Evidence map›Paper›PMID 34187217›Full record

ArticleThe Journal of international medical research2021

The clinical guiding value of a radiomics model for androgen deprivation therapy for prostate cancer.

Na Yu, Baoping Wang, Jialiang Ren, Hui Wu, Yang Gao, Aishi Liu, Guangming Niu

Open access · goldAbstract read
In one paragraph

Article in The Journal of international medical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 49% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Biomarkers in Localized Prostate Cancer: From Diagnosis to Treatment.International journal of molecular sciences · 2025
    Review
  3. 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

7 authors at 2 institutions in 1 country.

Na YuDepartment of Imaging Diagnosis, The Fifth People's Hospital of Datong, Datong, Shanxi Province, China.ORCID https://orcid.org/0000-0002-8716-6454
Baoping WangDepartment of Imaging Diagnosis, The Fifth People's Hospital of Datong, Datong, Shanxi Province, China.
Jialiang RenGeneral Electric Pharmaceutical (Shanghai), Beijing, China.
Hui WuDepartment of Imaging Diagnosis, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.ORCID https://orcid.org/0000-0002-1620-5321
Yang GaoDepartment of Imaging Diagnosis, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.
Aishi LiuDepartment of Imaging Diagnosis, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.
Guangming NiuDepartment of Imaging Diagnosis, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, China.
Inner Mongolia Medical University · CNShanxi Datong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThree models were used to evaluate prostate cancer after androgen deprivation therapy (ADT) and to determine the value of detecting residual lesions after treatment.

methodsWe retrospectively analysed patients with prostate cancer who received ADT from January 2018 to June 2019. Patients were divided into ADT responder and ADT non-responder groups, and clinical risk factors were determined. Regions of interest were manually contoured on each slice on fat-saturated-T2-weighted imaging, and radiomic features were extracted. Uni- and multivariate logistic regression were used to establish radiomics, clinical and combined models.

resultsThere were 23 ADT non-responders and 20 ADT responders. In the clinical model, total prostate-specific antigen concentration and T stage were independent predictors of efficacy (area under the curve (AUC) = 0.774). The characteristics, MinIntensity and Correlation_ angle135_offset4 indicated an effective clinical model (AUC = 0.807). GLCMEntropy_ AllDirection_offset1_SD was the best feature to differentiate residual lesions from the central gland (CG) (Lesion-CG model, AUC = 0.955). Correlation_angle135_offset4, GLCMEntropy_ AllDirection_offset4_SD and GLCMEntropy_AllDirection_offset7_SD differentiated residual lesions from the peripheral zone (PZ) (Lesion-PZ model, AUC = 0.855). The AUC for the combined model was 0.904.

conclusionsOur models can guide the clinical treatment of patients with different ADT responses. Furthermore, the radiomics model can detect prostate cancer that is non-responsive to ADT.

Indexed as

Prostatic NeoplasmsAndrogen AntagonistsAndrogensHumansMagnetic Resonance ImagingMaleRetrospective StudiesAndrogen AntagonistsAndrogensandrogen deprivation treatmentclinical modellogistic regression analysismagnetic resonance imagingprostate cancerRadiomics

Identifiers

PMID34187217
PMCPMC8258766
OpenAlexW3176993273

What OpenQuestion holds

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LicenceCC BY-NC
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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.