Evidence map›Paper›PMID 40002269›Full record

ReviewCancers2025

Double PitNETs: A Case Report and Literature Review.

Mitsuru Nishiyama, Noriaki Fukuhara, Hiroshi Nishioka, Shozo Yamada

Abstract readReview
In one paragraph

Review in Cancers, 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. Article
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

4 authors.

Mitsuru NishiyamaDepartment of Endocrinology, Metabolism and Nephrology, Kochi Medical School, Kochi University, 1-185, Kohasu, Oko-cho, Nankoku City 783-8505, Kochi, Japan.ORCID 0000-0003-4417-7476
Noriaki FukuharaDepartment of Hypothalamic and Pituitary Surgery, Toranomon Hospital, Minato-ku, Tokyo 105-8470, Japan.
Hiroshi NishiokaDepartment of Hypothalamic and Pituitary Surgery, Toranomon Hospital, Minato-ku, Tokyo 105-8470, Japan.
Shozo YamadaDepartment of Hypothalamic and Pituitary Surgery, Toranomon Hospital, Minato-ku, Tokyo 105-8470, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Double pituitary neuroendocrine tumors (double PitNETs) are two distinct tumors in the same gland and are infrequent in clinical practice. In typical double PitNETs, an MRI detects two separate tumors that are diagnosed by pathology; they could also appear as a single tumor, and pathology would then identify the two independent tumors. A literature review was conducted, and 142 cases were analyzed to determine the characteristics of double PitNETs. Of these cases, acromegaly (45.5%) was the most common clinical feature, followed by Cushing's disease (35.1%) and prolactinoma (17.9%), indicating that double PitNETs are usually noticed by hormonal excess symptoms due to at least one functional tumor. The pathological analysis of 284 tumors showed that somatotroph (28.9%) and corticotroph (26.8%) tumors were predominant, with a recent increase in the proportion of gonadotroph tumors. Regarding transcription factors, 51.1% were of GH-PRL-TSH PIT1-lineage, 26.1% ACTH TPIT-lineage, and 17.9% LH-FSH SF1-lineage. The radiological analysis of 82 cases revealed that double tumors (45.1%) and single tumors (47.6%) were comparable, suggesting that double PitNETs are often detected as a single tumor, and attention should be paid to hidden micro-tumors during surgery. Double PitNETs are complicated by a wide variety of clinical, radiological, and pathological findings, but diagnostic and therapeutic approaches are advancing.

Indexed as

acromegalyCushing’s diseasedouble pituitary adenomadouble pituitary neuroendocrine tumor (PitNET)non-functioning pituitary tumorprolactinomaTSH-producing tumor

Identifiers

PMID40002269
PMCPMC11853428

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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 OpenQuestion graph.