Designing quality control for neonatal screening assays

Else-Maj R Suolinna1, Toni E Torresani, James O Westgard

  • 1PerkinElmer Life Sciences Wallac, Turku, Finland.

Insights

Neonatal screening identifies high-risk infants using cut-off values. EZ Rules software optimizes quality control rules for assays like AutoDELFIA neoTSH, ensuring accurate diagnosis and treatment.

Area of Science:

  • Clinical Chemistry
  • Laboratory Quality Control
  • Neonatal Screening

Background:

  • Neonatal screening aims to identify infants at high risk for disorders, requiring further diagnostic and treatment actions.
  • Test result interpretation relies on cut-off values to separate high-risk from low-risk groups.
  • A grey zone between low and high cut-offs can define assay quality requirements.

Purpose of the Study:

  • To utilize the EZ Rules software for automatically selecting quality control (QC) rules for neonatal screening assays.
  • To establish an appropriate QC rule for the AutoDELFIA neoTSH assay using a defined grey zone.

Main Methods:

  • Employed EZ Rules software, which calculates control rules based on user-inputted assay precision, bias, and preanalytical variation.
  • Defined the medical decision interval using the grey zone (10-20 mU/L TSH) as recommended by the American Academy of Pediatrics.
  • Inputted parameters for the AutoDELFIA neoTSH assay: 9% total imprecision, 0% bias, and 20% preanalytical variation, with two controls.

Main Results:

  • The EZ Rules software calculated a 1 3.0 s rule as sufficient for the AutoDELFIA neoTSH assay with two controls.
  • This rule ensures runs are rejected only if one of two controls exceeds the 3.0 standard deviation limit.
  • The study highlights that many labs use less effective 2 SD rules, leading to unnecessary rejections.

Conclusions:

  • EZ Rules software provides a valuable tool for selecting appropriate QC rules, optimizing laboratory efficiency.
  • A 1 3.0 s rule with two controls is adequate for the AutoDELFIA neoTSH assay, improving accuracy and reducing false rejections.
  • Implementing optimized QC rules is crucial for reliable neonatal screening and timely infant care.

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