Parallelism (laboratory test)

Definition of Parallelism for a laboratory test

This section is about parallelism in a specific type of test done in a laboratory. These tests, called quantitative laboratory tests, figure out how much of a substance is in a sample^[1]. For instance, they might measure how much glucose is in a blood sample. No matter the method used, we have to figure out the unknown concentration in the sample by comparing it to a known standard. We do this mathematically using regression analysis. For the mathematics to be right, the serial dilution curve of the substance in the sample has to match up with the dilution curve of the standard. So, in laboratory tests, parallelism means there is a similar relationship between the substance being measured (like a biomarker) and the signal from the standard.

Regulatory authorities

Regulatory authorities such as the Food and Drug Administration (FDA) and European Medicines Agency, (EMA) have made presence of parallelism mandatory for the approval of a test used in medicine and provided guidelines (free download from https://www.ema.europa.eu/en/documents/scientific-guideline/ich-guideline-m10-bioanalytical-method-validation-step-5_en.pdf). These guidelines spell out that "Parallelism demonstrates that the serially diluted incurred sample response curve is parallel to the calibration curve."

Determination of parallelism

Parallelism of a laboratory test can be determined visually or statistically^[2]. Each method has there advantages and limitations. For people without a statistical background the visual assessment is likely more intuitive^[1].

Presence of parallelism

Presence of parallelism is important for the reliable and accurate reporting of data. In routine laboratory practise parallelism can frequently be demonstrated for at least a partial range of the analyte^[3]. Therefore partial parallelism plots give a quick visual answer. An example is given for presence of parallelism comparing the dilution curve of a reference standard with the dilution curve of several samples. All horizontal lines in the figure are parallel between the red vertical reference lines^[2].

Absence of parallelism

Absence of parallelism is a problem because calculations may not be valid. An example for lack of parallelism is shown. The sample dilution curves are not parallel to the horizontal dilution curve of the reference standard.

Absence of paralellism (laboratory test)^[3]

^ ^a ^b Plikaytis, B D; Holder, P F; Pais, L B; Maslanka, S E; Gheesling, L L; Carlone, G M (October 1994). "Determination of parallelism and nonparallelism in bioassay dilution curves". Journal of Clinical Microbiology. 32 (10): 2441–2447. doi:10.1128/jcm.32.10.2441-2447.1994.
^ ^a ^b Pum, Joachim (2019). "A practical guide to validation and verification of analytical methods in the clinical laboratory". Advances in Clinical Chemistry: 215–281. doi:10.1016/bs.acc.2019.01.006.
^ ^a ^b ^c Petzold, Axel (January 2024). "Partial Parallelism Plots". Applied Sciences. 14 (2): 602. doi:10.3390/app14020602.{{cite journal}}: CS1 maint: unflagged free DOI (link)

[:pli-1] Plikaytis, B D; Holder, P F; Pais, L B; Maslanka, S E; Gheesling, L L; Carlone, G M (October 1994). "Determination of parallelism and nonparallelism in bioassay dilution curves". Journal of Clinical Microbiology. 32 (10): 2441–2447. doi:10.1128/jcm.32.10.2441-2447.1994.

[:pum-2] Pum, Joachim (2019). "A practical guide to validation and verification of analytical methods in the clinical laboratory". Advances in Clinical Chemistry: 215–281. doi:10.1016/bs.acc.2019.01.006.

[:ppp-3] Petzold, Axel (January 2024). "Partial Parallelism Plots". Applied Sciences. 14 (2): 602. doi:10.3390/app14020602.{{cite journal}}: CS1 maint: unflagged free DOI (link)

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