Evidence map›Paper›PMID 36884114›Full record

Trial reportJournal of cancer research and clinical oncology2023

Standard deviation of CT radiomic features among malignancies in each individual: prognostic ability in lung cancer patients.

Si Hongwei, Hao Xinzhong, Xu Huiqin, Xue Shuqin, Wang Ruonan, Li Li, Cao Jianzhong, Li Sijin

Registry-linked trialOpen access · greenAbstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03648151 (Influence of PET/CT Radiomic Features on the Outcome of Lung Cancer Patients), which is not on this map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 45% 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.

NCT03648151 completednot on this map

Influence of PET/CT Radiomic Features on the Outcome of Lung Cancer Patients

TypeobservationalSponsorThe First Affiliated Hospital of Shanxi Medical UniversityRan2010 to 2019Enrolled1,000ConditionsLung Cancer, Image, Body
3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Review
  2. Review
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.

Si Hongwei *Department of Nuclear Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui Province, China. sihw@163.com.
Hao Xinzhong *Department of Nuclear Medicine, The First Hospital of Shanxi Medical University, Taiyuan, 030001, Shanxi Province, China.
Xu HuiqinDepartment of Medical imaging, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University Health Science Center, 518035, Shenzhen, China.
Xue ShuqinDepartment of Nuclear Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui Province, China.
Wang RuonanDepartment of Nuclear Medicine, The First Hospital of Shanxi Medical University, Taiyuan, 030001, Shanxi Province, China.
Li LiDepartment of Nuclear Medicine, The First Hospital of Shanxi Medical University, Taiyuan, 030001, Shanxi Province, China.
Cao Jianzhong *Department of Radiation Oncology, The Cancer Hospital of Shanxi Province, Taiyuan, 030013, Shanxi Province, China.
Li SijinDepartment of Nuclear Medicine, The First Hospital of Shanxi Medical University, Taiyuan, 030001, Shanxi Province, China.
First Hospital of Shanxi Medical University · CNShanxi Medical University · CNFirst Affiliated Hospital of Anhui Medical University · CNShenzhen University Health Science Center · CN

Funding

Collaborative Innovation Center for Molecular Imaging and Precise D&T Center MP201604Science and Technology project of Health Commission of Anhui Province AHWJ2021b148
6 · The paper itself

Abstract

purposeIt was reported that individual heterogeneity among malignancies (IHAM) might correlate well to the prognosis of lung cancer; however, seldom radiomic study is on this field. Standard deviation (SD) in statistics could scale average amount of variability of a variable; therefore, we used SD of CT feature (Feature

methodsThe enrolled patients who had accepted PET/CT scans were selected from our previous study (ClinicalTrials.gov, NCT03648151). The patients had primary tumor and at least one LN, and standardized uptake value of LN higher than 2.0 and 2.5 were enrolled as the cohort 1 (n = 94) and 2 (n = 88), respectively. Feature

resultsIn the univariate and multi-variate Cox analysis, surgery, target therapy, and TNM stage were significantly against OS in the both cohorts. In the survival XGBoost analysis of the thin-section CT dataset, none Feature

conclusionStandard deviation of CT features among malignant foci within an individual was a powerful prognostic factor in vivo for lung cancer patients.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsClinical Studies as TopicFluorodeoxyglucose F18HumansPositron Emission Tomography Computed TomographyPrognosisRetrospective StudiesFluorodeoxyglucose F18Lung cancerRadiomicsStandard deviationStandard uptake value

Identifiers

PMID36884114
PMCPMC11796657
OpenAlexW4323535215

What OpenQuestion holds

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Registered trials

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.