modern computing allows complex regression models for reference value calculation, but biological relevance is not guaranteed.
    • Establishing reliable reference values for lung function tests is crucial for clinical diagnosis.

    Purpose of the Study:

    • To evaluate the efficacy of simple regression models for calculating lung function reference values.
    • To determine if logarithmic transformation improves data suitability for regression analysis.

    Main Methods:

    • Collected lung function data from 74 healthy non-smoking females and 51 males using 22 common tests.
    • Applied logarithmic transformation to the lung function data.
    • Utilized linear regression analysis, incorporating a binary sex variable.

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    Main Results:

    • Logarithmic transformation significantly reduced residual variation and satisfied the normality assumption.
    • A simple binary sex variable adequately described inter-sex differences, independent of age, height, and weight.
    • Simple regression models proved effective in describing the lung function data.

    Conclusions:

    • Logarithmic transformation of lung function measurements followed by linear regression is a recommended standard method for calculating reference values.
    • This approach provides a biologically meaningful and statistically sound method for establishing lung function norms.