Identification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis

Abstract Prolactinomas represent the most common type of secretory pituitary neoplasms, with a therapeutic management that varies considerably based on tumour size and degree of hyperprolactinemia. The aim of the current study was to evaluate the relationship between serum prolactin (PRL) concentrat...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Bianca M. Leca, Maria Mytilinaiou, Marina Tsoli, Andreea Epure, Simon J. B. Aylwin, Gregory Kaltsas, Harpal S. Randeva, Georgios K. Dimitriadis
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3d1f5a9291d64e33bc4fcb33f13e7454
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:3d1f5a9291d64e33bc4fcb33f13e7454
record_format	dspace
spelling	oai:doaj.org-article:3d1f5a9291d64e33bc4fcb33f13e74542021-12-02T16:49:07ZIdentification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis10.1038/s41598-021-89256-72045-2322https://doaj.org/article/3d1f5a9291d64e33bc4fcb33f13e74542021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89256-7https://doaj.org/toc/2045-2322Abstract Prolactinomas represent the most common type of secretory pituitary neoplasms, with a therapeutic management that varies considerably based on tumour size and degree of hyperprolactinemia. The aim of the current study was to evaluate the relationship between serum prolactin (PRL) concentrations and prolactinoma size, and to determine a cut-off PRL value that could differentiate micro- from macro-prolactinomas. A retrospective cohort study of 114 patients diagnosed with prolactinomas between 2007 and 2017 was conducted. All patients underwent gadolinium enhanced pituitary MRI and receiver operating characteristic (ROC) analyses were performed. 51.8% of patients in this study were men, with a mean age at the time of diagnosis of 42.32 ± 15.04 years. 48.2% of the total cohort were found to have microadenomas. Baseline serum PRL concentrations were strongly correlated to tumour dimension (r = 0.750, p = 0.001). When performing the ROC curve analysis, the area under the curve was 0.976, indicating an excellent accuracy of the diagnostic method. For a value of 204 μg/L (4338 mU/L), sensitivity and specificity were calculated at 0.932 and 0.891, respectively. When a cut off value of 204 μg/L (4338 mU/L) was used, specificity was 93.2%, and sensitivity 89.1%, acceptable to reliably differentiate between micro- and macro- adenomas.Bianca M. LecaMaria MytilinaiouMarina TsoliAndreea EpureSimon J. B. AylwinGregory KaltsasHarpal S. RandevaGeorgios K. DimitriadisNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-7 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Bianca M. Leca Maria Mytilinaiou Marina Tsoli Andreea Epure Simon J. B. Aylwin Gregory Kaltsas Harpal S. Randeva Georgios K. Dimitriadis Identification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis
description	Abstract Prolactinomas represent the most common type of secretory pituitary neoplasms, with a therapeutic management that varies considerably based on tumour size and degree of hyperprolactinemia. The aim of the current study was to evaluate the relationship between serum prolactin (PRL) concentrations and prolactinoma size, and to determine a cut-off PRL value that could differentiate micro- from macro-prolactinomas. A retrospective cohort study of 114 patients diagnosed with prolactinomas between 2007 and 2017 was conducted. All patients underwent gadolinium enhanced pituitary MRI and receiver operating characteristic (ROC) analyses were performed. 51.8% of patients in this study were men, with a mean age at the time of diagnosis of 42.32 ± 15.04 years. 48.2% of the total cohort were found to have microadenomas. Baseline serum PRL concentrations were strongly correlated to tumour dimension (r = 0.750, p = 0.001). When performing the ROC curve analysis, the area under the curve was 0.976, indicating an excellent accuracy of the diagnostic method. For a value of 204 μg/L (4338 mU/L), sensitivity and specificity were calculated at 0.932 and 0.891, respectively. When a cut off value of 204 μg/L (4338 mU/L) was used, specificity was 93.2%, and sensitivity 89.1%, acceptable to reliably differentiate between micro- and macro- adenomas.
format	article
author	Bianca M. Leca Maria Mytilinaiou Marina Tsoli Andreea Epure Simon J. B. Aylwin Gregory Kaltsas Harpal S. Randeva Georgios K. Dimitriadis
author_facet	Bianca M. Leca Maria Mytilinaiou Marina Tsoli Andreea Epure Simon J. B. Aylwin Gregory Kaltsas Harpal S. Randeva Georgios K. Dimitriadis
author_sort	Bianca M. Leca
title	Identification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis
title_short	Identification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis
title_full	Identification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis
title_fullStr	Identification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis
title_full_unstemmed	Identification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis
title_sort	identification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3d1f5a9291d64e33bc4fcb33f13e7454
work_keys_str_mv	AT biancamleca identificationofanoptimalprolactinthresholdtodetermineprolactinomasizeusingreceiveroperatingcharacteristicanalysis AT mariamytilinaiou identificationofanoptimalprolactinthresholdtodetermineprolactinomasizeusingreceiveroperatingcharacteristicanalysis AT marinatsoli identificationofanoptimalprolactinthresholdtodetermineprolactinomasizeusingreceiveroperatingcharacteristicanalysis AT andreeaepure identificationofanoptimalprolactinthresholdtodetermineprolactinomasizeusingreceiveroperatingcharacteristicanalysis AT simonjbaylwin identificationofanoptimalprolactinthresholdtodetermineprolactinomasizeusingreceiveroperatingcharacteristicanalysis AT gregorykaltsas identificationofanoptimalprolactinthresholdtodetermineprolactinomasizeusingreceiveroperatingcharacteristicanalysis AT harpalsrandeva identificationofanoptimalprolactinthresholdtodetermineprolactinomasizeusingreceiveroperatingcharacteristicanalysis AT georgioskdimitriadis identificationofanoptimalprolactinthresholdtodetermineprolactinomasizeusingreceiveroperatingcharacteristicanalysis
_version_	1718383390797856768

Identification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis

Ejemplares similares