Evidence map›Paper›PMID 36824703›Full record

ArticleEuropean journal of radiology open2023

Value of pre-treatment

Na Wang, Meng Dai, Yan Zhao, Zhaoqi Zhang, Jianfang Wang, Jingmian Zhang, Yingchen Wang, Yunuan Liu, Fenglian Jing, Xinming Zhao

Abstract read
In one paragraph

Article in European journal of radiology open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Na WangDepartment of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China.
Meng DaiDepartment of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China.
Yan ZhaoDepartment of Oncology, The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, China.
Zhaoqi ZhangDepartment of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China.
Jianfang WangDepartment of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China.
Jingmian ZhangDepartment of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China.
Yingchen WangDepartment of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China.
Yunuan LiuDepartment of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China.
Fenglian JingDepartment of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China.
Xinming ZhaoDepartment of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: To investigate the value of radiomics features extracted from pre-treatment Materials and methods: 124 patients with pathologically confirmed stage III-IV CRC who underwent pre-treatment Results: The C-indices of the radiomics model for predicting PFS and OS were 0.712 (95%CI: 0.680-0.744) and 0.758 (0.728-0.789), respectively. In the clinical model, these values were 0.690 (0.664-0.0.717) and 0.738 (0.709-0.767), respectively. However, in the complex model were 0.734 (0.705-0.762) and 0.780 (0.754-0.807), respectively. The Kaplan-Meier curves demonstrated that the radiomics model could effectively separate patients with stage III-IV stage CRC into high- and low-risk groups ( Conclusion: Pre-treatment

Indexed as

18F-FDGColorectal cancerPET/CTPrognosticRadiomicsStage III-IV

Identifiers

PMID36824703
PMCPMC9941411

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.