Evidence map›Paper›PMID 30150569›Full record

ReviewJournal of clinical medicine2018

Risk Stratification on Pheochromocytoma and Paraganglioma from Laboratory and Clinical Medicine.

Noriko Kimura, Kazuhiro Takekoshi, Mitsuhide Naruse

Open access · goldAbstract readReview
In one paragraph

Review in Journal of clinical medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 1 pooled it
11.6field-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.

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

57 citing papers in PubMed, 1 synthesis or guideline pooled it, 86 citations in OpenAlex.

  1. Pooled it
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  19. Case report: A novel somaticFrontiers in endocrinology · 2024
    Article
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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

3 authors at 3 institutions in 1 country.

Noriko KimuraDepartment of Clinical Research Pathology Division, Department of Diagnostic Pathology, National Hospital Organization Hakodate Hospital, Hakodate 041-8512, Hokkaido, Japan. kimura-path@hnh.hosp.go.jp.
Kazuhiro TakekoshiDivision of Sports Medicine, Faculty of Medicine, University of Tsukuba, Tsukuba 305-8575, Japan. k-takemd@md.tsukuba.ac.jp.
Mitsuhide NaruseDepartment of Endocrinology, Metabolism and Hypertension, National Hospital Organization, Kyoto Medical Center, Kyoto 612-8555, Japan. mnaruse@kyotolan.hosp.go.jp.
Hakodate National Hospital · JPKyoto Medical Center · JPUniversity of Tsukuba · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pheochromocytoma (PCC) and sympathetic paraganglioma (PGL) are rare neuroendocrine tumors characterized by catecholamine production in the adrenal medulla and extra-adrenal paraganglia. PCC and PGL (PPGL) with metastasis was termed malignant PPGL. However, the distinction between "benign" and "malignant" PPGLs has been debated. Currently, all PPGLs are believed to have some metastatic potential and are assigned malignant tumors (ICD-O/3) by the WHO Classification of Endocrine Organs (2017, 4th edition). Therefore, the previous categories benign and malignant PPGL have been eliminated in favor of risk stratification approach. The Grading of Adrenal Pheochromocytoma and Paraganglioma (GAPP) is a tool for risk stratification for predicting metastasis and the prognosis of patients. At least 30% of PPGLs are hereditary, with 20 genes identified and genotype-phenotype correlations clarified. Of these genes,

Indexed as

catecholaminediagnosisGAPPgene mutationimmunohistochemistrymetastasisparagangliomapathologypheochromocytomaprognosis

Identifiers

PMID30150569
PMCPMC6162838
OpenAlexW2884790729

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.