Evidence map›Paper›PMID 33917253›Full record

ArticleLife (Basel, Switzerland)2021

Prostate Cancer Diagnostic Algorithm as a "Road Map" from the First Stratification of the Patient to the Final Treatment Decision.

Hana Sedláčková, Olga Dolejšová, Milan Hora, Jiří Ferda, Ondřej Hes, Ondřej Topolčan, Radka Fuchsová, Radek Kučera

Abstract read
In one paragraph

Article in Life (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
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  4. 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.

Hana SedláčkováDepartment of Urology, Faculty of Medicine in Pilsen, University Hospital, 305 99 Pilsen, Czech Republic.ORCID 0000-0001-8827-1750
Olga DolejšováDepartment of Urology, Faculty of Medicine in Pilsen, University Hospital, 305 99 Pilsen, Czech Republic.
Milan HoraDepartment of Urology, Faculty of Medicine in Pilsen, University Hospital, 305 99 Pilsen, Czech Republic.ORCID 0000-0002-5061-3687
Jiří FerdaDepartment of Medical Imaging, Faculty of Medicine in Pilsen, University Hospital, 304 60 Pilsen, Czech Republic.
Ondřej HesDepartment of Pathology, Faculty of Medicine in Pilsen, University Hospital, 305 99 Pilsen, Czech Republic.
Ondřej TopolčanDepartment of Immunochemistry Diagnostics, Faculty of Medicine in Pilsen, University Hospital, 305 99 Pilsen, Czech Republic.
Radka FuchsováDepartment of Immunochemistry Diagnostics, Faculty of Medicine in Pilsen, University Hospital, 305 99 Pilsen, Czech Republic.
Radek KučeraDepartment of Immunochemistry Diagnostics, Faculty of Medicine in Pilsen, University Hospital, 305 99 Pilsen, Czech Republic.ORCID 0000-0002-2739-2302

Funding

BBMRI-CZ: Biobank network - a versatile platform for the research of the etiopathogenesis of diseases CZ.02.1.01/0.0/0.0/16_013/0001674.Ministry of Health, Czech Republic - conceptual development of research organization (Faculty Hospital in Pilsen - FNPl, 00669806) FNPl, 00669806
6 · The paper itself

Abstract

The diagnostics of prostate cancer are currently based on three pillars: prostate biomarker panel, imaging techniques, and histological verification. This paper presents a diagnostic algorithm that can serve as a "road map": from initial patient stratification to the final decision regarding treatment. The algorithm is based on a review of the current literature combined with our own experience. Diagnostic algorithms are a feature of an advanced healthcare system in which all steps are consciously coordinated and optimized to ensure the proper individualization of the treatment process. The prostate cancer diagnostic algorithm was created using the prostate specific antigen and in particular the Prostate Health Index in the first line of patient stratification. It then continued on the diagnostic pathway via imaging techniques, biopsy, or active surveillance, and then on to the treatment decision itself. In conclusion, the prostate cancer diagnostic algorithm presented here is a functional tool for initial patient stratification, comprehensive staging, and aggressiveness assessment. Above all, emphasis is placed on the use of the Prostate Health Index (PHI) in the first stratification of the patients as a predictor of aggressiveness and clinical stage of prostrate cancer (PCa). The inclusion of PHI in the algorithm significantly increases the accuracy and speed of the diagnostic procedure and allows to choose the optimal pathway just from the beginning. The use of advanced diagnostic techniques allows us to move towards to a more advanced level of cancer care. This diagnostics algorithm has become a standard of care in our hospital. The algorithm is continuously validated and modified based on our results.

Indexed as

biopsydiagnosisdiagnostic algorithmGleason scoreimagingmagnetic resonancepositron emission tomographyprostate cancerprostate health indexprostate-specific membrane antigen

Identifiers

PMID33917253
PMCPMC8068075

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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.