Evidence map›Paper›PMID 36983295›Full record

ArticleJournal of clinical medicine2023

Association between Preoperative 18-FDG PET-CT SUVmax and Next-Generation Sequencing Results in Postoperative Ovarian Malignant Tissue in Patients with Advanced Ovarian Cancer.

Jung Min Ryu, Yoon Young Jeong, Sun-Jae Lee, Byung Wook Choi, Youn Seok Choi

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 96% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 1 institution in 1 country.

Jung Min RyuDepartment of Obstetrics and Gynecology, School of Medicine, Daegu Catholic University, Daegu 42472, Repulic of Korea.ORCID 0000-0003-0125-9754
Yoon Young JeongDepartment of Obstetrics and Gynecology, School of Medicine, Daegu Catholic University, Daegu 42472, Repulic of Korea.ORCID 0000-0001-7434-4541
Sun-Jae LeeDepartment of Pathology, School of Medicine, Daegu Catholic University, Daegu 42472, Repulic of Korea.ORCID 0000-0002-8552-6049
Byung Wook ChoiDepartment of Nuclear Medicine, School of Medicine, Daegu Catholic University, Daegu 42472, Repulic of Korea.ORCID 0000-0002-7191-0007
Youn Seok ChoiDepartment of Obstetrics and Gynecology, School of Medicine, Daegu Catholic University, Daegu 42472, Repulic of Korea.ORCID 0000-0001-8901-9434
Daegu Catholic University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigated the association between maximum standardized uptake values (SUVmax) on preoperative 18-FDG PET-CT and next-generation sequencing (NGS) results in post-surgical ovarian malignant tissue in patients with advanced ovarian cancer. Twenty-five patients with stage IIIC or IV ovarian cancer who underwent both preoperative 18-FDG PET-CT and postoperative NGS for ovarian malignancies were retrospectively enrolled. Two patients had no detected variants, 21 of the 23 patients with any somatic variant had at least one single nucleotide variant (SNV) or insertion/deletion (indel), 10 patients showed copy number variation (CNV), and two patients had a fusion variant. SUVmax differed according to the presence of SNVs/indels, with an SUVmax of 13.06 for patients with ≥ 1 SNV/indel and 6.28 for patients without (

Indexed as

insertions and deletionsnext-generation sequencingovarian cancersingle nucleotide variantsSUVmaxTP53

Identifiers

PMID36983295
PMCPMC10057491
OpenAlexW4327621006

What OpenQuestion holds

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LicenceCC BY
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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.