Evidence map›Paper›PMID 37869094›Full record

ArticleFrontiers in oncology2023

Cohort profile: the Turin prostate cancer prognostication (TPCP) cohort.

Nicolas Destefanis, Valentina Fiano, Lorenzo Milani, Paolo Vasapolli, Michelangelo Fiorentino, Francesca Giunchi, Luca Lianas, Mauro Del Rio, Francesca Frexia, Luca Pireddu and 15 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2023. 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
0.5field-weighted citation impact, top 28% 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

4 citing papers in PubMed, 2 citations in OpenAlex.

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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

25 authors at 7 institutions in 2 countries.

Nicolas DestefanisCancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy.
Valentina FianoCancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy.
Lorenzo MilaniCancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy.
Paolo VasapolliCancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy.
Michelangelo FiorentinoDIMEC Department of Medicine and Surgery, Alma Mater Studiorum, University of Bologna, Bologna, Italy.
Francesca GiunchiDepartment of Pathology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Luca LianasVisual and Data-intensive Computing, CRS4 (Center for Advanced Studies, Research and Development in Sardinia), Pula, Italy.
Mauro Del RioVisual and Data-intensive Computing, CRS4 (Center for Advanced Studies, Research and Development in Sardinia), Pula, Italy.
Francesca FrexiaVisual and Data-intensive Computing, CRS4 (Center for Advanced Studies, Research and Development in Sardinia), Pula, Italy.
Luca PiredduVisual and Data-intensive Computing, CRS4 (Center for Advanced Studies, Research and Development in Sardinia), Pula, Italy.
Luca MolinaroPathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy.
Paola CassoniPathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy.
Mauro Giulio PapottiPathology Unit, Department of Oncology, University of Turin, Turin, Italy.
Paolo GonteroUrology Unit, Department of Surgical Sciences, University of Turin, Molinette Hospital, Turin, Italy.
Giorgio CallerisUrology Unit, Department of Surgical Sciences, University of Turin, Molinette Hospital, Turin, Italy.
Marco OderdaUrology Unit, Department of Surgical Sciences, University of Turin, Molinette Hospital, Turin, Italy.
Umberto RicardiDepartment of Oncology, University of Turin, Turin, Italy.
Giuseppe Carlo IorioDepartment of Oncology, University of Turin, Turin, Italy.
Piero FariselliComputational Biomedicine Unit, Department of Medical Sciences, University of Turin, Turin, Italy.
Elena IsaevskaCancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy.
Olof AkreDepartment of Molecular Medicine and Surgery, Section of Urology, Karolinska Institutet, Stockholm, Sweden.
Renata ZelicDepartment of Molecular Medicine and Surgery, Karolinska Institutet and Department of Pelvic Cancer, Karolinska University Hospital, Stockholm, Sweden.
Andreas PetterssonClinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Daniela ZugnaCancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy.
Lorenzo RichiardiCancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy.
University of Turin · ITCenter for Advanced Studies Research and Development in Sardinia · ITFondazione Ricerca Molinette · ITKarolinska Institutet · SEAzienda USL di Bologna · ITKarolinska University Hospital · SEUniversity of Bologna · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Prostate cancer (PCa) is the most frequent tumor among men in Europe and has both indolent and aggressive forms. There are several treatment options, the choice of which depends on multiple factors. To further improve current prognostication models, we established the Turin Prostate Cancer Prognostication (TPCP) cohort, an Italian retrospective biopsy cohort of patients with PCa and long-term follow-up. This work presents this new cohort with its main characteristics and the distributions of some of its core variables, along with its potential contributions to PCa research. Methods: The TPCP cohort includes consecutive non-metastatic patients with first positive biopsy for PCa performed between 2008 and 2013 at the main hospital in Turin, Italy. The follow-up ended on December 31 Results: The cohort includes 891 patients followed-up for a median time of 10 years. During this period, 97 patients had progression to metastatic disease and 301 died; of these, 56 died from PCa. In total, 65.3% of the cohort has a Gleason score less than or equal to 3 + 4, and 44.5% has a clinical stage cT1. Consistent with previous studies, age and clinical stage at diagnosis are important prognostic factors: the crude cumulative incidence of metastatic disease during the 14-years of follow-up increases from 9.1% among patients younger than 64 to 16.2% for patients in the age group of 75-84, and from 6.1% for cT1 stage to 27.9% in cT3 stage. Discussion: This study stands to be an important resource for updating existing prognostic models for PCa on an Italian cohort. In addition, the integrated collection of multi-modal data will allow development and/or validation of new models including new histopathological, digital, and molecular markers, with the goal of better directing clinical decisions to manage patients with PCa.

Indexed as

digital pathologyDNA methylationprognosisprognostic modellingprostate cancer

Identifiers

PMID37869094
PMCPMC10587560
OpenAlexW4387406958

What OpenQuestion holds

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Registered trials

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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.