The use of a “gray zone” considering measurement uncertainty in pharmacological tests. The serum growth hormone stimulation test as an example

Lazzati, Juan Manuel; Zaidman, Verónica; Maceiras, Mercedes; Belgorosky, Alicia; Chaler, Eduardo

doi:10.1515/cclm-2015-0954

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…Gray zones have been previously described for Aβ42/p-tau181 measured using INNOTEST ELISAs in patients with dementia, 43 and have also been described in recommendations for the use of CSF in the diagnostic workup of MCI patients. 44 Similar to other areas of medicine, including oncology and cardiology, [45][46][47] recommendations have included that the analysis be repeated or that an imaging-based investigation be performed. The upper and lower boundaries defining the gray zone for a given marker could even be used in the clinical chemistry laboratory providing the CSF results to clinicians, such that a gray zone result would result in immediate re-testing of the sample.…”

Section: Discussionmentioning

confidence: 99%

Robustness of CSF Aβ42/40 and Aβ42/P‐tau181 measured using fully automated immunoassays to detect AD‐related outcomes

Leuzy

Mattsson‐Carlgren

Cullen

et al. 2023

Alzheimer's & Dementia

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Section: Discussionmentioning

confidence: 99%

Robustness of CSF Aβ42/40 and Aβ42/P‐tau181 measured using fully automated immunoassays to detect AD‐related outcomes

Leuzy

Mattsson‐Carlgren

Cullen

et al. 2023

Alzheimer's & Dementia

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show abstract

“…However, the guidelines do not refer to determining the grey zone in reporting illicit substances [14] . The current literature suggests using the grey zone approach to immunologically screen blood donors for infectious diseases and pharmacological tests (such as serum growth hormone stimulation tests) [5] [15] . Coste et al reported that using the grey zone approach in conjunction with the Bland-Altman method should increase reliability [16] .…”

Section: Discussionmentioning

confidence: 99%

“…Several guidelines and recent research have proposed replacing traditional immunoassay methods in urine illicit drug testing with more accurate tests, such as liquid chromatography-tandem mass spectrometry (LC-MS/MS) [15] [17] [18] . However, immunoassays are preferred in routine use for drug testing programs, as they provide rapid results.…”

Section: Discussionmentioning

confidence: 99%

Reducing the need for repeating urine drug testing with the gray zone determined by the measurement uncertainty

et al. 2023

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Background On an initial urine screening test for illegal substances, if the concentration of a substance is at or above the determined legislative threshold, it is reported as positive. Repeat testing with the same sample to verify before reporting is a common practice of clinical laboratories. This study aimed to determine whether measurement uncertainty (MU) results can be used to detect a gray zone to reduce repeat testing. Materials and Methods A retrospective study using data from … ….. …… ……. laboratory information system between 1.January.2020 and 1.July.2022 was conducted. The MU values for urinary amphetamine, cannabinoid, cocaine, and opioid parameters using ADVIA Chemistry reagents (Siemens Healthcare Diagnostic Inc., Germany) on a Siemens ADVIA 1800 chemical analyzer were calculated. The gray zone was defined as the cut-off value ± MU. Samples that were studied twice within one hour before reporting for the same urine sample were analyzed. Results From a total of 31,839 patients’ (16–65 years), urine samples, 319 amphetamine, 198 cannabinoid, 112 cocaine, and 125 opiate tests were repeated. Mean biases between the repeat test results were -7.64 (95% CI: −13.71 to -1.57) for the amphetamine and 1.16 (95% CI: 0.31 to 2.01) for the cannabinoid results. Ten amphetamine, 12 cannabinoid and 2 cocaine test results changed from positive to negative or negative to positive on retesting, all within the gray zone level defined by the MU value. Conclusions It is necessary to define the gray zone around the cut-off value for each illicit substance based on its MU for repeat testing.

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Test‐retest variability of plasma biomarkers in Alzheimer's disease and its effects on clinical prediction models

Cullen

Bateman

Mattsson‐Carlgren

et al. 2022

Alzheimer's & Dementia

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Introduction:The effect of random error on the performance of blood-based biomarkers for Alzheimer's disease (AD) must be determined before clinical implementation. Methods:We measured test-retest variability of plasma amyloid beta (Aβ)42/Aβ40, neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and phosphorylated tau (p-tau)217 and simulated effects of this variability on biomarker performance when predicting either cerebrospinal fluid (CSF) Aβ status or conversion to AD dementia in 399 non-demented participants with cognitive symptoms.Results: Clinical performance was highest when combining all biomarkers. Among single-biomarkers, p-tau217 performed best. Test-retest variability ranged from 4.1% (Aβ42/Aβ40) to 25% (GFAP). This variability reduced the performance of the biomarkers (≈ΔAUC [area under the curve] −1% to −4%) with the least effects on models withThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

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The use of a “gray zone” considering measurement uncertainty in pharmacological tests. The serum growth hormone stimulation test as an example

Abstract: The use of a "grey zone" considering measurement uncertainty in pharmacological tests. The serum growth hormone stimulation test as an example.

Cited by 4 publications

References 8 publications

Robustness of CSF Aβ42/40 and Aβ42/P‐tau181 measured using fully automated immunoassays to detect AD‐related outcomes

Robustness of CSF Aβ42/40 and Aβ42/P‐tau181 measured using fully automated immunoassays to detect AD‐related outcomes

Reducing the need for repeating urine drug testing with the gray zone determined by the measurement uncertainty

Test‐retest variability of plasma biomarkers in Alzheimer's disease and its effects on clinical prediction models

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