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A new biological variation (BV)-based model for population-based reference intervals (popRIs) provides robust results using fewer individuals. This approach offers a more efficient method for establishing clinical laboratory reference intervals.

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Area of Science:

  • Clinical Chemistry
  • Hematology
  • Biostatistics

Background:

  • Conventional population-based reference intervals (popRIs) rely on large sample sizes (≥120 individuals).
  • Establishing accurate popRIs is crucial for interpreting laboratory test results.

Purpose of the Study:

  • To explore a novel model for popRIs utilizing biological variation (BV) data.
  • To compare BV-based popRIs with conventional popRIs using varying sample sizes.

Main Methods:

  • A BV-based model was developed using population set point (PSP) and total variation (BV + analytical variation).
  • BV-based popRIs were calculated for 48 measurands using sample sizes of n=16, n=30, and n=120.
  • Simulation studies estimated the minimum number of reference individuals required.

Main Results:

  • The median ratio of BV-based to conventional RI ranges was 0.98.
  • BV-based popRIs were similar across different sample sizes and generally met the 90% coverage criterion.
  • Fewer individuals were needed to estimate the PSP for most measurands compared to conventional methods.

Conclusions:

  • The BV-based popRI model yields robust reference intervals for most measurands.
  • This model requires a smaller reference group than conventional popRIs.
  • Implementation is feasible with reliable biological variation data.