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

Bianca M. Leca, Maria Mytilinaiou, Marina Tsoli, Andreea Epure, Simon J.B. Aylwin, Gregory Kaltsas, Harpal S. Randeva, Georgios K. Dimitriadis*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Article number9801
JournalScientific Reports
Issue number1
Publication statusPublished - 7 May 2021

Bibliographical note

Copyright: © 2021, The Author(s). Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit

Funding: National Institute for Health Research (NIHR), South London Clinical Research Network (CRN) “Green shoots” Investigator Award supported Dr Dimitriadis in the writing of this manuscript.


  • Endocrine system
  • metabolic diseases
  • endocrinology


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