Evidence map›Paper›PMID 33672144›Full record

ReviewInternational journal of environmental research and public health2021

Serum Free Amino Acid Profiling in Differential Diagnosis of Ovarian Tumors-A Comparative Study with Review of the Literature.

Agnieszka Horala, Szymon Plewa, Pawel Derezinski, Agnieszka Klupczynska, Jan Matysiak, Ewa Nowak-Markwitz, Zenon J Kokot

Open access · goldAbstract readReview
In one paragraph

Review in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Enhanced production of l-histidine inSynthetic and systems biotechnology · 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

7 authors at 1 institution in 1 country.

Agnieszka HoralaGynecologic Oncology Department, Poznan University of Medical Sciences, Polna 33 Street, 60-535 Poznan, Poland.
Szymon PlewaDepartment of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland.
Pawel DerezinskiDepartment of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland.
Agnieszka KlupczynskaDepartment of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland.ORCID 0000-0002-5028-1408
Jan MatysiakDepartment of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland.ORCID 0000-0002-9993-1504
Ewa Nowak-MarkwitzGynecologic Oncology Department, Poznan University of Medical Sciences, Polna 33 Street, 60-535 Poznan, Poland.
Zenon J KokotFaculty of Health Sciences, Calisia University, 13 Kaszubska Street, 62-800 Kalisz, Poland.
Poznan University of Medical Sciences · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proper preoperative ovarian cancer (OC) diagnosis remains challenging. Serum free amino acid (SFAA) profiles were investigated to identify potential novel biomarkers of OC and assess their performance in ovarian tumor differential diagnosis. Serum samples were divided based on the histopathological result: epithelial OC (

Indexed as

Ovarian NeoplasmsTandem Mass SpectrometryAmino AcidsBiomarkers, TumorDiagnosis, DifferentialFemaleHumansROC CurveAmino AcidsBiomarkers, Tumoramino acidsbiomarkermetabolic profilingmetabolomicsovarian cancerovarian neoplasmovarian tumour

Identifiers

PMID33672144
PMCPMC7926859
OpenAlexW3107011746

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.