Evidence map›Paper›PMID 40448416›Full record

ArticleJournal of clinical laboratory analysis2025

Significance of Inflammation Markers to Predict Curative Treatment for Prostate Cancer Patients on Active Surveillance.

Yenigürbüz Serkan, Ediz Caner, Akan Serkan, Kati Bulent, Vural Yasin, Alcin Adem, Yilmaz Omer

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Article in Journal of clinical laboratory analysis, 2025. 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

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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

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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. 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.

Yenigürbüz SerkanDepartment of Urology, Sultan 2. Abdulhamid Han Education and Research Hospital, Istanbul, Turkey.ORCID https://orcid.org/0000-0002-4862-2103
Ediz CanerDepartment of Urology, Sultan 2. Abdulhamid Han Education and Research Hospital, Istanbul, Turkey.
Akan SerkanDepartment of Urology, Fatih Sultan Mehmet Han Education and Research Hospital, Istanbul, Turkey.
Kati BulentDepartment of Urology, Harran University Hospital, Sanliurfa, Turkey.
Vural YasinDepartment of Urology, Fatih Sultan Mehmet Han Education and Research Hospital, Istanbul, Turkey.
Alcin AdemDepartment of Urology, Sultan 2. Abdulhamid Han Education and Research Hospital, Istanbul, Turkey.
Yilmaz OmerDepartment of Urology, Sultan 2. Abdulhamid Han Education and Research Hospital, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeActive surveillance (AS) strategy aims to avoid unnecessary or excessive early treatment in patients at a low risk for prostate cancer (PCa). However, a biomarker that can predict the need for early curative treatment in patients under AS has not been identified to date. In this study, we aimed to investigate the potential of inflammatory biomarkers in predicting the requirement of curative treatment in the early period in patients under AS. MATERIALS AND

methodsThis study included a total of 83 patients with the diagnosis of PCa and under AS. Patient age, prostate-specific antigen (PSA) level, prostate volume (PV), PSA density (PSAD), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), systemic immune-inflammation index (SII) and follow-up period were compared between the groups.

resultsThere was a significant difference between the two groups in terms of PSAD, NLR, PLR and SII (p = 0.037, p = 0.046, p = 0.008, p = 0.004 and p = 0.005, respectively). The cut-off value determined by performing ROC analysis to evaluate the levels that predict the need for curative treatment before AS was 0.125 for PSAD (sensitivity: 61.8%, specificity: 61.2%), 2.01 for NLR (sensitivity: 67.6%, specificity: 55.1%), 115.49 for PLR (sensitivity: 73.5%, specificity: 59.2%) and 465.40 for SII (sensitivity: 70.6%, specificity: 59.2%).

conclusionsThe analysis of PSAD, NLR, PLR and SII before making the decision to conduct AS can guide clinicians regarding curative treatment in the early period.

Indexed as

Biomarkers, TumorInflammationProstatic NeoplasmsWatchful WaitingAgedHumansLymphocytesMaleMiddle AgedNeutrophilsProstate-Specific AntigenROC CurveBiomarkers, TumorProstate-Specific Antigenactive surveillancebiomarkersinflammation mediatorsprostatic neoplasmstumor

Identifiers

PMID40448416
PMCPMC12217655

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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.