Evidence map›Paper›PMID 37831385›Full record

ArticleInternational urology and nephrology2024

Development and validation of a model for predicting the risk of prostate cancer.

Ya-Dong Li, Zheng-Ju Ren, Yuan-Qing Gou, Wei-Tan, Chuan Liu, Liang Gao

Abstract read
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In one paragraph

Article in International urology and nephrology, 2024. 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
0.3field-weighted citation impact, top 35% 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, 1 citations in OpenAlex.

  1. Overdiagnosis and Overtreatment in Prostate Cancer.Diseases (Basel, Switzerland) · 2025
    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

6 authors at 1 institution in 1 country.

Ya-Dong Li *Department of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Zheng-Ju Ren *Department of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Yuan-Qing GouDepartment of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Wei-TanDepartment of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Chuan LiuDepartment of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China. liuchuan100@hospital.cqmu.edu.cn.ORCID http://orcid.org/0000-0002-6362-0261
Liang GaoDepartment of Urology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China. gaoliang@cqmu.edu.cn.
Dalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAbnormal hematologic parameters before patients undergoing prostate biopsy play a pivotal role in guiding the surgical management of prostate cancer (PCa) incidence. This study aims to establish the first nomogram for predicting PCa risk for better surgical management.

methodsWe retrospectively reviewed and analyzed the data including basic information, preoperative hematologic parameters, and imaging examination of 540 consecutive patients who underwent transrectal ultrasound (TRUS)-guided prostate biopsy for elevated prostate-specific antigen (PSA) in our medical center between 2017 and 2021. Logistic regression analysis was used to determine the risk factors for PCa occurrence, and the nomogram was constructed to predict PCa occurrence. Finally, the data including 121 consecutive patients in 2022 were prospectively collected to further verify the results.

resultsIn retrospective analyses, univariate and multivariate logistic analyses identified that three variables including age, diabetes, and De Ritis ratio (aspartate transaminase/alanine transaminase, AST/ALT) were determined to be significantly associated with PCa occurrence. A nomogram was constructed based on these variables for predicting the risk of PCa, and a satisfied predictive accuracy of the model was determined with a C-index of 0.765, supported by a prospective validation group with a C-index of 0.736. The Decision curve analysis showed promising clinical application. In addition, our results also showed that the De Ritis ratio was significantly correlated with the clinical stage of PCa patients, including T, N, and M stages, but insignificantly related to the Gleason score.

conclusionsThe increased De Ritis ratio was significantly associated with the risk and clinical stage of PCa and this nomogram with good discrimination could effectively improve individualized surgical management for patient underdoing prostate biopsy.

Indexed as

Prostatic NeoplasmsHumansMaleNomogramsProstateProstate-Specific AntigenRetrospective StudiesRisk FactorsProstate-Specific AntigenDe Ritis ratioHematologic parametersNomogramProstate cancer

Identifiers

PMID37831385
OpenAlexW4387599390

What OpenQuestion holds

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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.