Evidence mapPaperPMID 39928792Full record

ReviewMedicine2025

Ovarian cancer causing hyperprolactinemia: A case report and narrative review.

Sandra Šakinienė, Džilda Veličkienė

Abstract readCase ReportsReview
In one paragraph

Review in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Sandra ŠakinienėDepartment of Endocrinology, Hospital of Lithuanian University of Health Sciences Kaunas Clinics, Kaunas, Lithuania.ORCID 0009-0006-6340-6544
Džilda VeličkienėDepartment of Endocrinology, Hospital of Lithuanian University of Health Sciences Kaunas Clinics, Kaunas, Lithuania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The most common cause of hyperprolactinemia is prolactinoma. In addition, it is necessary to exclude potential physiological and pharmacological factors as well as health disorders to determine the cause of hyperprolactinemia. However, few studies have linked elevated prolactin (PRL) levels to ovarian cancer (OC). OC cells can ectopically release PRL, which then attaches to PRL receptors (PRLRs) in ovarian tissue and initiates signaling cascades that induce OC carcinogenesis. Therefore, we can consider PRL as a biomarker or tumorigenesis factor for OC. Furthermore, both PRL and PRLRs are potential therapeutic targets. A 50-year-old female presented with complaints of breast enlargement, soreness, and hyperprolactinemia, in addition to advanced OC. Hyperprolactinemia along with advanced high-grade serous ovarian carcinoma. Due to the patient's fear of confined spaces, magnetic resonance imaging of the pituitary gland under general anesthesia was prescribed to rule out pituitary pathology. Magnetic resonance imaging was not performed due to the deterioration of the underlying condition, and the patient died 2.5 years after the diagnosis of OC. Hyperprolactinemia caused by OC is a rare condition for which there is a lack of literature and case studies. PRL produced by OC tissue binds to PRLRs in an autocrine or paracrine manner, initiating signaling cascades that induce OC tumorigenesis. In combination with other biomarkers, PRL may serve as a biomarker for OC. To establish the relation between OC and elevated PRL levels, additional large-scale population studies are required, with diagnostic and treatment procedures coming first.

Indexed as

HyperprolactinemiaOvarian NeoplasmsProlactinBiomarkers, TumorFatal OutcomeFemaleHumansMagnetic Resonance ImagingMiddle AgedPituitary GlandBiomarkers, TumorProlactin

Identifiers

PMID39928792
PMCPMC11813068

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.