Evidence map›Paper›PMID 37576897›Full record

ArticleFrontiers in oncology2023

Radiomic signatures based on pretreatment 18F-FDG PET/CT, combined with clinicopathological characteristics, as early prognostic biomarkers among patients with invasive breast cancer.

Tongtong Jia, Qingfu Lv, Xiaowei Cai, Shushan Ge, Shibiao Sang, Bin Zhang, Chunjing Yu, Shengming Deng

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

8 authors at 4 institutions in 1 country.

Tongtong JiaDepartment of Nuclear Medicine, the First Affiliated Hospital of Soochow University, Suzhou, China.
Qingfu LvDepartment of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Xiaowei CaiDepartment of Nuclear Medicine, The Affiliated Suqian First People's Hospital of Nanjing Medical University, Suqian, China.
Shushan GeDepartment of Nuclear Medicine, the First Affiliated Hospital of Soochow University, Suzhou, China.
Shibiao SangDepartment of Nuclear Medicine, the First Affiliated Hospital of Soochow University, Suzhou, China.
Bin ZhangDepartment of Nuclear Medicine, the First Affiliated Hospital of Soochow University, Suzhou, China.
Chunjing YuDepartment of Nuclear Medicine, Affiliated Hospital of Jiangnan University, Wuxi, China.
Shengming DengDepartment of Nuclear Medicine, the First Affiliated Hospital of Soochow University, Suzhou, China.
First Affiliated Hospital of Soochow University · CNSoochow University · CNNanjing Medical University · CNWuxi Fourth People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The aim of this study was to investigate the predictive role of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ( Methods: We retrospectively enrolled a total of 91 patients who underwent preoperative Results: The Rad-score, age, clinical M stage, and minimum standardized uptake value (SUV Conclusion: The combination of clinicopathological risks and baseline PET/CT-derived Rad-score could be used to evaluate the prognosis in patients with IBC. The predictive nomogram based on the C-R model further enhanced individualized estimation and allowed for more accurate prediction of patient outcomes.

Indexed as

biomarkerbreast cancernomogramPET/CTprognosisradiomic

Identifiers

PMID37576897
PMCPMC10415070
OpenAlexW4385296868

What OpenQuestion holds

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LicenceCC BY
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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.