Evidence map›Paper›PMID 34017065›Full record

ReviewModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc2021

Pituitary neuroendocrine tumors: a model for neuroendocrine tumor classification.

Sylvia L Asa, Ozgur Mete, Michael D Cusimano, Ian E McCutcheon, Arie Perry, Shozo Yamada, Hiroshi Nishioka, Olivera Casar-Borota, Silvia Uccella, Stefano La Rosa and 3 more

Registry-linked trialAbstract readReview
PubMed Publisher
In one paragraph

Review in Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06523582 (Genetic Bases of Neuroendocrine Neoplasms in Mexican Patients), which is not on this map. Cited by 55 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 1 pooled it
9.1field-weighted citation impact, top 1% of its field
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.

NCT06523582 recruitingnot on this mapstarted 2022, after this paper: background citation

Genetic Bases of Neuroendocrine Neoplasms in Mexican Patients

TypeobservationalSponsorUniversidad Nacional Autonoma de MexicoRan2022 to 2037Enrolled750ConditionsNeuroendocrine Neoplasm, Neuroendocrine Neoplasm of Gastrointestinal Tract, Neuroendocrine Neoplasm of Lung, Thymic Neuroendocrine Neoplasm
3 · Its place in the literature

Who cites it

55 citing papers in PubMed, 1 synthesis or guideline pooled it, 82 citations in OpenAlex.

  1. Pooled it
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  8. Development and validation of a machine learning model based on interpretable clinical characteristics for preoperative prediction of Ki-67 expression in pituitary adenomas.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
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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

13 authors at 20 institutions in 11 countries.

Sylvia L AsaDepartment of Pathology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH, USA. Pathlady01@gmail.com.ORCID 0000-0001-8418-5054
Ozgur MeteDepartment of Pathology, University Health Network, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-0469-2801
Michael D CusimanoDepartment of Neurosurgery, Saint Michael's Hospital, University of Toronto, Toronto, ON, Canada.
Ian E McCutcheonDepartment of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Arie PerryDepartment of Pathology, University of California San Francisco, San Francisco, CA, USA.ORCID 0000-0002-8300-7261
Shozo YamadaHypothalamic and Pituitary Center, Moriyama Neurological Center Hospital, Tokyo, Japan.
Hiroshi NishiokaDepartment of Hypothalamic and Pituitary Surgery, Toranomon Hospital, Tokyo, Japan.
Olivera Casar-BorotaDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Silvia UccellaDepartment of Pathology, University of Insubria, Varese, Italy.
Stefano La RosaInstitute of Pathology, University Hospital and University of Lausanne, Lausanne, Switzerland.
Ashley B Grossman *Department of Endocrinology, University of Oxford, London, UK.
Shereen Ezzat *Department of Medicine, University Health Network, University of Toronto, Toronto, ON, Canada.
Attendees of the 15th Meeting of the International Pituitary Pathology Club, Istanbul October 2019
Istanbul University-Cerrahpaşa · TRUniversity Health Network · CAHôpital Orthopédique de la Suisse Romande · CHThe University of Sydney · AUColumbia University Irving Medical Center · USMarmara University · TRSt. Michael's Hospital · CAThe Royal Free Hospital · GBThe University of Texas MD Anderson Cancer Center · USTohoku University · JPToranomon Hospital · JPUniversität Hamburg · DEUniversity Hospitals of Cleveland · USUniversity of Belgrade · RSUniversity of Bologna · ITUniversity of California, San Francisco · USUniversity of Insubria · ITUniversity of Lausanne · CHUniversity of Manchester · GBUppsala University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The classification of adenohypophysial neoplasms as "pituitary neuroendocrine tumors" (PitNETs) was proposed in 2017 to reflect their characteristics as epithelial neuroendocrine neoplasms with a spectrum of clinical behaviors ranging from small indolent lesions to large, locally invasive, unresectable tumors. Tumor growth and hormone hypersecretion cause significant morbidity and mortality in a subset of patients. The proposal was endorsed by a WHO working group that sought to provide a unified approach to neuroendocrine neoplasia in all body sites. We review the features that are characteristic of neuroendocrine cells, the epidemiology and prognosis of these tumors, as well as further refinements in terms used for other pituitary tumors to ensure consistency with the WHO framework. The intense study of PitNETs has provided information about the importance of cellular differentiation in tumor prognosis as a model for neuroendocrine tumors in different locations.

Indexed as

HumansNeuroendocrine TumorsPituitary Neoplasms

Identifiers

PMID34017065
OpenAlexW3160359312

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.