Evidence map›Paper›PMID 31938662›Full record

ReviewCureus2019

A Practical Approach to the Differential Diagnosis of Intracranial Tumors: Gross, Histology, and Immunoprofile-based Algorithm.

George S Stoyanov, Lilyana Petkova, Deyan L Dzhenkov

Abstract readReview
In one paragraph

Review in Cureus, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Intracranial embryonal neoplasm in an alpaca.Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc · 2023
    Article
  5. 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

3 authors.

George S StoyanovGeneral and Clinical Pathology, Forensic Medicine and Deontology, Medical University of Varna, Varna, BGR.
Lilyana PetkovaGeneral and Clinical Pathology, Forensic Medicine and Deontology, Medical University of Varna, Varna, BGR.
Deyan L DzhenkovGeneral and Clinical Pathology, Forensic Medicine and Deontology, Medical University of Varna, Varna, BGR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intracranial tumors are a diverse group of conditions, both benign and malignant, primary and metastatic and always require detailed medical information, radiological reports and deep knowledge of the histological hallmarks and immunohistochemical profile of different types of tumors and tumor-like processes. Despite it clinically often being possible to differentiate between primary and metastatic tumors, based on the tumor location and age of the patient, histological variants and rare tumor entries should always be considered in the histological differential diagnosis. A thorough diagnostic algorithm based on the location of the tumor and its histological features, together with some common pitfalls in immunohistochemical profiling, based on the 2016 revised World Health Organization (WHO) classification of tumors of the central nervous system should be implemented in all cases. Such an algorithm is especially valuable in cases where only small tumor fragments are sent for morphological evaluation, such as in deep parenchyma tumors. In these instances where only small fragments of the tumor are present for histology, some key features, corresponding to the WHO grade, may easily be missed or underreported. Furthermore, the histological verification of the tumor entry is the first, often overlooked, step in defining the presence or absence of WHO grade-specific mutations.

Indexed as

diagnostic algorithmglioblastomaimmunohistochemistrypathologyscherer figurestumors of the central nervous system

Identifiers

PMID31938662
PMCPMC6957037

What OpenQuestion 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 OpenQuestion graph.