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Optimizing laboratory defined macroprolactin algorithm

INTRODUCTION: Macroprolactinaemia is a well-known analytical problem in diagnostics of hyperprolactinaemia usually detected with polyethylene glycol (PEG) precipitation method. Since there is no harmonization in macroprolactin detection and reporting results, this study proposes and evaluates the us...

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Autores principales: Šostarić, Milica, Bokulić, Adriana, Marijančević, Domagoj, Zec, Ivana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Croatian Society of Medical Biochemistry and Laboratory Medicine 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6559613/
https://www.ncbi.nlm.nih.gov/pubmed/31223260
http://dx.doi.org/10.11613/BM.2019.020706
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author Šostarić, Milica
Bokulić, Adriana
Marijančević, Domagoj
Zec, Ivana
author_facet Šostarić, Milica
Bokulić, Adriana
Marijančević, Domagoj
Zec, Ivana
author_sort Šostarić, Milica
collection PubMed
description INTRODUCTION: Macroprolactinaemia is a well-known analytical problem in diagnostics of hyperprolactinaemia usually detected with polyethylene glycol (PEG) precipitation method. Since there is no harmonization in macroprolactin detection and reporting results, this study proposes and evaluates the usefulness of in-house developed algorithm. The aims were to determine the most suitable way of reporting results after PEG treatment and the possibilities of rationalizing the precipitation procedure. MATERIALS AND METHODS: This is a retrospective study based on extracted data for 1136 patients. Prolactin concentrations were measured before and after PEG precipitation on Roche cobas e601. Macroprolactinaemia was defined by percentage recovery and post-PEG prolactin concentrations. RESULTS: Prevalence of macroprolactinaemia using recovery criteria of ≤ 40%, ≤ 60%, and post-PEG prolactin concentrations was 3.3%, 8.8% and 7.8%, respectively. Raising the cut-off value from the upper limit of the manufacturer’s reference interval to 32.9 µg/L does not drastically change detected macroprolactinaemia with recovery criteria. Post-PEG prolactin concentrations showed more than half of the patients with macroprolactinaemia would be overlooked. Regardless of the criteria, a cut-off of 47.0 µg/L would miss most of the macroprolactinaemic patients. Repeated recovery measurements of follow-up patients showed there is a significant difference with mean absolute bias of 9%. CONCLUSIONS: Post-PEG prolactin concentration with corresponding reference interval is the most suitable way of reporting results. All samples with prolactin concentration above the upper limit of the manufacturer’s reference interval should be submitted to PEG precipitation. Follow-up period could be prolonged since the difference between the recoveries of repeated measurements is not clinically significant.
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spelling pubmed-65596132019-06-20 Optimizing laboratory defined macroprolactin algorithm Šostarić, Milica Bokulić, Adriana Marijančević, Domagoj Zec, Ivana Biochem Med (Zagreb) Original Articles INTRODUCTION: Macroprolactinaemia is a well-known analytical problem in diagnostics of hyperprolactinaemia usually detected with polyethylene glycol (PEG) precipitation method. Since there is no harmonization in macroprolactin detection and reporting results, this study proposes and evaluates the usefulness of in-house developed algorithm. The aims were to determine the most suitable way of reporting results after PEG treatment and the possibilities of rationalizing the precipitation procedure. MATERIALS AND METHODS: This is a retrospective study based on extracted data for 1136 patients. Prolactin concentrations were measured before and after PEG precipitation on Roche cobas e601. Macroprolactinaemia was defined by percentage recovery and post-PEG prolactin concentrations. RESULTS: Prevalence of macroprolactinaemia using recovery criteria of ≤ 40%, ≤ 60%, and post-PEG prolactin concentrations was 3.3%, 8.8% and 7.8%, respectively. Raising the cut-off value from the upper limit of the manufacturer’s reference interval to 32.9 µg/L does not drastically change detected macroprolactinaemia with recovery criteria. Post-PEG prolactin concentrations showed more than half of the patients with macroprolactinaemia would be overlooked. Regardless of the criteria, a cut-off of 47.0 µg/L would miss most of the macroprolactinaemic patients. Repeated recovery measurements of follow-up patients showed there is a significant difference with mean absolute bias of 9%. CONCLUSIONS: Post-PEG prolactin concentration with corresponding reference interval is the most suitable way of reporting results. All samples with prolactin concentration above the upper limit of the manufacturer’s reference interval should be submitted to PEG precipitation. Follow-up period could be prolonged since the difference between the recoveries of repeated measurements is not clinically significant. Croatian Society of Medical Biochemistry and Laboratory Medicine 2019-06-15 2019-06-15 /pmc/articles/PMC6559613/ /pubmed/31223260 http://dx.doi.org/10.11613/BM.2019.020706 Text en ©Croatian Society of Medical Biochemistry and Laboratory Medicine. This is an Open Access article distributed under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Šostarić, Milica
Bokulić, Adriana
Marijančević, Domagoj
Zec, Ivana
Optimizing laboratory defined macroprolactin algorithm
title Optimizing laboratory defined macroprolactin algorithm
title_full Optimizing laboratory defined macroprolactin algorithm
title_fullStr Optimizing laboratory defined macroprolactin algorithm
title_full_unstemmed Optimizing laboratory defined macroprolactin algorithm
title_short Optimizing laboratory defined macroprolactin algorithm
title_sort optimizing laboratory defined macroprolactin algorithm
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6559613/
https://www.ncbi.nlm.nih.gov/pubmed/31223260
http://dx.doi.org/10.11613/BM.2019.020706
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